install.packages('correlation')the correlation package
This notebook shows you how to use the correlations package as a way to quickly obtain correlation of interest among variables in your data.
You need to first install the package:
After installing the package, load it in along with tidyverse
library(tidyverse)── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.5.1 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.1
✔ purrr 1.0.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(correlation)Warning: package 'correlation' was built under R version 4.4.1Load in some data:
dat <- read_csv('https://raw.githubusercontent.com/scskalicky/scskalicky.github.io/refs/heads/main/sample_dat/psych_distance_nz.csv')Rows: 378 Columns: 39
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): condition, country
dbl (37): emotions1, emotions2, emotions3, emotions4, emotions5, emotions6, ...
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.What is this data? We have a number of variables measuring different related constructs.
glimpse(dat)Rows: 378
Columns: 39
$ emotions1 <dbl> 4, 4, 2, 2, 2, 1, 4, 5, 1, 2, 3, 7, 4, 4, 1, 5, 3,…
$ emotions2 <dbl> 1, 4, 5, 2, 2, 2, 5, 2, 1, 2, 3, 6, 4, 4, 4, 4, 4,…
$ emotions3 <dbl> 4, 6, 5, 1, 2, 4, 4, 6, 5, 5, 3, 5, 4, 4, 2, 4, 2,…
$ emotions4 <dbl> 4, 3, 3, 1, 1, 2, 6, 3, 1, 2, 3, 7, 4, 4, 2, 6, 2,…
$ emotions5 <dbl> 1, 5, 5, 5, 1, 1, 4, 5, 5, 2, 3, 3, 4, 4, 2, 5, 2,…
$ emotions6 <dbl> 1, 2, 5, 1, 1, 3, 5, 5, 1, 1, 3, 3, 4, 4, 2, 5, 5,…
$ emotions7 <dbl> 4, 5, 6, 1, 4, 4, 6, 6, 1, 5, 5, 3, 4, 4, 2, 5, 5,…
$ attention1 <dbl> 7, 6, 3, 5, 6, 6, 4, 7, 7, 6, 6, 7, 6, 6, 6, 5, 7,…
$ attention2 <dbl> 7, 5, 4, 2, 6, 6, 5, 7, 7, 6, 6, 7, 6, 6, 6, 6, 6,…
$ attention3 <dbl> 5, 5, 2, 2, 4, 6, 7, 7, 5, 6, 2, 7, 3, 5, 2, 7, 7,…
$ psychdistance1 <dbl> 5, 6, 6, 1, 6, 6, 5, 6, 7, 7, 5, 4, 6, 4, 3, 5, 2,…
$ psychdistance2 <dbl> 6, 6, 6, 1, 6, 6, 6, 7, 7, 7, 6, 6, 6, 5, 6, 5, 6,…
$ psychdistance3 <dbl> 2, 6, 1, 1, 4, 2, 7, 3, 7, 7, 5, 5, 6, 4, 3, 3, 1,…
$ liking1 <dbl> 3, 4, 4, 1, 4, 6, 5, 7, 3, 7, 3, 4, 2, 3, 2, 6, 6,…
$ liking2 <dbl> 4, 4, 2, 1, 3, 5, 4, 1, 2, 1, 1, 7, 3, 2, 2, 5, 6,…
$ liking3 <dbl> 4, 5, 4, 1, 5, 6, 6, 7, 2, 7, 3, 6, 3, 5, 2, 5, 6,…
$ liking4 <dbl> 2, 2, 2, 1, 2, 2, 5, 1, 2, 2, 1, 6, 3, 1, 2, 4, 4,…
$ liking5 <dbl> 2, 2, 4, 1, 2, 2, 4, 1, 2, 1, 1, 6, 1, 1, 2, 5, 4,…
$ humor1 <dbl> 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 4, 1, 2, 2, 3, 6,…
$ humor2 <dbl> 3, 5, 2, 1, 1, 2, 4, 1, 2, 1, 1, 6, 2, 1, 3, 4, 6,…
$ humor3 <dbl> 2, 4, 1, 1, 1, 3, 4, 1, 2, 1, 1, 6, 2, 3, 3, 4, 6,…
$ aversiveness <dbl> 4, 5, 5, 5, 1, 2, 4, 7, 5, 7, 3, 3, 1, 4, 2, 4, 6,…
$ messagediscounting1 <dbl> 5, 3, 2, 6, 1, 2, 2, 1, 1, 1, 6, 2, 1, 1, 4, 2, 2,…
$ messagediscounting2 <dbl> 4, 5, 2, 4, 1, 2, 6, 1, 2, 1, 6, 3, 3, 5, 5, 5, 3,…
$ messagediscounting3 <dbl> 5, 7, 4, 7, 4, 2, 2, 2, 3, 1, 6, 2, 3, 3, 5, 6, 3,…
$ messagediscounting4 <dbl> 5, 5, 2, 6, 2, 2, 5, 1, 1, 1, 7, 2, 1, 2, 7, 6, 6,…
$ attitudepositive1 <dbl> 3, 2, 3, 7, 4, 6, 4, 3, 5, 2, 6, 6, 5, 5, 4, 7, 6,…
$ attitudepositive2 <dbl> 3, 1, 3, 7, 5, 6, 1, 2, 3, 2, 6, 5, 5, 5, 4, 6, 6,…
$ attitudepositive3 <dbl> 5, 2, 3, 7, 2, 6, 1, 2, 2, 2, 6, 6, 5, 3, 4, 4, 4,…
$ attitudenegative1 <dbl> 5, 6, 6, 2, 3, 2, 7, 6, 3, 7, 1, 6, 3, 3, 1, 1, 3,…
$ attitudenegative2 <dbl> 5, 7, 5, 3, 3, 3, 6, 5, 5, 7, 2, 6, 3, 5, 2, 2, 2,…
$ attitudenegative3 <dbl> 5, 6, 2, 2, 5, 2, 7, 6, 6, 7, 5, 6, 3, 5, 2, 4, 4,…
$ age <dbl> 37, 20, 37, 24, 27, 27, 26, 71, 41, 32, 42, 29, 34…
$ newsconsumption1 <dbl> 5, 3, 3, 1, 2, 3, 5, 5, 1, 3, 2, 4, 3, 2, 2, 3, 3,…
$ newsconsumption2 <dbl> 5, 5, 3, 2, 5, 5, 6, 5, 4, 4, 1, 5, 4, 4, 4, 5, 3,…
$ newsconsumption3 <dbl> 4, 4, 2, 1, 4, 4, 2, 2, 1, 1, 4, 6, 5, 2, 2, 2, 3,…
$ newsconsumption4 <dbl> 4, 5, 1, 4, 4, 4, 2, 2, 1, 1, 4, 4, 5, 5, 4, 3, 3,…
$ condition <chr> "sat", "sat", "sat", "reg", "reg", "sat", "reg", "…
$ country <chr> "NZ", "UK", "NZ", "NZ", "NZ", "NZ", "UK", "UK", "N…What might want to obtain correlations of these variables, but only for certain categories (e.g., seeing how strongly the emotion measures correlate internally).
How can we do this? One method is to perform individual correlations one-by-one:
cor.test(dat$emotions1, dat$emotions2)
Pearson's product-moment correlation
data: dat$emotions1 and dat$emotions2
t = 12.063, df = 376, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.4513958 0.5972595
sample estimates:
cor
0.5282135 Well, doing that would take a long time! The correlation package is one way to increase the efficiency of this process.
You can read how to use it all on the official documentation, so here I will cover just some basics to get us started.
Running correlations on the entire data set
You can use the function to calculate correlations among every variable in the data quite easily. Notice that this provides every possible correlation to every other possible variable!
correlation(dat)# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI
----------------------------------------------------------------------
emotions1 | emotions2 | 0.53 | [ 0.45, 0.60]
emotions1 | emotions3 | 0.38 | [ 0.29, 0.47]
emotions1 | emotions4 | 0.55 | [ 0.47, 0.61]
emotions1 | emotions5 | 0.11 | [ 0.01, 0.21]
emotions1 | emotions6 | 0.03 | [-0.07, 0.13]
emotions1 | emotions7 | 0.03 | [-0.08, 0.13]
emotions1 | attention1 | -0.04 | [-0.14, 0.06]
emotions1 | attention2 | 9.30e-03 | [-0.09, 0.11]
emotions1 | attention3 | 0.18 | [ 0.08, 0.28]
emotions1 | psychdistance1 | 0.07 | [-0.03, 0.17]
emotions1 | psychdistance2 | -0.03 | [-0.13, 0.07]
emotions1 | psychdistance3 | 0.11 | [ 0.01, 0.21]
emotions1 | liking1 | 0.03 | [-0.07, 0.13]
emotions1 | liking2 | 0.42 | [ 0.33, 0.50]
emotions1 | liking3 | 0.21 | [ 0.11, 0.31]
emotions1 | liking4 | 0.37 | [ 0.28, 0.45]
emotions1 | liking5 | 0.39 | [ 0.30, 0.47]
emotions1 | humor1 | 0.11 | [ 0.01, 0.20]
emotions1 | humor2 | 0.12 | [ 0.02, 0.22]
emotions1 | humor3 | 0.25 | [ 0.15, 0.34]
emotions1 | aversiveness | -0.08 | [-0.18, 0.02]
emotions1 | messagediscounting1 | 0.06 | [-0.05, 0.16]
emotions1 | messagediscounting2 | 0.02 | [-0.08, 0.12]
emotions1 | messagediscounting3 | -0.09 | [-0.18, 0.02]
emotions1 | messagediscounting4 | 2.42e-03 | [-0.10, 0.10]
emotions1 | attitudepositive1 | 0.07 | [-0.03, 0.17]
emotions1 | attitudepositive2 | 0.06 | [-0.04, 0.16]
emotions1 | attitudepositive3 | 0.04 | [-0.06, 0.14]
emotions1 | attitudenegative1 | -0.02 | [-0.12, 0.08]
emotions1 | attitudenegative2 | 5.02e-03 | [-0.10, 0.11]
emotions1 | attitudenegative3 | -0.05 | [-0.15, 0.05]
emotions1 | age | -0.05 | [-0.15, 0.05]
emotions1 | newsconsumption1 | 0.07 | [-0.03, 0.17]
emotions1 | newsconsumption2 | 0.01 | [-0.09, 0.11]
emotions1 | newsconsumption3 | 0.03 | [-0.07, 0.13]
emotions1 | newsconsumption4 | -0.04 | [-0.14, 0.06]
emotions2 | emotions3 | 0.26 | [ 0.16, 0.35]
emotions2 | emotions4 | 0.47 | [ 0.39, 0.55]
emotions2 | emotions5 | -0.02 | [-0.12, 0.08]
emotions2 | emotions6 | -0.05 | [-0.15, 0.05]
emotions2 | emotions7 | -0.10 | [-0.20, 0.00]
emotions2 | attention1 | -0.10 | [-0.20, 0.00]
emotions2 | attention2 | -0.06 | [-0.16, 0.04]
emotions2 | attention3 | 0.12 | [ 0.01, 0.21]
emotions2 | psychdistance1 | 0.03 | [-0.07, 0.13]
emotions2 | psychdistance2 | 0.01 | [-0.09, 0.11]
emotions2 | psychdistance3 | 0.04 | [-0.06, 0.14]
emotions2 | liking1 | -0.03 | [-0.13, 0.07]
emotions2 | liking2 | 0.31 | [ 0.22, 0.40]
emotions2 | liking3 | 0.13 | [ 0.03, 0.23]
emotions2 | liking4 | 0.30 | [ 0.21, 0.39]
emotions2 | liking5 | 0.35 | [ 0.26, 0.43]
emotions2 | humor1 | 0.11 | [ 0.01, 0.21]
emotions2 | humor2 | 0.12 | [ 0.02, 0.22]
emotions2 | humor3 | 0.26 | [ 0.17, 0.35]
emotions2 | aversiveness | -0.14 | [-0.23, -0.03]
emotions2 | messagediscounting1 | 0.07 | [-0.04, 0.17]
emotions2 | messagediscounting2 | 0.07 | [-0.03, 0.17]
emotions2 | messagediscounting3 | -7.76e-03 | [-0.11, 0.09]
emotions2 | messagediscounting4 | 0.07 | [-0.03, 0.17]
emotions2 | attitudepositive1 | 0.06 | [-0.04, 0.16]
emotions2 | attitudepositive2 | 0.08 | [-0.02, 0.18]
emotions2 | attitudepositive3 | 0.08 | [-0.02, 0.18]
emotions2 | attitudenegative1 | -0.02 | [-0.12, 0.08]
emotions2 | attitudenegative2 | 0.04 | [-0.06, 0.14]
emotions2 | attitudenegative3 | -0.07 | [-0.17, 0.03]
emotions2 | age | -0.12 | [-0.22, -0.02]
emotions2 | newsconsumption1 | -0.02 | [-0.12, 0.08]
emotions2 | newsconsumption2 | 0.02 | [-0.08, 0.12]
emotions2 | newsconsumption3 | 0.06 | [-0.04, 0.16]
emotions2 | newsconsumption4 | 0.02 | [-0.08, 0.12]
emotions3 | emotions4 | 0.35 | [ 0.25, 0.43]
emotions3 | emotions5 | 0.34 | [ 0.25, 0.43]
emotions3 | emotions6 | 0.13 | [ 0.03, 0.23]
emotions3 | emotions7 | 0.30 | [ 0.21, 0.39]
emotions3 | attention1 | -0.03 | [-0.13, 0.07]
emotions3 | attention2 | 0.02 | [-0.09, 0.12]
emotions3 | attention3 | 0.21 | [ 0.11, 0.30]
emotions3 | psychdistance1 | 0.19 | [ 0.09, 0.28]
emotions3 | psychdistance2 | 0.03 | [-0.07, 0.13]
emotions3 | psychdistance3 | 0.25 | [ 0.15, 0.34]
emotions3 | liking1 | 0.11 | [ 0.01, 0.21]
emotions3 | liking2 | 0.16 | [ 0.06, 0.25]
