This output includes primary and exploratory analyses conducted on US-based participants.

This analysis is based on the following packages.

library(readr)
library(dplyr)
library(psych)
library(haven)
library(broom)
library(papaja)
library(knitr)
library(ggplot2)

Begin by reading in the data and creating subsets for use in different analyses.

df <- read_sav("US_munged_correctspelling.sav")

# Recode Petition for bionomial
df <- df %>% 
  mutate(Petition_RC = Petition - 1)

# Remove "Neither" ideology from dataset for primary analysis
df_ideological <- df %>% 
  filter(IdeologyLibCons!=3)

# Create manipulation checks passed dataset
df_passed <- df_ideological %>% 
  filter((Source == "Radical" & MC_Source == 1) | 
         (Source == "Environmental" & MC_Source == 2) |
         (Source == "Doctor" & MC_Source == 3)) %>% ## Filter based on MC Check 1
  filter((Action == "Individual" & MC_Message == 1) |
         (Action == "Collective" & MC_Message == 2) |
         (Action == "No Behaviour" & MC_Message == 3))

# Create manipulation checks passed dataset for exploratory analyses
df_passed_explor <- df %>% 
  filter((Source == "Radical" & MC_Source == 1) | 
         (Source == "Environmental" & MC_Source == 2) |
         (Source == "Doctor" & MC_Source == 3)) %>% ## Filter based on MC Check 1
  filter((Action == "Individual" & MC_Message == 1) |
         (Action == "Collective" & MC_Message == 2) |
         (Action == "No Behaviour" & MC_Message == 3))

All liberal and conservative participants

These analyses include all participants who indicated that they were liberal or conservative (i.e. the independents are removed). However, here participants have not been removed for failing manipulation checks.

Investigate Petition Signing

Frequency of signing behaviour by group

df_ideological %>%
  group_by(Action, Source, IdeologyLibCons) %>%
  summarise("Declined Signing"=sum(Petition_RC)) %>% 
  apa_table(caption="Frequency of signing behaviour by group")

(#tab:freq) Frequency of signing behaviour by group

Action	Source	IdeologyLibCons	Declined Signing
Collective	Doctor	1	7.00
Collective	Doctor	2	16.00
Collective	Environmental	1	9.00
Collective	Environmental	2	18.00
Collective	Radical	1	10.00
Collective	Radical	2	13.00
Individual	Doctor	1	8.00
Individual	Doctor	2	20.00
Individual	Environmental	1	14.00
Individual	Environmental	2	15.00
Individual	Radical	1	12.00
Individual	Radical	2	12.00
No Behaviour	Doctor	1	13.00
No Behaviour	Doctor	2	18.00
No Behaviour	Environmental	1	9.00
No Behaviour	Environmental	2	17.00
No Behaviour	Radical	1	9.00
No Behaviour	Radical	2	17.00

Binomial logistic regression

Log liklihood of signing the petition was investigated using the generalised linear model and the binomial distribution. Petition signing was predicted by Source, Suggested Action, and their interaction.

Petition_analysis <- glm(Petition_RC ~ Source*Action, family="binomial", data=df_ideological)
tidy(Petition_analysis) %>% 
  apa_table()

(#tab:unnamed-chunk-3) **

term	estimate	std.error	statistic	p.value
(Intercept)	0.19	0.31	0.62	0.54
SourceEnvironmental	0.21	0.43	0.49	0.62
SourceRadical	-0.05	0.44	-0.12	0.91
ActionIndividual	0.58	0.46	1.26	0.21
ActionNo Behaviour	0.85	0.47	1.80	0.07
SourceEnvironmental:ActionIndividual	-0.25	0.64	-0.40	0.69
SourceRadical:ActionIndividual	-0.37	0.63	-0.58	0.56
SourceEnvironmental:ActionNo Behaviour	-0.88	0.64	-1.39	0.17
SourceRadical:ActionNo Behaviour	-0.62	0.64	-0.97	0.33

glance(Petition_analysis) %>% 
  apa_table()

(#tab:unnamed-chunk-3) **

null.deviance	df.null	logLik	AIC	BIC	deviance	df.residual
512.96	384	-253.16	524.31	559.89	506.31	376

Pro-environmental behaviour

Descriptives Citizenship Behaviour by Cell

data.frame(df_ideological) %>%
  group_by(Action, Source, IdeologyLibCons) %>%
  summarise(mean=mean(CitizenshipPEB_Total)) %>% 
  apa_table()

(#tab:unnamed-chunk-4) **

Action	Source	IdeologyLibCons	mean
Collective	Doctor	1	3.22
Collective	Doctor	2	2.04
Collective	Environmental	1	3.05
Collective	Environmental	2	2.05
Collective	Radical	1	3.45
Collective	Radical	2	2.09
Individual	Doctor	1	2.87
Individual	Doctor	2	2.02
Individual	Environmental	1	3.14
Individual	Environmental	2	1.91
Individual	Radical	1	2.91
Individual	Radical	2	2.21
No Behaviour	Doctor	1	2.54
No Behaviour	Doctor	2	2.02
No Behaviour	Environmental	1	3.22
No Behaviour	Environmental	2	1.88
No Behaviour	Radical	1	3.17
No Behaviour	Radical	2	2.07

Descriptives Independent Behaviour by Cell

data.frame(df_ideological) %>%
  group_by(Action, Source, IdeologyLibCons) %>%
  summarise(mean=mean(PersonalPEB_Total))  %>% 
  apa_table()