emotions3 | liking3 | 0.31 | [ 0.22, 0.40]
emotions3 | liking4 | 0.16 | [ 0.06, 0.26]
emotions3 | liking5 | 0.18 | [ 0.08, 0.28]
emotions3 | humor1 | -0.20 | [-0.30, -0.10]
emotions3 | humor2 | -0.11 | [-0.21, -0.01]
emotions3 | humor3 | 0.04 | [-0.06, 0.14]
emotions3 | aversiveness | 0.18 | [ 0.08, 0.28]
emotions3 | messagediscounting1 | -0.26 | [-0.35, -0.16]
emotions3 | messagediscounting2 | -0.12 | [-0.21, -0.01]
emotions3 | messagediscounting3 | -0.20 | [-0.30, -0.10]
emotions3 | messagediscounting4 | -0.21 | [-0.30, -0.11]
emotions3 | attitudepositive1 | -0.04 | [-0.14, 0.06]
emotions3 | attitudepositive2 | -0.15 | [-0.25, -0.05]
emotions3 | attitudepositive3 | -0.02 | [-0.12, 0.08]
emotions3 | attitudenegative1 | 0.12 | [ 0.02, 0.22]
emotions3 | attitudenegative2 | 0.13 | [ 0.03, 0.23]
emotions3 | attitudenegative3 | 0.07 | [-0.03, 0.17]
emotions3 | age | -0.05 | [-0.15, 0.05]
emotions3 | newsconsumption1 | -0.02 | [-0.12, 0.08]
emotions3 | newsconsumption2 | -0.01 | [-0.11, 0.09]
emotions3 | newsconsumption3 | -0.03 | [-0.13, 0.07]
emotions3 | newsconsumption4 | -0.05 | [-0.15, 0.05]
emotions4 | emotions5 | 0.07 | [-0.04, 0.17]
emotions4 | emotions6 | 0.07 | [-0.03, 0.17]
emotions4 | emotions7 | 0.06 | [-0.04, 0.16]
emotions4 | attention1 | -0.07 | [-0.17, 0.03]
emotions4 | attention2 | 6.08e-03 | [-0.09, 0.11]
emotions4 | attention3 | 0.07 | [-0.03, 0.17]
emotions4 | psychdistance1 | -0.01 | [-0.11, 0.09]
emotions4 | psychdistance2 | -0.04 | [-0.14, 0.06]
emotions4 | psychdistance3 | 0.10 | [ 0.00, 0.20]
emotions4 | liking1 | 2.02e-03 | [-0.10, 0.10]
emotions4 | liking2 | 0.30 | [ 0.20, 0.39]
emotions4 | liking3 | 0.15 | [ 0.05, 0.25]
emotions4 | liking4 | 0.30 | [ 0.20, 0.39]
emotions4 | liking5 | 0.34 | [ 0.25, 0.43]
emotions4 | humor1 | 0.02 | [-0.08, 0.12]
emotions4 | humor2 | 0.04 | [-0.06, 0.14]
emotions4 | humor3 | 0.18 | [ 0.08, 0.28]
emotions4 | aversiveness | 1.80e-03 | [-0.10, 0.10]
emotions4 | messagediscounting1 | -5.82e-03 | [-0.11, 0.10]
emotions4 | messagediscounting2 | 0.02 | [-0.08, 0.12]
emotions4 | messagediscounting3 | -0.06 | [-0.16, 0.04]
emotions4 | messagediscounting4 | -0.06 | [-0.16, 0.04]
emotions4 | attitudepositive1 | 0.13 | [ 0.03, 0.23]
emotions4 | attitudepositive2 | 0.09 | [-0.01, 0.19]
emotions4 | attitudepositive3 | 0.09 | [-0.01, 0.19]
emotions4 | attitudenegative1 | -0.03 | [-0.13, 0.08]
emotions4 | attitudenegative2 | -0.01 | [-0.11, 0.09]
emotions4 | attitudenegative3 | -0.03 | [-0.13, 0.07]
emotions4 | age | 0.03 | [-0.07, 0.13]
emotions4 | newsconsumption1 | -3.50e-03 | [-0.10, 0.10]
emotions4 | newsconsumption2 | -0.03 | [-0.13, 0.07]
emotions4 | newsconsumption3 | -0.04 | [-0.14, 0.06]
emotions4 | newsconsumption4 | -0.07 | [-0.17, 0.03]
emotions5 | emotions6 | 0.39 | [ 0.30, 0.47]
emotions5 | emotions7 | 0.46 | [ 0.38, 0.54]
emotions5 | attention1 | -3.09e-03 | [-0.10, 0.10]
emotions5 | attention2 | -0.06 | [-0.16, 0.04]
emotions5 | attention3 | 0.16 | [ 0.06, 0.26]
emotions5 | psychdistance1 | 0.22 | [ 0.12, 0.31]
emotions5 | psychdistance2 | 0.02 | [-0.08, 0.12]
emotions5 | psychdistance3 | 0.31 | [ 0.21, 0.40]
emotions5 | liking1 | -3.88e-03 | [-0.10, 0.10]
emotions5 | liking2 | -6.21e-03 | [-0.11, 0.09]
emotions5 | liking3 | 0.18 | [ 0.08, 0.27]
emotions5 | liking4 | 0.04 | [-0.06, 0.14]
emotions5 | liking5 | -6.95e-03 | [-0.11, 0.09]
emotions5 | humor1 | -0.21 | [-0.30, -0.11]
emotions5 | humor2 | -0.20 | [-0.29, -0.10]
emotions5 | humor3 | -0.06 | [-0.16, 0.04]
emotions5 | aversiveness | 0.48 | [ 0.40, 0.56]
emotions5 | messagediscounting1 | -0.22 | [-0.32, -0.13]
emotions5 | messagediscounting2 | -0.13 | [-0.23, -0.03]
emotions5 | messagediscounting3 | -0.12 | [-0.22, -0.02]
emotions5 | messagediscounting4 | -0.22 | [-0.31, -0.12]
emotions5 | attitudepositive1 | -0.22 | [-0.31, -0.12]
emotions5 | attitudepositive2 | -0.26 | [-0.35, -0.17]
emotions5 | attitudepositive3 | -0.15 | [-0.24, -0.05]
emotions5 | attitudenegative1 | 0.18 | [ 0.08, 0.28]
emotions5 | attitudenegative2 | 0.16 | [ 0.06, 0.26]
emotions5 | attitudenegative3 | 0.20 | [ 0.10, 0.29]
emotions5 | age | -4.98e-03 | [-0.11, 0.10]
emotions5 | newsconsumption1 | 0.10 | [ 0.00, 0.20]
emotions5 | newsconsumption2 | 0.03 | [-0.07, 0.13]
emotions5 | newsconsumption3 | -0.06 | [-0.16, 0.05]
emotions5 | newsconsumption4 | -0.10 | [-0.19, 0.01]
emotions6 | emotions7 | 0.48 | [ 0.40, 0.55]
emotions6 | attention1 | -0.05 | [-0.15, 0.05]
emotions6 | attention2 | -0.04 | [-0.14, 0.06]
emotions6 | attention3 | -4.19e-04 | [-0.10, 0.10]
emotions6 | psychdistance1 | 0.06 | [-0.04, 0.16]
emotions6 | psychdistance2 | 0.04 | [-0.06, 0.14]
emotions6 | psychdistance3 | 0.08 | [-0.02, 0.18]
emotions6 | liking1 | -0.06 | [-0.16, 0.04]
emotions6 | liking2 | -0.10 | [-0.20, 0.00]
emotions6 | liking3 | 4.75e-03 | [-0.10, 0.11]
emotions6 | liking4 | 0.05 | [-0.05, 0.15]
emotions6 | liking5 | -0.01 | [-0.11, 0.09]
emotions6 | humor1 | 0.02 | [-0.08, 0.12]
emotions6 | humor2 | 0.01 | [-0.09, 0.11]
emotions6 | humor3 | -0.03 | [-0.13, 0.07]
emotions6 | aversiveness | 0.37 | [ 0.28, 0.46]
emotions6 | messagediscounting1 | -0.02 | [-0.12, 0.08]
emotions6 | messagediscounting2 | 3.03e-03 | [-0.10, 0.10]
emotions6 | messagediscounting3 | -0.06 | [-0.16, 0.04]
emotions6 | messagediscounting4 | 0.02 | [-0.08, 0.12]
emotions6 | attitudepositive1 | -0.02 | [-0.12, 0.08]
emotions6 | attitudepositive2 | -3.01e-03 | [-0.10, 0.10]
emotions6 | attitudepositive3 | 0.02 | [-0.08, 0.13]
emotions6 | attitudenegative1 | 0.12 | [ 0.02, 0.22]
emotions6 | attitudenegative2 | 0.10 | [-0.01, 0.19]
emotions6 | attitudenegative3 | 0.08 | [-0.02, 0.18]
emotions6 | age | -0.02 | [-0.12, 0.08]
emotions6 | newsconsumption1 | 0.01 | [-0.09, 0.11]
emotions6 | newsconsumption2 | 0.05 | [-0.06, 0.15]
emotions6 | newsconsumption3 | -0.10 | [-0.20, 0.00]
emotions6 | newsconsumption4 | -0.03 | [-0.13, 0.07]
emotions7 | attention1 | -0.02 | [-0.13, 0.08]
emotions7 | attention2 | -3.13e-03 | [-0.10, 0.10]
emotions7 | attention3 | 0.08 | [-0.02, 0.18]
emotions7 | psychdistance1 | 0.17 | [ 0.07, 0.27]
emotions7 | psychdistance2 | 0.05 | [-0.05, 0.15]
emotions7 | psychdistance3 | 0.19 | [ 0.09, 0.28]
emotions7 | liking1 | 0.06 | [-0.04, 0.16]
emotions7 | liking2 | -0.06 | [-0.16, 0.04]
emotions7 | liking3 | 0.10 | [ 0.00, 0.20]
emotions7 | liking4 | 0.02 | [-0.08, 0.12]
emotions7 | liking5 | -0.04 | [-0.14, 0.06]
emotions7 | humor1 | -0.09 | [-0.19, 0.01]
emotions7 | humor2 | -0.10 | [-0.20, 0.00]
emotions7 | humor3 | -0.04 | [-0.14, 0.06]
emotions7 | aversiveness | 0.47 | [ 0.38, 0.54]
emotions7 | messagediscounting1 | -0.15 | [-0.25, -0.05]
emotions7 | messagediscounting2 | -0.08 | [-0.18, 0.02]
emotions7 | messagediscounting3 | -0.06 | [-0.16, 0.04]
emotions7 | messagediscounting4 | -0.16 | [-0.25, -0.06]
emotions7 | attitudepositive1 | -0.16 | [-0.25, -0.06]
emotions7 | attitudepositive2 | -0.18 | [-0.27, -0.08]
emotions7 | attitudepositive3 | -0.05 | [-0.15, 0.06]
emotions7 | attitudenegative1 | 0.19 | [ 0.09, 0.28]
emotions7 | attitudenegative2 | 0.06 | [-0.04, 0.16]
emotions7 | attitudenegative3 | 0.10 | [ 0.00, 0.20]
emotions7 | age | -0.01 | [-0.11, 0.09]
emotions7 | newsconsumption1 | 0.04 | [-0.06, 0.14]
emotions7 | newsconsumption2 | 0.03 | [-0.07, 0.13]
emotions7 | newsconsumption3 | -0.05 | [-0.15, 0.06]
emotions7 | newsconsumption4 | -4.99e-03 | [-0.11, 0.10]
attention1 | attention2 | 0.67 | [ 0.62, 0.73]
attention1 | attention3 | 0.24 | [ 0.15, 0.34]
attention1 | psychdistance1 | -3.21e-03 | [-0.10, 0.10]
attention1 | psychdistance2 | 0.08 | [-0.02, 0.18]
attention1 | psychdistance3 | -7.16e-03 | [-0.11, 0.09]
attention1 | liking1 | 0.14 | [ 0.04, 0.23]
attention1 | liking2 | 0.02 | [-0.09, 0.12]
attention1 | liking3 | 0.03 | [-0.07, 0.13]
attention1 | liking4 | 0.03 | [-0.07, 0.13]
attention1 | liking5 | -0.06 | [-0.16, 0.04]
attention1 | humor1 | 0.01 | [-0.09, 0.12]
attention1 | humor2 | 0.07 | [-0.03, 0.17]
attention1 | humor3 | 5.71e-03 | [-0.10, 0.11]
attention1 | aversiveness | 0.04 | [-0.06, 0.14]
attention1 | messagediscounting1 | -0.04 | [-0.14, 0.06]
attention1 | messagediscounting2 | -0.02 | [-0.12, 0.08]
attention1 | messagediscounting3 | 0.02 | [-0.08, 0.12]
attention1 | messagediscounting4 | -0.04 | [-0.14, 0.06]
attention1 | attitudepositive1 | 0.01 | [-0.09, 0.11]
attention1 | attitudepositive2 | -4.30e-17 | [-0.10, 0.10]
attention1 | attitudepositive3 | -6.83e-03 | [-0.11, 0.09]
attention1 | attitudenegative1 | -0.03 | [-0.13, 0.08]
attention1 | attitudenegative2 | -7.30e-03 | [-0.11, 0.09]
attention1 | attitudenegative3 | 0.02 | [-0.08, 0.12]
attention1 | age | 0.14 | [ 0.04, 0.24]
attention1 | newsconsumption1 | 0.04 | [-0.06, 0.14]
attention1 | newsconsumption2 | 0.07 | [-0.03, 0.17]
attention1 | newsconsumption3 | 0.10 | [ 0.00, 0.20]
attention1 | newsconsumption4 | 0.02 | [-0.08, 0.12]
attention2 | attention3 | 0.27 | [ 0.18, 0.36]
attention2 | psychdistance1 | 0.05 | [-0.05, 0.15]
attention2 | psychdistance2 | 0.13 | [ 0.03, 0.23]
attention2 | psychdistance3 | 0.08 | [-0.02, 0.18]
attention2 | liking1 | 0.14 | [ 0.04, 0.24]
attention2 | liking2 | 0.12 | [ 0.01, 0.21]
attention2 | liking3 | 0.09 | [-0.01, 0.19]
attention2 | liking4 | 0.09 | [-0.02, 0.19]
attention2 | liking5 | 0.05 | [-0.05, 0.15]
attention2 | humor1 | 0.02 | [-0.08, 0.12]
attention2 | humor2 | 0.10 | [ 0.00, 0.20]
attention2 | humor3 | 0.08 | [-0.03, 0.18]
attention2 | aversiveness | -5.42e-03 | [-0.11, 0.10]
attention2 | messagediscounting1 | -0.03 | [-0.13, 0.08]
attention2 | messagediscounting2 | -0.06 | [-0.16, 0.04]
attention2 | messagediscounting3 | -0.03 | [-0.13, 0.07]
attention2 | messagediscounting4 | -0.06 | [-0.16, 0.04]
attention2 | attitudepositive1 | 0.03 | [-0.07, 0.13]
attention2 | attitudepositive2 | -0.05 | [-0.15, 0.05]
attention2 | attitudepositive3 | -0.04 | [-0.14, 0.06]
attention2 | attitudenegative1 | 0.01 | [-0.09, 0.11]
attention2 | attitudenegative2 | -0.05 | [-0.15, 0.05]
attention2 | attitudenegative3 | -0.04 | [-0.14, 0.06]
attention2 | age | 0.08 | [-0.02, 0.18]
attention2 | newsconsumption1 | -0.02 | [-0.12, 0.08]
attention2 | newsconsumption2 | 0.08 | [-0.02, 0.18]
attention2 | newsconsumption3 | 0.07 | [-0.03, 0.17]
attention2 | newsconsumption4 | 0.04 | [-0.06, 0.14]
attention3 | psychdistance1 | 0.20 | [ 0.10, 0.30]
attention3 | psychdistance2 | 0.18 | [ 0.08, 0.27]
attention3 | psychdistance3 | 0.24 | [ 0.14, 0.33]
attention3 | liking1 | 0.51 | [ 0.44, 0.58]
attention3 | liking2 | 0.38 | [ 0.29, 0.46]
attention3 | liking3 | 0.72 | [ 0.66, 0.76]
attention3 | liking4 | 0.30 | [ 0.21, 0.39]
attention3 | liking5 | 0.28 | [ 0.19, 0.37]
attention3 | humor1 | -0.10 | [-0.20, 0.00]
attention3 | humor2 | -0.02 | [-0.12, 0.08]
attention3 | humor3 | 0.25 | [ 0.15, 0.34]
attention3 | aversiveness | 0.19 | [ 0.09, 0.28]
attention3 | messagediscounting1 | -0.19 | [-0.29, -0.09]
attention3 | messagediscounting2 | -0.13 | [-0.23, -0.03]
attention3 | messagediscounting3 | -0.17 | [-0.27, -0.07]
attention3 | messagediscounting4 | -0.23 | [-0.33, -0.14]
attention3 | attitudepositive1 | -0.08 | [-0.18, 0.02]
attention3 | attitudepositive2 | -0.11 | [-0.21, -0.01]
attention3 | attitudepositive3 | -0.03 | [-0.13, 0.07]
attention3 | attitudenegative1 | 0.18 | [ 0.08, 0.27]
attention3 | attitudenegative2 | 0.09 | [-0.01, 0.19]
attention3 | attitudenegative3 | 0.14 | [ 0.04, 0.24]
attention3 | age | 0.11 | [ 0.01, 0.21]
attention3 | newsconsumption1 | 0.16 | [ 0.06, 0.26]
attention3 | newsconsumption2 | 0.05 | [-0.05, 0.15]
attention3 | newsconsumption3 | 0.02 | [-0.08, 0.12]
attention3 | newsconsumption4 | -0.07 | [-0.17, 0.03]
psychdistance1 | psychdistance2 | 0.42 | [ 0.33, 0.50]
psychdistance1 | psychdistance3 | 0.51 | [ 0.43, 0.58]
psychdistance1 | liking1 | 0.19 | [ 0.09, 0.28]
psychdistance1 | liking2 | 0.10 | [ 0.00, 0.20]
psychdistance1 | liking3 | 0.29 | [ 0.19, 0.38]
psychdistance1 | liking4 | 0.05 | [-0.05, 0.15]
psychdistance1 | liking5 | 0.07 | [-0.03, 0.17]
psychdistance1 | humor1 | -0.14 | [-0.23, -0.03]
psychdistance1 | humor2 | -0.11 | [-0.21, -0.01]
psychdistance1 | humor3 | 0.01 | [-0.09, 0.11]
psychdistance1 | aversiveness | 0.16 | [ 0.06, 0.25]
psychdistance1 | messagediscounting1 | -0.21 | [-0.30, -0.11]
psychdistance1 | messagediscounting2 | -0.17 | [-0.26, -0.07]
psychdistance1 | messagediscounting3 | -0.12 | [-0.22, -0.02]
psychdistance1 | messagediscounting4 | -0.18 | [-0.27, -0.08]
psychdistance1 | attitudepositive1 | -0.01 | [-0.11, 0.09]
psychdistance1 | attitudepositive2 | -0.11 | [-0.21, -0.01]
psychdistance1 | attitudepositive3 | -0.02 | [-0.12, 0.08]
psychdistance1 | attitudenegative1 | 0.06 | [-0.05, 0.16]
psychdistance1 | attitudenegative2 | 0.05 | [-0.05, 0.15]
psychdistance1 | attitudenegative3 | 0.06 | [-0.05, 0.16]
psychdistance1 | age | -0.10 | [-0.20, 0.00]
psychdistance1 | newsconsumption1 | 0.06 | [-0.04, 0.16]
psychdistance1 | newsconsumption2 | -4.19e-03 | [-0.11, 0.10]
psychdistance1 | newsconsumption3 | 0.03 | [-0.07, 0.13]
psychdistance1 | newsconsumption4 | -0.06 | [-0.16, 0.04]
psychdistance2 | psychdistance3 | 0.32 | [ 0.22, 0.40]
psychdistance2 | liking1 | 0.15 | [ 0.05, 0.25]
psychdistance2 | liking2 | 0.10 | [ 0.00, 0.20]
psychdistance2 | liking3 | 0.21 | [ 0.12, 0.31]
psychdistance2 | liking4 | 0.02 | [-0.08, 0.12]
psychdistance2 | liking5 | 0.07 | [-0.03, 0.17]
psychdistance2 | humor1 | -0.02 | [-0.13, 0.08]
psychdistance2 | humor2 | -6.95e-03 | [-0.11, 0.09]
psychdistance2 | humor3 | 7.22e-03 | [-0.09, 0.11]
psychdistance2 | aversiveness | 0.11 | [ 0.01, 0.21]
psychdistance2 | messagediscounting1 | -0.11 | [-0.21, -0.01]
psychdistance2 | messagediscounting2 | -0.05 | [-0.15, 0.05]
psychdistance2 | messagediscounting3 | -0.06 | [-0.16, 0.04]
psychdistance2 | messagediscounting4 | -0.10 | [-0.20, 0.00]
psychdistance2 | attitudepositive1 | 0.06 | [-0.04, 0.16]
psychdistance2 | attitudepositive2 | -0.07 | [-0.17, 0.03]
psychdistance2 | attitudepositive3 | 0.05 | [-0.06, 0.15]
psychdistance2 | attitudenegative1 | -0.06 | [-0.16, 0.04]
psychdistance2 | attitudenegative2 | -0.06 | [-0.16, 0.04]
psychdistance2 | attitudenegative3 | -0.06 | [-0.16, 0.04]
psychdistance2 | age | -0.07 | [-0.17, 0.03]
psychdistance2 | newsconsumption1 | 0.02 | [-0.08, 0.12]
psychdistance2 | newsconsumption2 | 0.11 | [ 0.01, 0.21]
psychdistance2 | newsconsumption3 | 0.16 | [ 0.06, 0.25]
psychdistance2 | newsconsumption4 | 0.06 | [-0.04, 0.16]
psychdistance3 | liking1 | 0.09 | [-0.01, 0.19]
psychdistance3 | liking2 | 0.13 | [ 0.03, 0.23]
psychdistance3 | liking3 | 0.27 | [ 0.17, 0.36]
psychdistance3 | liking4 | 0.04 | [-0.06, 0.15]
psychdistance3 | liking5 | 0.08 | [-0.02, 0.18]
psychdistance3 | humor1 | -0.16 | [-0.26, -0.06]
psychdistance3 | humor2 | -0.10 | [-0.20, 0.00]
psychdistance3 | humor3 | 2.34e-03 | [-0.10, 0.10]
psychdistance3 | aversiveness | 0.14 | [ 0.04, 0.24]
psychdistance3 | messagediscounting1 | -0.24 | [-0.33, -0.14]
psychdistance3 | messagediscounting2 | -0.18 | [-0.27, -0.08]
psychdistance3 | messagediscounting3 | -0.18 | [-0.27, -0.08]
psychdistance3 | messagediscounting4 | -0.25 | [-0.34, -0.15]
psychdistance3 | attitudepositive1 | -0.07 | [-0.16, 0.04]
psychdistance3 | attitudepositive2 | -0.16 | [-0.25, -0.06]
psychdistance3 | attitudepositive3 | -0.05 | [-0.15, 0.05]
psychdistance3 | attitudenegative1 | 0.03 | [-0.07, 0.13]
psychdistance3 | attitudenegative2 | 0.13 | [ 0.03, 0.22]
psychdistance3 | attitudenegative3 | 0.05 | [-0.05, 0.15]
psychdistance3 | age | -0.09 | [-0.19, 0.01]
psychdistance3 | newsconsumption1 | 0.10 | [-0.01, 0.19]
psychdistance3 | newsconsumption2 | -0.04 | [-0.14, 0.07]
psychdistance3 | newsconsumption3 | 0.01 | [-0.09, 0.12]
psychdistance3 | newsconsumption4 | -0.12 | [-0.22, -0.02]
liking1 | liking2 | 0.33 | [ 0.23, 0.41]
liking1 | liking3 | 0.58 | [ 0.51, 0.65]
liking1 | liking4 | 0.31 | [ 0.21, 0.40]
liking1 | liking5 | 0.21 | [ 0.11, 0.31]
liking1 | humor1 | 0.03 | [-0.07, 0.13]
liking1 | humor2 | 0.04 | [-0.06, 0.14]
liking1 | humor3 | 0.23 | [ 0.13, 0.32]
liking1 | aversiveness | 0.16 | [ 0.06, 0.26]
liking1 | messagediscounting1 | -0.07 | [-0.17, 0.03]
liking1 | messagediscounting2 | -0.03 | [-0.13, 0.07]
liking1 | messagediscounting3 | -0.10 | [-0.20, 0.00]
liking1 | messagediscounting4 | -0.11 | [-0.21, -0.01]
liking1 | attitudepositive1 | -0.01 | [-0.11, 0.09]
liking1 | attitudepositive2 | -0.03 | [-0.13, 0.07]
liking1 | attitudepositive3 | 0.04 | [-0.06, 0.14]
liking1 | attitudenegative1 | 0.10 | [ 0.00, 0.20]
liking1 | attitudenegative2 | 0.02 | [-0.08, 0.12]
liking1 | attitudenegative3 | -0.06 | [-0.16, 0.04]
liking1 | age | 0.13 | [ 0.03, 0.22]
liking1 | newsconsumption1 | 0.15 | [ 0.05, 0.25]
liking1 | newsconsumption2 | -1.49e-03 | [-0.10, 0.10]
liking1 | newsconsumption3 | -8.76e-03 | [-0.11, 0.09]
liking1 | newsconsumption4 | -0.03 | [-0.14, 0.07]
liking2 | liking3 | 0.43 | [ 0.34, 0.51]
liking2 | liking4 | 0.58 | [ 0.51, 0.64]
liking2 | liking5 | 0.59 | [ 0.52, 0.66]
liking2 | humor1 | 0.27 | [ 0.17, 0.36]
liking2 | humor2 | 0.35 | [ 0.26, 0.44]
liking2 | humor3 | 0.59 | [ 0.52, 0.65]
liking2 | aversiveness | -0.06 | [-0.16, 0.04]
liking2 | messagediscounting1 | 0.15 | [ 0.05, 0.25]
liking2 | messagediscounting2 | 0.18 | [ 0.08, 0.27]
liking2 | messagediscounting3 | 0.06 | [-0.04, 0.16]
liking2 | messagediscounting4 | 0.09 | [-0.01, 0.19]
liking2 | attitudepositive1 | 5.46e-03 | [-0.10, 0.11]
liking2 | attitudepositive2 | 6.27e-03 | [-0.09, 0.11]
liking2 | attitudepositive3 | 0.02 | [-0.08, 0.12]
liking2 | attitudenegative1 | 4.79e-03 | [-0.10, 0.11]
liking2 | attitudenegative2 | 0.04 | [-0.07, 0.14]
liking2 | attitudenegative3 | 8.00e-03 | [-0.09, 0.11]
liking2 | age | -0.07 | [-0.17, 0.03]
liking2 | newsconsumption1 | 0.08 | [-0.02, 0.18]
liking2 | newsconsumption2 | 0.06 | [-0.04, 0.16]
liking2 | newsconsumption3 | 0.07 | [-0.03, 0.17]
liking2 | newsconsumption4 | -0.04 | [-0.14, 0.06]
liking3 | liking4 | 0.33 | [ 0.23, 0.42]
liking3 | liking5 | 0.33 | [ 0.24, 0.42]
liking3 | humor1 | -0.12 | [-0.21, -0.02]
liking3 | humor2 | -0.06 | [-0.16, 0.04]
liking3 | humor3 | 0.27 | [ 0.17, 0.36]
liking3 | aversiveness | 0.22 | [ 0.12, 0.31]
liking3 | messagediscounting1 | -0.22 | [-0.32, -0.12]
liking3 | messagediscounting2 | -0.12 | [-0.22, -0.02]
liking3 | messagediscounting3 | -0.19 | [-0.28, -0.09]
liking3 | messagediscounting4 | -0.22 | [-0.31, -0.12]
liking3 | attitudepositive1 | -0.05 | [-0.15, 0.05]
liking3 | attitudepositive2 | -0.11 | [-0.21, -0.01]
liking3 | attitudepositive3 | -0.03 | [-0.13, 0.07]
liking3 | attitudenegative1 | 0.20 | [ 0.10, 0.30]
liking3 | attitudenegative2 | 0.13 | [ 0.03, 0.23]
liking3 | attitudenegative3 | 0.14 | [ 0.04, 0.24]
liking3 | age | 0.03 | [-0.07, 0.13]
liking3 | newsconsumption1 | 0.17 | [ 0.07, 0.26]
liking3 | newsconsumption2 | 0.04 | [-0.06, 0.14]
liking3 | newsconsumption3 | 0.03 | [-0.07, 0.13]
liking3 | newsconsumption4 | -0.09 | [-0.19, 0.01]
liking4 | liking5 | 0.56 | [ 0.48, 0.62]
liking4 | humor1 | 0.36 | [ 0.27, 0.44]
liking4 | humor2 | 0.37 | [ 0.28, 0.45]
liking4 | humor3 | 0.55 | [ 0.48, 0.62]
liking4 | aversiveness | 0.03 | [-0.07, 0.13]
liking4 | messagediscounting1 | 0.25 | [ 0.15, 0.34]
liking4 | messagediscounting2 | 0.21 | [ 0.11, 0.31]
liking4 | messagediscounting3 | -1.53e-03 | [-0.10, 0.10]
liking4 | messagediscounting4 | 0.14 | [ 0.04, 0.24]
liking4 | attitudepositive1 | -0.01 | [-0.11, 0.09]
liking4 | attitudepositive2 | 0.05 | [-0.05, 0.15]
liking4 | attitudepositive3 | 0.03 | [-0.07, 0.13]
liking4 | attitudenegative1 | 0.05 | [-0.05, 0.15]
liking4 | attitudenegative2 | -5.09e-04 | [-0.10, 0.10]
liking4 | attitudenegative3 | 2.22e-03 | [-0.10, 0.10]
liking4 | age | 0.08 | [-0.03, 0.18]
liking4 | newsconsumption1 | 0.06 | [-0.04, 0.16]
liking4 | newsconsumption2 | 0.10 | [ 0.00, 0.20]
liking4 | newsconsumption3 | 0.08 | [-0.02, 0.18]
liking4 | newsconsumption4 | 0.02 | [-0.08, 0.12]
liking5 | humor1 | 0.36 | [ 0.27, 0.45]
liking5 | humor2 | 0.37 | [ 0.28, 0.45]
liking5 | humor3 | 0.55 | [ 0.48, 0.62]
liking5 | aversiveness | -0.08 | [-0.18, 0.03]
liking5 | messagediscounting1 | 0.19 | [ 0.09, 0.29]
liking5 | messagediscounting2 | 0.15 | [ 0.05, 0.25]
liking5 | messagediscounting3 | 0.06 | [-0.04, 0.16]
liking5 | messagediscounting4 | 0.11 | [ 0.01, 0.21]
liking5 | attitudepositive1 | 0.08 | [-0.02, 0.18]
liking5 | attitudepositive2 | 0.07 | [-0.03, 0.17]
liking5 | attitudepositive3 | 0.06 | [-0.04, 0.16]
liking5 | attitudenegative1 | 0.06 | [-0.04, 0.16]
liking5 | attitudenegative2 | -0.02 | [-0.12, 0.08]
liking5 | attitudenegative3 | -0.02 | [-0.12, 0.08]
liking5 | age | -0.04 | [-0.14, 0.06]
liking5 | newsconsumption1 | 0.03 | [-0.07, 0.13]
liking5 | newsconsumption2 | 0.04 | [-0.06, 0.14]
liking5 | newsconsumption3 | 0.01 | [-0.09, 0.11]
liking5 | newsconsumption4 | 0.01 | [-0.09, 0.11]
humor1 | humor2 | 0.76 | [ 0.72, 0.80]
humor1 | humor3 | 0.56 | [ 0.48, 0.62]
humor1 | aversiveness | -0.07 | [-0.17, 0.03]
humor1 | messagediscounting1 | 0.58 | [ 0.51, 0.65]
humor1 | messagediscounting2 | 0.47 | [ 0.39, 0.55]
humor1 | messagediscounting3 | 0.31 | [ 0.21, 0.39]
humor1 | messagediscounting4 | 0.50 | [ 0.42, 0.57]
humor1 | attitudepositive1 | 0.16 | [ 0.06, 0.26]
humor1 | attitudepositive2 | 0.20 | [ 0.10, 0.29]
humor1 | attitudepositive3 | 0.19 | [ 0.09, 0.28]
humor1 | attitudenegative1 | -0.07 | [-0.17, 0.03]
humor1 | attitudenegative2 | -0.12 | [-0.22, -0.02]
humor1 | attitudenegative3 | -0.14 | [-0.24, -0.04]
humor1 | age | -0.05 | [-0.15, 0.05]
humor1 | newsconsumption1 | -0.03 | [-0.13, 0.07]
humor1 | newsconsumption2 | 0.09 | [-0.01, 0.19]
humor1 | newsconsumption3 | 0.18 | [ 0.08, 0.27]
humor1 | newsconsumption4 | 0.18 | [ 0.08, 0.28]
humor2 | humor3 | 0.62 | [ 0.56, 0.68]
humor2 | aversiveness | -0.09 | [-0.19, 0.01]
humor2 | messagediscounting1 | 0.49 | [ 0.41, 0.56]
humor2 | messagediscounting2 | 0.42 | [ 0.34, 0.50]
humor2 | messagediscounting3 | 0.24 | [ 0.14, 0.33]
humor2 | messagediscounting4 | 0.45 | [ 0.36, 0.53]
humor2 | attitudepositive1 | 0.14 | [ 0.04, 0.24]
humor2 | attitudepositive2 | 0.16 | [ 0.06, 0.25]
humor2 | attitudepositive3 | 0.10 | [ 0.00, 0.20]
humor2 | attitudenegative1 | -0.06 | [-0.16, 0.05]
humor2 | attitudenegative2 | -0.10 | [-0.20, 0.00]
humor2 | attitudenegative3 | -0.13 | [-0.22, -0.03]
humor2 | age | -0.15 | [-0.25, -0.05]
humor2 | newsconsumption1 | -0.02 | [-0.12, 0.08]
humor2 | newsconsumption2 | 0.09 | [-0.01, 0.19]
humor2 | newsconsumption3 | 0.17 | [ 0.07, 0.26]
humor2 | newsconsumption4 | 0.14 | [ 0.03, 0.23]
humor3 | aversiveness | -0.03 | [-0.13, 0.07]
humor3 | messagediscounting1 | 0.35 | [ 0.26, 0.43]
humor3 | messagediscounting2 | 0.30 | [ 0.20, 0.39]
humor3 | messagediscounting3 | 0.15 | [ 0.05, 0.25]
humor3 | messagediscounting4 | 0.27 | [ 0.17, 0.36]
humor3 | attitudepositive1 | 0.04 | [-0.06, 0.14]
humor3 | attitudepositive2 | 0.04 | [-0.06, 0.14]
humor3 | attitudepositive3 | 0.06 | [-0.04, 0.16]
humor3 | attitudenegative1 | 0.04 | [-0.06, 0.14]
humor3 | attitudenegative2 | 0.05 | [-0.05, 0.15]
humor3 | attitudenegative3 | 5.07e-03 | [-0.10, 0.11]
humor3 | age | -0.09 | [-0.19, 0.02]
humor3 | newsconsumption1 | 0.03 | [-0.07, 0.13]
humor3 | newsconsumption2 | 0.06 | [-0.04, 0.16]
humor3 | newsconsumption3 | 0.09 | [-0.01, 0.19]
humor3 | newsconsumption4 | 0.07 | [-0.03, 0.17]
aversiveness | messagediscounting1 | -0.15 | [-0.25, -0.05]
aversiveness | messagediscounting2 | -0.09 | [-0.19, 0.01]
aversiveness | messagediscounting3 | -0.20 | [-0.30, -0.11]
aversiveness | messagediscounting4 | -0.14 | [-0.24, -0.04]
aversiveness | attitudepositive1 | -0.19 | [-0.29, -0.09]
aversiveness | attitudepositive2 | -0.23 | [-0.32, -0.13]
aversiveness | attitudepositive3 | -0.09 | [-0.19, 0.01]
aversiveness | attitudenegative1 | 0.24 | [ 0.14, 0.33]
aversiveness | attitudenegative2 | 0.18 | [ 0.08, 0.28]
aversiveness | attitudenegative3 | 0.20 | [ 0.10, 0.30]
aversiveness | age | 0.17 | [ 0.07, 0.27]
aversiveness | newsconsumption1 | 0.08 | [-0.02, 0.18]
aversiveness | newsconsumption2 | 0.07 | [-0.03, 0.17]
aversiveness | newsconsumption3 | -9.29e-03 | [-0.11, 0.09]
aversiveness | newsconsumption4 | -0.02 | [-0.12, 0.08]
messagediscounting1 | messagediscounting2 | 0.68 | [ 0.62, 0.73]
messagediscounting1 | messagediscounting3 | 0.54 | [ 0.47, 0.61]
messagediscounting1 | messagediscounting4 | 0.70 | [ 0.65, 0.75]
messagediscounting1 | attitudepositive1 | 0.08 | [-0.02, 0.18]
messagediscounting1 | attitudepositive2 | 0.20 | [ 0.11, 0.30]
messagediscounting1 | attitudepositive3 | 0.11 | [ 0.01, 0.21]
messagediscounting1 | attitudenegative1 | -0.03 | [-0.13, 0.07]
messagediscounting1 | attitudenegative2 | -0.07 | [-0.17, 0.03]
messagediscounting1 | attitudenegative3 | -0.03 | [-0.13, 0.08]
messagediscounting1 | age | -0.01 | [-0.11, 0.09]
messagediscounting1 | newsconsumption1 | -0.08 | [-0.18, 0.02]
messagediscounting1 | newsconsumption2 | -0.05 | [-0.15, 0.05]
messagediscounting1 | newsconsumption3 | 0.08 | [-0.02, 0.18]
messagediscounting1 | newsconsumption4 | 0.08 | [-0.02, 0.18]
messagediscounting2 | messagediscounting3 | 0.50 | [ 0.42, 0.57]
messagediscounting2 | messagediscounting4 | 0.62 | [ 0.56, 0.68]
messagediscounting2 | attitudepositive1 | 0.06 | [-0.05, 0.16]
messagediscounting2 | attitudepositive2 | 0.15 | [ 0.05, 0.25]
messagediscounting2 | attitudepositive3 | 0.05 | [-0.05, 0.15]
messagediscounting2 | attitudenegative1 | 0.03 | [-0.07, 0.13]
messagediscounting2 | attitudenegative2 | 2.27e-03 | [-0.10, 0.10]
messagediscounting2 | attitudenegative3 | 0.04 | [-0.06, 0.14]
messagediscounting2 | age | -0.01 | [-0.11, 0.09]
messagediscounting2 | newsconsumption1 | -0.11 | [-0.20, -0.01]
messagediscounting2 | newsconsumption2 | -0.04 | [-0.14, 0.06]
messagediscounting2 | newsconsumption3 | 0.06 | [-0.04, 0.16]
messagediscounting2 | newsconsumption4 | 0.07 | [-0.03, 0.17]
messagediscounting3 | messagediscounting4 | 0.43 | [ 0.35, 0.51]
messagediscounting3 | attitudepositive1 | -0.01 | [-0.11, 0.09]
messagediscounting3 | attitudepositive2 | 0.08 | [-0.03, 0.18]
messagediscounting3 | attitudepositive3 | 0.01 | [-0.09, 0.11]
messagediscounting3 | attitudenegative1 | -0.08 | [-0.18, 0.03]
messagediscounting3 | attitudenegative2 | -0.08 | [-0.18, 0.02]
messagediscounting3 | attitudenegative3 | -0.04 | [-0.14, 0.06]
messagediscounting3 | age | -0.14 | [-0.24, -0.04]
messagediscounting3 | newsconsumption1 | -0.11 | [-0.21, -0.01]
messagediscounting3 | newsconsumption2 | -0.06 | [-0.16, 0.04]
messagediscounting3 | newsconsumption3 | 0.08 | [-0.02, 0.18]
messagediscounting3 | newsconsumption4 | 0.13 | [ 0.03, 0.23]
messagediscounting4 | attitudepositive1 | 0.09 | [-0.02, 0.19]
messagediscounting4 | attitudepositive2 | 0.17 | [ 0.08, 0.27]
messagediscounting4 | attitudepositive3 | 0.09 | [-0.01, 0.19]
messagediscounting4 | attitudenegative1 | -0.03 | [-0.13, 0.07]
messagediscounting4 | attitudenegative2 | -0.05 | [-0.15, 0.05]
messagediscounting4 | attitudenegative3 | -0.03 | [-0.13, 0.07]
messagediscounting4 | age | -0.11 | [-0.21, -0.01]
messagediscounting4 | newsconsumption1 | -0.17 | [-0.26, -0.07]
messagediscounting4 | newsconsumption2 | 0.01 | [-0.09, 0.11]
messagediscounting4 | newsconsumption3 | 0.11 | [ 0.01, 0.21]
messagediscounting4 | newsconsumption4 | 0.09 | [-0.01, 0.19]
attitudepositive1 | attitudepositive2 | 0.52 | [ 0.44, 0.59]
attitudepositive1 | attitudepositive3 | 0.52 | [ 0.44, 0.59]
attitudepositive1 | attitudenegative1 | -0.57 | [-0.64, -0.50]
attitudepositive1 | attitudenegative2 | -0.37 | [-0.46, -0.28]
attitudepositive1 | attitudenegative3 | -0.33 | [-0.41, -0.23]
attitudepositive1 | age | 0.03 | [-0.07, 0.13]
attitudepositive1 | newsconsumption1 | -0.05 | [-0.15, 0.05]
attitudepositive1 | newsconsumption2 | -0.02 | [-0.12, 0.08]
attitudepositive1 | newsconsumption3 | 0.15 | [ 0.04, 0.24]
attitudepositive1 | newsconsumption4 | 0.07 | [-0.03, 0.17]
attitudepositive2 | attitudepositive3 | 0.43 | [ 0.35, 0.51]
attitudepositive2 | attitudenegative1 | -0.36 | [-0.44, -0.27]
attitudepositive2 | attitudenegative2 | -0.52 | [-0.59, -0.44]
attitudepositive2 | attitudenegative3 | -0.32 | [-0.41, -0.23]
attitudepositive2 | age | -0.02 | [-0.12, 0.08]
attitudepositive2 | newsconsumption1 | -5.98e-03 | [-0.11, 0.09]
attitudepositive2 | newsconsumption2 | -0.03 | [-0.13, 0.08]
attitudepositive2 | newsconsumption3 | 0.16 | [ 0.06, 0.26]
attitudepositive2 | newsconsumption4 | 0.12 | [ 0.02, 0.22]
attitudepositive3 | attitudenegative1 | -0.25 | [-0.35, -0.16]
attitudepositive3 | attitudenegative2 | -0.25 | [-0.34, -0.15]
attitudepositive3 | attitudenegative3 | -0.49 | [-0.56, -0.41]
attitudepositive3 | age | 0.02 | [-0.08, 0.12]
attitudepositive3 | newsconsumption1 | -0.04 | [-0.14, 0.06]
attitudepositive3 | newsconsumption2 | -0.05 | [-0.15, 0.05]
attitudepositive3 | newsconsumption3 | 0.17 | [ 0.07, 0.27]
attitudepositive3 | newsconsumption4 | 0.12 | [ 0.02, 0.22]
attitudenegative1 | attitudenegative2 | 0.54 | [ 0.47, 0.61]
attitudenegative1 | attitudenegative3 | 0.50 | [ 0.42, 0.57]
attitudenegative1 | age | -0.05 | [-0.15, 0.05]
attitudenegative1 | newsconsumption1 | 0.06 | [-0.04, 0.16]
attitudenegative1 | newsconsumption2 | -0.01 | [-0.11, 0.09]
attitudenegative1 | newsconsumption3 | -0.09 | [-0.19, 0.01]
attitudenegative1 | newsconsumption4 | -0.12 | [-0.22, -0.02]
attitudenegative2 | attitudenegative3 | 0.48 | [ 0.40, 0.56]
attitudenegative2 | age | -0.04 | [-0.14, 0.06]
attitudenegative2 | newsconsumption1 | 0.07 | [-0.03, 0.17]
attitudenegative2 | newsconsumption2 | -0.03 | [-0.13, 0.07]
attitudenegative2 | newsconsumption3 | -0.13 | [-0.23, -0.03]
attitudenegative2 | newsconsumption4 | -0.24 | [-0.34, -0.15]
attitudenegative3 | age | 0.02 | [-0.08, 0.12]
attitudenegative3 | newsconsumption1 | 0.03 | [-0.07, 0.13]
attitudenegative3 | newsconsumption2 | 0.02 | [-0.08, 0.12]
attitudenegative3 | newsconsumption3 | -0.13 | [-0.23, -0.03]
attitudenegative3 | newsconsumption4 | -0.15 | [-0.25, -0.05]
age | newsconsumption1 | 0.30 | [ 0.21, 0.39]
age | newsconsumption2 | 0.18 | [ 0.08, 0.27]
age | newsconsumption3 | 0.04 | [-0.06, 0.14]
age | newsconsumption4 | -0.08 | [-0.18, 0.02]
newsconsumption1 | newsconsumption2 | 0.31 | [ 0.22, 0.40]
newsconsumption1 | newsconsumption3 | 0.13 | [ 0.03, 0.23]
newsconsumption1 | newsconsumption4 | 6.31e-04 | [-0.10, 0.10]
newsconsumption2 | newsconsumption3 | 0.21 | [ 0.11, 0.31]
newsconsumption2 | newsconsumption4 | 0.19 | [ 0.10, 0.29]
newsconsumption3 | newsconsumption4 | 0.49 | [ 0.41, 0.57]
Parameter1 | t(376) | p
-------------------------------------------
emotions1 | 12.06 | < .001***
emotions1 | 8.04 | < .001***
emotions1 | 12.68 | < .001***
emotions1 | 2.17 | > .999
emotions1 | 0.57 | > .999
emotions1 | 0.50 | > .999
emotions1 | -0.79 | > .999
emotions1 | 0.18 | > .999
emotions1 | 3.55 | 0.220
emotions1 | 1.44 | > .999
emotions1 | -0.61 | > .999
emotions1 | 2.22 | > .999
emotions1 | 0.63 | > .999
emotions1 | 8.85 | < .001***
emotions1 | 4.20 | 0.018*
emotions1 | 7.71 | < .001***
emotions1 | 8.21 | < .001***
emotions1 | 2.07 | > .999
emotions1 | 2.28 | > .999
emotions1 | 4.92 | < .001***
emotions1 | -1.49 | > .999
emotions1 | 1.07 | > .999
emotions1 | 0.43 | > .999
emotions1 | -1.66 | > .999
emotions1 | 0.05 | > .999
emotions1 | 1.37 | > .999
emotions1 | 1.18 | > .999
emotions1 | 0.84 | > .999
emotions1 | -0.38 | > .999
emotions1 | 0.10 | > .999
emotions1 | -1.06 | > .999
emotions1 | -0.99 | > .999
emotions1 | 1.32 | > .999
emotions1 | 0.22 | > .999
emotions1 | 0.62 | > .999
emotions1 | -0.72 | > .999
emotions2 | 5.13 | < .001***
emotions2 | 10.37 | < .001***
emotions2 | -0.37 | > .999
emotions2 | -1.01 | > .999
emotions2 | -1.88 | > .999
emotions2 | -2.00 | > .999
emotions2 | -1.23 | > .999
emotions2 | 2.25 | > .999
emotions2 | 0.54 | > .999
emotions2 | 0.23 | > .999
emotions2 | 0.78 | > .999
emotions2 | -0.59 | > .999
emotions2 | 6.38 | < .001***
emotions2 | 2.60 | > .999
emotions2 | 6.11 | < .001***
emotions2 | 7.22 | < .001***
emotions2 | 2.22 | > .999
emotions2 | 2.40 | > .999
emotions2 | 5.28 | < .001***
emotions2 | -2.65 | > .999
emotions2 | 1.27 | > .999
emotions2 | 1.40 | > .999
emotions2 | -0.15 | > .999
emotions2 | 1.37 | > .999
emotions2 | 1.11 | > .999
emotions2 | 1.58 | > .999
emotions2 | 1.64 | > .999
emotions2 | -0.36 | > .999
emotions2 | 0.82 | > .999
emotions2 | -1.34 | > .999
emotions2 | -2.42 | > .999
emotions2 | -0.45 | > .999
emotions2 | 0.42 | > .999
emotions2 | 1.26 | > .999
emotions2 | 0.45 | > .999
emotions3 | 7.15 | < .001***
emotions3 | 7.06 | < .001***
emotions3 | 2.55 | > .999
emotions3 | 6.19 | < .001***
emotions3 | -0.51 | > .999
emotions3 | 0.31 | > .999
emotions3 | 4.16 | 0.021*
emotions3 | 3.68 | 0.141
emotions3 | 0.58 | > .999
emotions3 | 5.04 | < .001***
emotions3 | 2.09 | > .999
emotions3 | 3.10 | > .999
emotions3 | 6.32 | < .001***
emotions3 | 3.16 | 0.833
emotions3 | 3.54 | 0.228
emotions3 | -4.02 | 0.038*
emotions3 | -2.23 | > .999
emotions3 | 0.85 | > .999
emotions3 | 3.57 | 0.207
emotions3 | -5.16 | < .001***
emotions3 | -2.26 | > .999
emotions3 | -4.00 | 0.040*
emotions3 | -4.09 | 0.028*
emotions3 | -0.74 | > .999
emotions3 | -2.97 | > .999
emotions3 | -0.42 | > .999
emotions3 | 2.31 | > .999
emotions3 | 2.55 | > .999
emotions3 | 1.41 | > .999
emotions3 | -0.98 | > .999
emotions3 | -0.36 | > .999
emotions3 | -0.28 | > .999
emotions3 | -0.60 | > .999
emotions3 | -1.00 | > .999
emotions4 | 1.27 | > .999
emotions4 | 1.29 | > .999
emotions4 | 1.23 | > .999
emotions4 | -1.29 | > .999
emotions4 | 0.12 | > .999
emotions4 | 1.40 | > .999
emotions4 | -0.20 | > .999
emotions4 | -0.74 | > .999
emotions4 | 1.88 | > .999
emotions4 | 0.04 | > .999
emotions4 | 6.06 | < .001***
emotions4 | 3.04 | > .999
emotions4 | 6.01 | < .001***
emotions4 | 7.08 | < .001***
emotions4 | 0.38 | > .999
emotions4 | 0.78 | > .999
emotions4 | 3.57 | 0.207
emotions4 | 0.03 | > .999
emotions4 | -0.11 | > .999
emotions4 | 0.34 | > .999
emotions4 | -1.21 | > .999
emotions4 | -1.17 | > .999
emotions4 | 2.61 | > .999
emotions4 | 1.74 | > .999
emotions4 | 1.71 | > .999
emotions4 | -0.49 | > .999
emotions4 | -0.23 | > .999
emotions4 | -0.63 | > .999
emotions4 | 0.66 | > .999
emotions4 | -0.07 | > .999
emotions4 | -0.58 | > .999
emotions4 | -0.80 | > .999
emotions4 | -1.36 | > .999
emotions5 | 8.20 | < .001***
emotions5 | 10.13 | < .001***
emotions5 | -0.06 | > .999
emotions5 | -1.15 | > .999
emotions5 | 3.15 | 0.865
emotions5 | 4.32 | 0.011*
emotions5 | 0.35 | > .999
emotions5 | 6.29 | < .001***
emotions5 | -0.08 | > .999
emotions5 | -0.12 | > .999
emotions5 | 3.52 | 0.243
emotions5 | 0.72 | > .999
emotions5 | -0.13 | > .999
emotions5 | -4.17 | 0.021*
emotions5 | -3.92 | 0.055
emotions5 | -1.20 | > .999
emotions5 | 10.68 | < .001***
emotions5 | -4.46 | 0.006**
emotions5 | -2.64 | > .999
emotions5 | -2.40 | > .999
emotions5 | -4.29 | 0.013*
emotions5 | -4.35 | 0.010**
emotions5 | -5.26 | < .001***
emotions5 | -2.89 | > .999
emotions5 | 3.62 | 0.171
emotions5 | 3.21 | 0.711
emotions5 | 3.95 | 0.050*
emotions5 | -0.10 | > .999
emotions5 | 1.93 | > .999
emotions5 | 0.58 | > .999
emotions5 | -1.08 | > .999
emotions5 | -1.86 | > .999
emotions6 | 10.58 | < .001***
emotions6 | -0.94 | > .999
emotions6 | -0.82 | > .999
emotions6 | -8.12e-03 | > .999
emotions6 | 1.19 | > .999
emotions6 | 0.84 | > .999
emotions6 | 1.60 | > .999
emotions6 | -1.10 | > .999
emotions6 | -1.88 | > .999
emotions6 | 0.09 | > .999
emotions6 | 0.99 | > .999
emotions6 | -0.27 | > .999
emotions6 | 0.42 | > .999
emotions6 | 0.24 | > .999
emotions6 | -0.52 | > .999
emotions6 | 7.79 | < .001***
emotions6 | -0.46 | > .999
emotions6 | 0.06 | > .999
emotions6 | -1.17 | > .999
emotions6 | 0.32 | > .999
emotions6 | -0.39 | > .999
emotions6 | -0.06 | > .999
emotions6 | 0.48 | > .999
emotions6 | 2.29 | > .999
emotions6 | 1.86 | > .999
emotions6 | 1.63 | > .999
emotions6 | -0.44 | > .999
emotions6 | 0.20 | > .999
emotions6 | 0.89 | > .999
emotions6 | -1.90 | > .999
emotions6 | -0.52 | > .999
emotions7 | -0.48 | > .999
emotions7 | -0.06 | > .999
emotions7 | 1.62 | > .999
emotions7 | 3.36 | 0.435
emotions7 | 1.02 | > .999
emotions7 | 3.68 | 0.140
emotions7 | 1.14 | > .999
emotions7 | -1.13 | > .999
emotions7 | 1.91 | > .999
emotions7 | 0.32 | > .999
emotions7 | -0.80 | > .999
emotions7 | -1.76 | > .999
emotions7 | -2.03 | > .999
emotions7 | -0.76 | > .999
emotions7 | 10.25 | < .001***
emotions7 | -2.93 | > .999
emotions7 | -1.50 | > .999
emotions7 | -1.19 | > .999
emotions7 | -3.10 | > .999
emotions7 | -3.10 | > .999
emotions7 | -3.45 | 0.311
emotions7 | -0.89 | > .999
emotions7 | 3.65 | 0.155
emotions7 | 1.11 | > .999
emotions7 | 1.92 | > .999
emotions7 | -0.20 | > .999
emotions7 | 0.80 | > .999
emotions7 | 0.53 | > .999
emotions7 | -0.89 | > .999
emotions7 | -0.10 | > .999
attention1 | 17.73 | < .001***
attention1 | 4.84 | 0.001**
attention1 | -0.06 | > .999
attention1 | 1.57 | > .999
attention1 | -0.14 | > .999
attention1 | 2.67 | > .999
attention1 | 0.30 | > .999
attention1 | 0.60 | > .999
attention1 | 0.62 | > .999
attention1 | -1.11 | > .999
attention1 | 0.28 | > .999
attention1 | 1.44 | > .999
attention1 | 0.11 | > .999
attention1 | 0.73 | > .999
attention1 | -0.73 | > .999
attention1 | -0.43 | > .999
attention1 | 0.37 | > .999
attention1 | -0.80 | > .999
attention1 | 0.23 | > .999
attention1 | -8.35e-16 | > .999
attention1 | -0.13 | > .999
attention1 | -0.51 | > .999
attention1 | -0.14 | > .999
attention1 | 0.43 | > .999
attention1 | 2.70 | > .999
attention1 | 0.84 | > .999
attention1 | 1.34 | > .999
attention1 | 1.94 | > .999
attention1 | 0.41 | > .999
attention2 | 5.50 | < .001***
attention2 | 0.96 | > .999
attention2 | 2.54 | > .999
attention2 | 1.56 | > .999
attention2 | 2.79 | > .999
attention2 | 2.25 | > .999
attention2 | 1.70 | > .999
attention2 | 1.67 | > .999
attention2 | 0.97 | > .999
attention2 | 0.33 | > .999
attention2 | 2.02 | > .999
attention2 | 1.47 | > .999
attention2 | -0.11 | > .999
attention2 | -0.50 | > .999
attention2 | -1.14 | > .999
attention2 | -0.54 | > .999
attention2 | -1.11 | > .999
attention2 | 0.60 | > .999
attention2 | -0.97 | > .999
attention2 | -0.72 | > .999
attention2 | 0.24 | > .999
attention2 | -1.02 | > .999
attention2 | -0.72 | > .999
attention2 | 1.56 | > .999
attention2 | -0.32 | > .999
attention2 | 1.58 | > .999
attention2 | 1.29 | > .999
attention2 | 0.72 | > .999
attention3 | 4.01 | 0.039*
attention3 | 3.46 | 0.306
attention3 | 4.70 | 0.002**
attention3 | 11.63 | < .001***
attention3 | 7.86 | < .001***
attention3 | 19.89 | < .001***
attention3 | 6.11 | < .001***
attention3 | 5.75 | < .001***
attention3 | -1.93 | > .999
attention3 | -0.37 | > .999
attention3 | 4.96 | < .001***
attention3 | 3.69 | 0.134
attention3 | -3.82 | 0.083
attention3 | -2.60 | > .999
attention3 | -3.33 | 0.481
attention3 | -4.67 | 0.002**
attention3 | -1.64 | > .999
attention3 | -2.15 | > .999
attention3 | -0.51 | > .999
attention3 | 3.52 | 0.248
attention3 | 1.81 | > .999
attention3 | 2.74 | > .999
attention3 | 2.12 | > .999
attention3 | 3.20 | 0.732
attention3 | 0.95 | > .999
attention3 | 0.38 | > .999
attention3 | -1.36 | > .999
psychdistance1 | 8.89 | < .001***
psychdistance1 | 11.41 | < .001***
psychdistance1 | 3.67 | 0.143
psychdistance1 | 2.00 | > .999
psychdistance1 | 5.86 | < .001***
psychdistance1 | 1.02 | > .999
psychdistance1 | 1.45 | > .999
psychdistance1 | -2.64 | > .999
psychdistance1 | -2.15 | > .999
psychdistance1 | 0.26 | > .999
psychdistance1 | 3.08 | > .999
psychdistance1 | -4.17 | 0.021*
psychdistance1 | -3.25 | 0.626
psychdistance1 | -2.36 | > .999
psychdistance1 | -3.50 | 0.270
psychdistance1 | -0.20 | > .999
psychdistance1 | -2.22 | > .999
psychdistance1 | -0.47 | > .999
psychdistance1 | 1.08 | > .999
psychdistance1 | 0.93 | > .999
psychdistance1 | 1.08 | > .999
psychdistance1 | -1.93 | > .999
psychdistance1 | 1.12 | > .999
psychdistance1 | -0.08 | > .999
psychdistance1 | 0.67 | > .999
psychdistance1 | -1.18 | > .999
psychdistance2 | 6.44 | < .001***
psychdistance2 | 3.00 | > .999
psychdistance2 | 1.93 | > .999
psychdistance2 | 4.26 | 0.014*
psychdistance2 | 0.41 | > .999
psychdistance2 | 1.29 | > .999
psychdistance2 | -0.47 | > .999
psychdistance2 | -0.13 | > .999
psychdistance2 | 0.14 | > .999
psychdistance2 | 2.12 | > .999
psychdistance2 | -2.08 | > .999
psychdistance2 | -0.90 | > .999
psychdistance2 | -1.18 | > .999
psychdistance2 | -1.87 | > .999
psychdistance2 | 1.22 | > .999
psychdistance2 | -1.35 | > .999
psychdistance2 | 0.89 | > .999
psychdistance2 | -1.24 | > .999
psychdistance2 | -1.11 | > .999
psychdistance2 | -1.10 | > .999
psychdistance2 | -1.35 | > .999
psychdistance2 | 0.40 | > .999
psychdistance2 | 2.15 | > .999
psychdistance2 | 3.08 | > .999
psychdistance2 | 1.16 | > .999
psychdistance3 | 1.70 | > .999
psychdistance3 | 2.59 | > .999
psychdistance3 | 5.37 | < .001***
psychdistance3 | 0.87 | > .999
psychdistance3 | 1.49 | > .999
psychdistance3 | -3.15 | 0.860
psychdistance3 | -1.90 | > .999
psychdistance3 | 0.05 | > .999
psychdistance3 | 2.78 | > .999
psychdistance3 | -4.81 | 0.001**
psychdistance3 | -3.49 | 0.271
psychdistance3 | -3.45 | 0.313
psychdistance3 | -5.04 | < .001***
psychdistance3 | -1.26 | > .999
psychdistance3 | -3.05 | > .999
psychdistance3 | -1.02 | > .999
psychdistance3 | 0.57 | > .999
psychdistance3 | 2.48 | > .999
psychdistance3 | 0.96 | > .999
psychdistance3 | -1.72 | > .999
psychdistance3 | 1.85 | > .999
psychdistance3 | -0.69 | > .999
psychdistance3 | 0.28 | > .999
psychdistance3 | -2.43 | > .999
liking1 | 6.67 | < .001***
liking1 | 13.89 | < .001***
liking1 | 6.30 | < .001***
liking1 | 4.23 | 0.016*
liking1 | 0.64 | > .999
liking1 | 0.81 | > .999
liking1 | 4.56 | 0.004**
liking1 | 3.14 | 0.895
liking1 | -1.32 | > .999
liking1 | -0.63 | > .999
liking1 | -1.97 | > .999
liking1 | -2.17 | > .999
liking1 | -0.24 | > .999
liking1 | -0.59 | > .999
liking1 | 0.73 | > .999
liking1 | 2.03 | > .999
liking1 | 0.46 | > .999
liking1 | -1.15 | > .999
liking1 | 2.46 | > .999
liking1 | 3.04 | > .999
liking1 | -0.03 | > .999
liking1 | -0.17 | > .999
liking1 | -0.68 | > .999
liking2 | 9.22 | < .001***
liking2 | 13.85 | < .001***
liking2 | 14.30 | < .001***
liking2 | 5.39 | < .001***
liking2 | 7.26 | < .001***
liking2 | 14.03 | < .001***
liking2 | -1.18 | > .999
liking2 | 2.99 | > .999
liking2 | 3.47 | 0.289
liking2 | 1.16 | > .999
liking2 | 1.79 | > .999
liking2 | 0.11 | > .999
liking2 | 0.12 | > .999
liking2 | 0.47 | > .999
liking2 | 0.09 | > .999
liking2 | 0.70 | > .999
liking2 | 0.16 | > .999
liking2 | -1.42 | > .999
liking2 | 1.62 | > .999
liking2 | 1.16 | > .999
liking2 | 1.43 | > .999
liking2 | -0.77 | > .999
liking3 | 6.73 | < .001***
liking3 | 6.88 | < .001***
liking3 | -2.27 | > .999
liking3 | -1.19 | > .999
liking3 | 5.40 | < .001***
liking3 | 4.39 | 0.008**
liking3 | -4.42 | 0.007**
liking3 | -2.34 | > .999
liking3 | -3.65 | 0.154
liking3 | -4.33 | 0.011*
liking3 | -1.01 | > .999
liking3 | -2.23 | > .999
liking3 | -0.58 | > .999
liking3 | 3.96 | 0.048*
liking3 | 2.61 | > .999
liking3 | 2.73 | > .999
liking3 | 0.66 | > .999
liking3 | 3.31 | 0.508
liking3 | 0.76 | > .999
liking3 | 0.59 | > .999
liking3 | -1.82 | > .999
liking4 | 12.97 | < .001***
liking4 | 7.43 | < .001***
liking4 | 7.69 | < .001***
liking4 | 12.77 | < .001***
liking4 | 0.54 | > .999
liking4 | 5.03 | < .001***
liking4 | 4.22 | 0.017*
liking4 | -0.03 | > .999
liking4 | 2.76 | > .999
liking4 | -0.23 | > .999
liking4 | 0.93 | > .999
liking4 | 0.67 | > .999
liking4 | 1.04 | > .999
liking4 | -9.87e-03 | > .999
liking4 | 0.04 | > .999
liking4 | 1.47 | > .999
liking4 | 1.22 | > .999
liking4 | 1.93 | > .999
liking4 | 1.49 | > .999
liking4 | 0.36 | > .999
liking5 | 7.55 | < .001***
liking5 | 7.75 | < .001***
liking5 | 12.76 | < .001***
liking5 | -1.47 | > .999
liking5 | 3.83 | 0.079
liking5 | 3.01 | > .999
liking5 | 1.19 | > .999
liking5 | 2.11 | > .999
liking5 | 1.65 | > .999
liking5 | 1.41 | > .999
liking5 | 1.20 | > .999
liking5 | 1.16 | > .999
liking5 | -0.45 | > .999
liking5 | -0.35 | > .999
liking5 | -0.78 | > .999
liking5 | 0.63 | > .999
liking5 | 0.77 | > .999
liking5 | 0.23 | > .999
liking5 | 0.22 | > .999
humor1 | 22.93 | < .001***
humor1 | 12.95 | < .001***
humor1 | -1.45 | > .999
humor1 | 13.94 | < .001***
humor1 | 10.44 | < .001***
humor1 | 6.22 | < .001***
humor1 | 11.24 | < .001***
humor1 | 3.23 | 0.658
humor1 | 3.92 | 0.057
humor1 | 3.68 | 0.140
humor1 | -1.34 | > .999
humor1 | -2.35 | > .999
humor1 | -2.76 | > .999
humor1 | -1.03 | > .999
humor1 | -0.55 | > .999
humor1 | 1.76 | > .999
humor1 | 3.46 | 0.300
humor1 | 3.55 | 0.223
humor2 | 15.42 | < .001***
humor2 | -1.73 | > .999
humor2 | 10.90 | < .001***
humor2 | 9.02 | < .001***
humor2 | 4.70 | 0.002**
humor2 | 9.73 | < .001***
humor2 | 2.70 | > .999
humor2 | 3.05 | > .999
humor2 | 2.00 | > .999
humor2 | -1.09 | > .999
humor2 | -2.00 | > .999
humor2 | -2.48 | > .999
humor2 | -2.92 | > .999
humor2 | -0.43 | > .999
humor2 | 1.72 | > .999
humor2 | 3.26 | 0.597
humor2 | 2.65 | > .999
humor3 | -0.62 | > .999
humor3 | 7.19 | < .001***
humor3 | 6.07 | < .001***
humor3 | 2.90 | > .999
humor3 | 5.45 | < .001***
humor3 | 0.86 | > .999
humor3 | 0.77 | > .999
humor3 | 1.22 | > .999
humor3 | 0.73 | > .999
humor3 | 0.94 | > .999
humor3 | 0.10 | > .999
humor3 | -1.67 | > .999
humor3 | 0.51 | > .999
humor3 | 1.21 | > .999
humor3 | 1.79 | > .999
humor3 | 1.34 | > .999
aversiveness | -2.98 | > .999
aversiveness | -1.76 | > .999
aversiveness | -4.04 | 0.035*
aversiveness | -2.74 | > .999
aversiveness | -3.75 | 0.107
aversiveness | -4.56 | 0.004**
aversiveness | -1.80 | > .999
aversiveness | 4.79 | 0.001**
aversiveness | 3.63 | 0.169
aversiveness | 4.01 | 0.039*
aversiveness | 3.39 | 0.389
aversiveness | 1.58 | > .999
aversiveness | 1.36 | > .999
aversiveness | -0.18 | > .999
aversiveness | -0.33 | > .999
messagediscounting1 | 18.00 | < .001***
messagediscounting1 | 12.53 | < .001***
messagediscounting1 | 19.15 | < .001***
messagediscounting1 | 1.64 | > .999
messagediscounting1 | 4.04 | 0.035*
messagediscounting1 | 2.21 | > .999
messagediscounting1 | -0.57 | > .999
messagediscounting1 | -1.31 | > .999
messagediscounting1 | -0.50 | > .999
messagediscounting1 | -0.25 | > .999
messagediscounting1 | -1.65 | > .999
messagediscounting1 | -0.90 | > .999
messagediscounting1 | 1.50 | > .999
messagediscounting1 | 1.55 | > .999
messagediscounting2 | 11.06 | < .001***
messagediscounting2 | 15.45 | < .001***
messagediscounting2 | 1.07 | > .999
messagediscounting2 | 2.96 | > .999
messagediscounting2 | 0.97 | > .999
messagediscounting2 | 0.56 | > .999
messagediscounting2 | 0.04 | > .999
messagediscounting2 | 0.81 | > .999
messagediscounting2 | -0.27 | > .999
messagediscounting2 | -2.07 | > .999
messagediscounting2 | -0.85 | > .999
messagediscounting2 | 1.20 | > .999
messagediscounting2 | 1.39 | > .999
messagediscounting3 | 9.32 | < .001***
messagediscounting3 | -0.26 | > .999
messagediscounting3 | 1.47 | > .999
messagediscounting3 | 0.26 | > .999
messagediscounting3 | -1.48 | > .999
messagediscounting3 | -1.56 | > .999
messagediscounting3 | -0.72 | > .999
messagediscounting3 | -2.70 | > .999
messagediscounting3 | -2.22 | > .999
messagediscounting3 | -1.20 | > .999
messagediscounting3 | 1.64 | > .999
messagediscounting3 | 2.60 | > .999
messagediscounting4 | 1.67 | > .999
messagediscounting4 | 3.45 | 0.319
messagediscounting4 | 1.69 | > .999
messagediscounting4 | -0.58 | > .999
messagediscounting4 | -0.94 | > .999
messagediscounting4 | -0.57 | > .999
messagediscounting4 | -2.22 | > .999
messagediscounting4 | -3.30 | 0.517
messagediscounting4 | 0.21 | > .999
messagediscounting4 | 2.11 | > .999
messagediscounting4 | 1.80 | > .999
attitudepositive1 | 11.75 | < .001***
attitudepositive1 | 11.85 | < .001***
attitudepositive1 | -13.54 | < .001***
attitudepositive1 | -7.80 | < .001***
attitudepositive1 | -6.68 | < .001***
attitudepositive1 | 0.56 | > .999
attitudepositive1 | -0.95 | > .999
attitudepositive1 | -0.43 | > .999
attitudepositive1 | 2.84 | > .999
attitudepositive1 | 1.30 | > .999
attitudepositive2 | 9.37 | < .001***
attitudepositive2 | -7.45 | < .001***
attitudepositive2 | -11.74 | < .001***
attitudepositive2 | -6.60 | < .001***
attitudepositive2 | -0.46 | > .999
attitudepositive2 | -0.12 | > .999
attitudepositive2 | -0.49 | > .999
attitudepositive2 | 3.13 | 0.914
attitudepositive2 | 2.38 | > .999
attitudepositive3 | -5.11 | < .001***
attitudepositive3 | -4.91 | < .001***
attitudepositive3 | -10.85 | < .001***
attitudepositive3 | 0.32 | > .999
attitudepositive3 | -0.72 | > .999
attitudepositive3 | -1.07 | > .999
attitudepositive3 | 3.42 | 0.353
attitudepositive3 | 2.33 | > .999
attitudenegative1 | 12.47 | < .001***
attitudenegative1 | 11.08 | < .001***
attitudenegative1 | -1.00 | > .999
attitudenegative1 | 1.25 | > .999
attitudenegative1 | -0.19 | > .999
attitudenegative1 | -1.75 | > .999
attitudenegative1 | -2.32 | > .999
attitudenegative2 | 10.68 | < .001***
attitudenegative2 | -0.84 | > .999
attitudenegative2 | 1.41 | > .999
attitudenegative2 | -0.57 | > .999
attitudenegative2 | -2.51 | > .999
attitudenegative2 | -4.84 | 0.001**
attitudenegative3 | 0.38 | > .999
attitudenegative3 | 0.59 | > .999
attitudenegative3 | 0.41 | > .999
attitudenegative3 | -2.50 | > .999
attitudenegative3 | -3.04 | > .999
age | 6.19 | < .001***
age | 3.53 | 0.241
age | 0.72 | > .999
age | -1.52 | > .999
newsconsumption1 | 6.40 | < .001***
newsconsumption1 | 2.63 | > .999
newsconsumption1 | 0.01 | > .999
newsconsumption2 | 4.19 | 0.019*
newsconsumption2 | 3.85 | 0.074
newsconsumption3 | 10.99 | < .001***
p-value adjustment method: Holm (1979)
Observations: 378what are the potential problems?
The resulting number of correlations are quite large because we asked for every single relation in the data. One problem is that we might not even want some of these contrasts - especially if we have for example separate DV and IVs that we are testing before a regression. In that case, we might want to only correlate the DV against IVs one time each, rather than correlate all the IVs together, and so on.
selecting specific variables for correlations
Here, one thing we want to know is whether or not there are internal correlations among similar scale items. How can we do that?
One method would be to create a subset of our data and then run the correlation command. We can use. a pipe to do this, as follows:
emotion_cor <- dat %>%
select(starts_with('emotion')) %>%
correlation()
emotion_cor# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(376) | p
--------------------------------------------------------------------
emotions1 | emotions2 | 0.53 | [ 0.45, 0.60] | 12.06 | < .001***
emotions1 | emotions3 | 0.38 | [ 0.29, 0.47] | 8.04 | < .001***
emotions1 | emotions4 | 0.55 | [ 0.47, 0.61] | 12.68 | < .001***
emotions1 | emotions5 | 0.11 | [ 0.01, 0.21] | 2.17 | 0.278
emotions1 | emotions6 | 0.03 | [-0.07, 0.13] | 0.57 | > .999
emotions1 | emotions7 | 0.03 | [-0.08, 0.13] | 0.50 | > .999
emotions2 | emotions3 | 0.26 | [ 0.16, 0.35] | 5.13 | < .001***
emotions2 | emotions4 | 0.47 | [ 0.39, 0.55] | 10.37 | < .001***
emotions2 | emotions5 | -0.02 | [-0.12, 0.08] | -0.37 | > .999
emotions2 | emotions6 | -0.05 | [-0.15, 0.05] | -1.01 | > .999
emotions2 | emotions7 | -0.10 | [-0.20, 0.00] | -1.88 | 0.491
emotions3 | emotions4 | 0.35 | [ 0.25, 0.43] | 7.15 | < .001***
emotions3 | emotions5 | 0.34 | [ 0.25, 0.43] | 7.06 | < .001***
emotions3 | emotions6 | 0.13 | [ 0.03, 0.23] | 2.55 | 0.111
emotions3 | emotions7 | 0.30 | [ 0.21, 0.39] | 6.19 | < .001***
emotions4 | emotions5 | 0.07 | [-0.04, 0.17] | 1.27 | > .999
emotions4 | emotions6 | 0.07 | [-0.03, 0.17] | 1.29 | > .999
emotions4 | emotions7 | 0.06 | [-0.04, 0.16] | 1.23 | > .999
emotions5 | emotions6 | 0.39 | [ 0.30, 0.47] | 8.20 | < .001***
emotions5 | emotions7 | 0.46 | [ 0.38, 0.54] | 10.13 | < .001***
emotions6 | emotions7 | 0.48 | [ 0.40, 0.55] | 10.58 | < .001***
p-value adjustment method: Holm (1979)
Observations: 378This is much easier to work with, although we might want to reprenst this as a more classic correlation matrix. We can do that with summary():
summary(emotion_cor)# Correlation Matrix (pearson-method)
Parameter | emotions7 | emotions6 | emotions5 | emotions4 | emotions3 | emotions2
---------------------------------------------------------------------------------
emotions1 | 0.03 | 0.03 | 0.11 | 0.55*** | 0.38*** | 0.53***
emotions2 | -0.10 | -0.05 | -0.02 | 0.47*** | 0.26*** |
emotions3 | 0.30*** | 0.13 | 0.34*** | 0.35*** | |
emotions4 | 0.06 | 0.07 | 0.07 | | |
emotions5 | 0.46*** | 0.39*** | | | |
emotions6 | 0.48*** | | | | |
p-value adjustment method: Holm (1979)We can also obtain heatmap style plots of the correlations 8)
plot(summary(emotion_cor))
using group_by() arguments
The correlation function plays well with group_by() in tidyverse. For example, let’s compare correlations among humor ratings for satire/non-satire. W
humor_cor <- dat %>%
select(starts_with('humor'), condition) %>%
group_by(condition) %>%
correlation()We obtain a grouped set of correlations!
humor_cor# Correlation Matrix (pearson-method)
Group | Parameter1 | Parameter2 | r | 95% CI | t | df | p
-------------------------------------------------------------------------------
reg | humor1 | humor2 | 0.56 | [0.45, 0.65] | 9.23 | 189 | < .001***
reg | humor1 | humor3 | 0.29 | [0.15, 0.41] | 4.17 | 189 | < .001***
reg | humor2 | humor3 | 0.47 | [0.36, 0.58] | 7.39 | 189 | < .001***
sat | humor1 | humor2 | 0.81 | [0.76, 0.86] | 19.05 | 185 | < .001***
sat | humor1 | humor3 | 0.64 | [0.55, 0.72] | 11.33 | 185 | < .001***
sat | humor2 | humor3 | 0.66 | [0.58, 0.74] | 12.11 | 185 | < .001***
p-value adjustment method: Holm (1979)
Observations: 187-191And we can also obtain the same matrix:
summary(humor_cor)# Correlation Matrix (pearson-method)
Group | Parameter | humor3 | humor2
-------------------------------------
reg | humor1 | 0.29*** | 0.56***
reg | humor2 | 0.47*** |
sat | humor1 | 0.64*** | 0.81***
sat | humor2 | 0.66*** |
p-value adjustment method: Holm (1979)using the select() arguments
Even though we are selecting smaller subsets of our data, we are still correlating everything against everything else. However we might not always want to do this.
Let’s say that we want to correlate the psychdistance1 variable with all of the emotion and humor variables. We can specify the nature of the correlations using the select() and select2() arguments within correlation.
For example:
# show the correlation between vars in select() and select2()
correlation(dat, select = "psychdistance1",
select2 = c('emotions1',
'emotions2',
'emotions3',
'emotions4',
'emotions5',
'emotions6',
'emotions7'))# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(376) | p
------------------------------------------------------------------------
psychdistance1 | emotions1 | 0.07 | [-0.03, 0.17] | 1.44 | 0.600
psychdistance1 | emotions2 | 0.03 | [-0.07, 0.13] | 0.54 | > .999
psychdistance1 | emotions3 | 0.19 | [ 0.09, 0.28] | 3.68 | 0.002**
psychdistance1 | emotions4 | -0.01 | [-0.11, 0.09] | -0.20 | > .999
psychdistance1 | emotions5 | 0.22 | [ 0.12, 0.31] | 4.32 | < .001***
psychdistance1 | emotions6 | 0.06 | [-0.04, 0.16] | 1.19 | 0.710
psychdistance1 | emotions7 | 0.17 | [ 0.07, 0.27] | 3.36 | 0.004**
p-value adjustment method: Holm (1979)
Observations: 378This method means that we do not need to create subsets of the data, but instead need to create selections of variables from the larger dataframe. We could for instance create a vector of variable names from our df first
target_vars <- c(paste0('emotions', seq(1:7)), paste0('humor', 1:3))
target_vars [1] "emotions1" "emotions2" "emotions3" "emotions4" "emotions5" "emotions6"
[7] "emotions7" "humor1" "humor2" "humor3" And then pass this vector to the select2() argument:
correlation(dat, select = 'psychdistance1', select2 = target_vars)# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(376) | p
-------------------------------------------------------------------------
psychdistance1 | emotions1 | 0.07 | [-0.03, 0.17] | 1.44 | 0.750
psychdistance1 | emotions2 | 0.03 | [-0.07, 0.13] | 0.54 | > .999
psychdistance1 | emotions3 | 0.19 | [ 0.09, 0.28] | 3.68 | 0.002**
psychdistance1 | emotions4 | -0.01 | [-0.11, 0.09] | -0.20 | > .999
psychdistance1 | emotions5 | 0.22 | [ 0.12, 0.31] | 4.32 | < .001***
psychdistance1 | emotions6 | 0.06 | [-0.04, 0.16] | 1.19 | 0.946
psychdistance1 | emotions7 | 0.17 | [ 0.07, 0.27] | 3.36 | 0.007**
psychdistance1 | humor1 | -0.14 | [-0.23, -0.03] | -2.64 | 0.060
psychdistance1 | humor2 | -0.11 | [-0.21, -0.01] | -2.15 | 0.193
psychdistance1 | humor3 | 0.01 | [-0.09, 0.11] | 0.26 | > .999
p-value adjustment method: Holm (1979)
Observations: 378combine it all
Now we can also do this with a grouped dataframe:
pdcor2 <- dat %>%
group_by(condition) %>%
correlation(select = 'psychdistance1', select2 = target_vars)The results in raw form:
pdcor2# Correlation Matrix (pearson-method)
Group | Parameter1 | Parameter2 | r | 95% CI | t | df | p
--------------------------------------------------------------------------------------
reg | psychdistance1 | emotions1 | 0.03 | [-0.11, 0.17] | 0.38 | 189 | > .999
reg | psychdistance1 | emotions2 | -1.49e-03 | [-0.14, 0.14] | -0.02 | 189 | > .999
reg | psychdistance1 | emotions3 | 0.12 | [-0.02, 0.26] | 1.68 | 189 | 0.750
reg | psychdistance1 | emotions4 | -7.95e-03 | [-0.15, 0.13] | -0.11 | 189 | > .999
reg | psychdistance1 | emotions5 | 0.20 | [ 0.05, 0.33] | 2.74 | 189 | 0.068
reg | psychdistance1 | emotions6 | 0.07 | [-0.07, 0.21] | 0.94 | 189 | > .999
reg | psychdistance1 | emotions7 | 0.16 | [ 0.02, 0.30] | 2.25 | 189 | 0.233
reg | psychdistance1 | humor1 | -0.06 | [-0.20, 0.09] | -0.78 | 189 | > .999
reg | psychdistance1 | humor2 | -0.02 | [-0.16, 0.13] | -0.21 | 189 | > .999
reg | psychdistance1 | humor3 | 0.09 | [-0.05, 0.23] | 1.22 | 189 | > .999
sat | psychdistance1 | emotions1 | 0.12 | [-0.02, 0.26] | 1.70 | 185 | 0.639
sat | psychdistance1 | emotions2 | 0.05 | [-0.09, 0.20] | 0.74 | 185 | > .999
sat | psychdistance1 | emotions3 | 0.20 | [ 0.06, 0.33] | 2.79 | 185 | 0.052
sat | psychdistance1 | emotions4 | -0.04 | [-0.18, 0.11] | -0.50 | 185 | > .999
sat | psychdistance1 | emotions5 | 0.21 | [ 0.06, 0.34] | 2.86 | 185 | 0.047*
sat | psychdistance1 | emotions6 | 0.04 | [-0.10, 0.19] | 0.60 | 185 | > .999
sat | psychdistance1 | emotions7 | 0.15 | [ 0.01, 0.29] | 2.04 | 185 | 0.338
sat | psychdistance1 | humor1 | -0.11 | [-0.25, 0.03] | -1.51 | 185 | 0.802
sat | psychdistance1 | humor2 | -0.10 | [-0.24, 0.04] | -1.41 | 185 | 0.804
sat | psychdistance1 | humor3 | 0.02 | [-0.12, 0.16] | 0.28 | 185 | > .999
p-value adjustment method: Holm (1979)
Observations: 187-191And summary matrix:
summary(pdcor2)# Correlation Matrix (pearson-method)
Group | Parameter | emotions1 | emotions2 | emotions3 | emotions4
----------------------------------------------------------------------
reg | psychdistance1 | 0.03 | 0.00 | 0.12 | -0.01
sat | psychdistance1 | 0.12 | 0.05 | 0.20 | -0.04
Group | emotions5 | emotions6 | emotions7 | humor1 | humor2 | humor3
--------------------------------------------------------------------
reg | 0.20 | 0.07 | 0.16 | -0.06 | -0.02 | 0.09
sat | 0.21* | 0.04 | 0.15 | -0.11 | -0.10 | 0.02
p-value adjustment method: Holm (1979)adjusting the types of correlations
The default correlation is a pearson product moment correlation. But we can ask for other types, such as non-parametric Spearman’s or Kendall’s, Bayesian correlations, or multilevel correlations. To change this, we use the method argument:
# calculate spearman correlations
correlation(dat, select = 'psychdistance1',
select2 = target_vars,
method = 'spearman')# Correlation Matrix (spearman-method)
Parameter1 | Parameter2 | rho | 95% CI | S | p
-------------------------------------------------------------------------------
psychdistance1 | emotions1 | 0.05 | [-0.05, 0.15] | 8.54e+06 | > .999
psychdistance1 | emotions2 | 1.10e-03 | [-0.10, 0.10] | 8.99e+06 | > .999
psychdistance1 | emotions3 | 0.18 | [ 0.07, 0.28] | 7.41e+06 | 0.005**
psychdistance1 | emotions4 | -0.04 | [-0.14, 0.06] | 9.36e+06 | > .999
psychdistance1 | emotions5 | 0.22 | [ 0.11, 0.31] | 7.06e+06 | < .001***
psychdistance1 | emotions6 | 0.05 | [-0.05, 0.16] | 8.53e+06 | > .999
psychdistance1 | emotions7 | 0.17 | [ 0.07, 0.27] | 7.46e+06 | 0.006**
psychdistance1 | humor1 | -0.14 | [-0.24, -0.04] | 1.03e+07 | 0.039*
psychdistance1 | humor2 | -0.12 | [-0.22, -0.02] | 1.01e+07 | 0.118
psychdistance1 | humor3 | -8.32e-03 | [-0.11, 0.10] | 9.08e+06 | > .999
p-value adjustment method: Holm (1979)
Observations: 378p-value adjustments
You can also choose among different methods for p-value adjustments (including not adjusting them at all!). The default method adjusts using the Holm method, and is one reason why we probably do not want to calculate all possible correlations in our data (as this will create penalised p-values that might not make sense for our data!)
# the default method
correlation(dat, select = 'psychdistance1',
select2 = target_vars,
p_adjust = 'holm')# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(376) | p
-------------------------------------------------------------------------
psychdistance1 | emotions1 | 0.07 | [-0.03, 0.17] | 1.44 | 0.750
psychdistance1 | emotions2 | 0.03 | [-0.07, 0.13] | 0.54 | > .999
psychdistance1 | emotions3 | 0.19 | [ 0.09, 0.28] | 3.68 | 0.002**
psychdistance1 | emotions4 | -0.01 | [-0.11, 0.09] | -0.20 | > .999
psychdistance1 | emotions5 | 0.22 | [ 0.12, 0.31] | 4.32 | < .001***
psychdistance1 | emotions6 | 0.06 | [-0.04, 0.16] | 1.19 | 0.946
psychdistance1 | emotions7 | 0.17 | [ 0.07, 0.27] | 3.36 | 0.007**
psychdistance1 | humor1 | -0.14 | [-0.23, -0.03] | -2.64 | 0.060
psychdistance1 | humor2 | -0.11 | [-0.21, -0.01] | -2.15 | 0.193
psychdistance1 | humor3 | 0.01 | [-0.09, 0.11] | 0.26 | > .999
p-value adjustment method: Holm (1979)
Observations: 378# change to the more conservative bonferroni, notice the higher p values
correlation(dat, select = 'psychdistance1',
select2 = target_vars,
p_adjust = 'bonferroni')# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(376) | p
-------------------------------------------------------------------------
psychdistance1 | emotions1 | 0.07 | [-0.03, 0.17] | 1.44 | > .999
psychdistance1 | emotions2 | 0.03 | [-0.07, 0.13] | 0.54 | > .999
psychdistance1 | emotions3 | 0.19 | [ 0.09, 0.28] | 3.68 | 0.003**
psychdistance1 | emotions4 | -0.01 | [-0.11, 0.09] | -0.20 | > .999
psychdistance1 | emotions5 | 0.22 | [ 0.12, 0.31] | 4.32 | < .001***
psychdistance1 | emotions6 | 0.06 | [-0.04, 0.16] | 1.19 | > .999
psychdistance1 | emotions7 | 0.17 | [ 0.07, 0.27] | 3.36 | 0.009**
psychdistance1 | humor1 | -0.14 | [-0.23, -0.03] | -2.64 | 0.085
psychdistance1 | humor2 | -0.11 | [-0.21, -0.01] | -2.15 | 0.322
psychdistance1 | humor3 | 0.01 | [-0.09, 0.11] | 0.26 | > .999
p-value adjustment method: Bonferroni
Observations: 378# i don't want to adjust my p values!
correlation(dat, select = 'psychdistance1',
select2 = target_vars,
p_adjust = 'none')# Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(376) | p
-------------------------------------------------------------------------
psychdistance1 | emotions1 | 0.07 | [-0.03, 0.17] | 1.44 | 0.150
psychdistance1 | emotions2 | 0.03 | [-0.07, 0.13] | 0.54 | 0.589
psychdistance1 | emotions3 | 0.19 | [ 0.09, 0.28] | 3.68 | < .001***
psychdistance1 | emotions4 | -0.01 | [-0.11, 0.09] | -0.20 | 0.842
psychdistance1 | emotions5 | 0.22 | [ 0.12, 0.31] | 4.32 | < .001***
psychdistance1 | emotions6 | 0.06 | [-0.04, 0.16] | 1.19 | 0.237
psychdistance1 | emotions7 | 0.17 | [ 0.07, 0.27] | 3.36 | < .001***
psychdistance1 | humor1 | -0.14 | [-0.23, -0.03] | -2.64 | 0.009**
psychdistance1 | humor2 | -0.11 | [-0.21, -0.01] | -2.15 | 0.032*
psychdistance1 | humor3 | 0.01 | [-0.09, 0.11] | 0.26 | 0.792
p-value adjustment method: none
Observations: 378