(#tab:unnamed-chunk-5) **

Action	Source	IdeologyLibCons	mean
Collective	Doctor	1	3.70
Collective	Doctor	2	3.50
Collective	Environmental	1	3.66
Collective	Environmental	2	3.17
Collective	Radical	1	4.22
Collective	Radical	2	3.29
Individual	Doctor	1	3.75
Individual	Doctor	2	3.13
Individual	Environmental	1	3.89
Individual	Environmental	2	3.38
Individual	Radical	1	3.78
Individual	Radical	2	3.50
No Behaviour	Doctor	1	3.53
No Behaviour	Doctor	2	3.40
No Behaviour	Environmental	1	3.80
No Behaviour	Environmental	2	3.19
No Behaviour	Radical	1	3.74
No Behaviour	Radical	2	3.53

MANOVA for Pro-Environmental Behaviour

Because of the two measures of pro-envionmental behaviour are correlated. A MANOVA was conducted to investigate the effect of Source, Suggested Action, and Ideology on the two DVs. Only individuals who indicated that they identified as “Liberal” or “Conservative” were included in the analysis.

# Investigate Pro-Environmental Behaviour
manova_analysis<-manova(cbind(CitizenshipPEB_Total, PersonalPEB_Total) ~ Source*as.factor(IdeologyLibCons)*Action, data=df_ideological)
summary(manova_analysis)

##                                           Df   Pillai approx F num Df
## Source                                     2 0.013691    1.265      4
## as.factor(IdeologyLibCons)                 1 0.246808   59.966      2
## Action                                     2 0.008095    0.746      4
## Source:as.factor(IdeologyLibCons)          2 0.005856    0.539      4
## Source:Action                              4 0.015804    0.731      8
## as.factor(IdeologyLibCons):Action          2 0.007541    0.694      4
## Source:as.factor(IdeologyLibCons):Action   4 0.034639    1.617      8
## Residuals                                367                         
##                                          den Df Pr(>F)    
## Source                                      734 0.2823    
## as.factor(IdeologyLibCons)                  366 <2e-16 ***
## Action                                      734 0.5610    
## Source:as.factor(IdeologyLibCons)           734 0.7072    
## Source:Action                               734 0.6644    
## as.factor(IdeologyLibCons):Action           734 0.5959    
## Source:as.factor(IdeologyLibCons):Action    734 0.1162    
## Residuals                                                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

ANOVA for Citizenship behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology (2) on Citizenship behaviours.

Citizenship_anova<-aov(CitizenshipPEB_Total ~ Source*as.factor(IdeologyLibCons)*Action, data=df_ideological)

res<-papaja::apa_print(Citizenship_anova)
apa_table(res$table)

(#tab:unnamed-chunk-7) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	1.45	2	367	0.90	.236	.008
As factorIdeologyLibCons	115.74	1	367	0.90	< .001	.240
Action	1.13	2	367	0.90	.325	.006
Source \(\times\) As factorIdeologyLibCons	1.06	2	367	0.90	.348	.006
Source \(\times\) Action	0.56	4	367	0.90	.693	.006
As factorIdeologyLibCons \(\times\) Action	0.60	2	367	0.90	.550	.003
Source \(\times\) As factorIdeologyLibCons \(\times\) Action	1.19	4	367	0.90	.316	.013

ANOVA for Personal behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology (2) on Personal behaviours.

PersonalPEB_anova<-aov(PersonalPEB_Total ~ Source*as.factor(IdeologyLibCons)*Action, data=df_ideological)

res<-papaja::apa_print(PersonalPEB_anova)
apa_table(res$table)

(#tab:unnamed-chunk-8) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	1.83	2	367	0.67	.162	.010
As factorIdeologyLibCons	29.92	1	367	0.67	< .001	.075
Action	0.12	2	367	0.67	.885	.001
Source \(\times\) As factorIdeologyLibCons	0.61	2	367	0.67	.547	.003
Source \(\times\) Action	0.74	4	367	0.67	.565	.008
As factorIdeologyLibCons \(\times\) Action	0.63	2	367	0.67	.531	.003
Source \(\times\) As factorIdeologyLibCons \(\times\) Action	1.51	4	367	0.67	.198	.016

Dataset that passed all manipulation checks

In this series of analyses we include only participants that have passed both manipulation checks. As with the previous series of analyses only participants who indicated that they were liberal or conservative were included (i.e. the independents are removed).

Investigate Petition Signing

Frequency of signing behaviour by group

data.frame(df_passed) %>%
  group_by(Action, Source, IdeologyLibCons) %>%
  summarise("Declined Signing"=sum(Petition_RC))

Binomial logistic regression

Petition_analysis<-glm(Petition_RC ~ Source*Action, family="binomial", data=df_passed)
tidy(Petition_analysis)

glance(Petition_analysis)

Pro-environmental behaviour

Descriptives Citizenship Behaviour by Cell

data.frame(df_passed) %>%
  group_by(Action, Source, IdeologyLibCons) %>%
  summarise(mean=mean(CitizenshipPEB_Total))

Descriptives Independent Behaviour by Cell

data.frame(df_passed) %>%
  group_by(Action, Source, IdeologyLibCons) %>%
  summarise(mean=mean(PersonalPEB_Total))

MANOVA for Pro-Environmental Behaviour

# Investigate Pro-Environmental Behaviour
manova_analysis<-manova(cbind(CitizenshipPEB_Total, PersonalPEB_Total) ~ Source*as.factor(IdeologyLibCons)*Action, data=df_passed)
summary(manova_analysis)

##                                           Df   Pillai approx F num Df
## Source                                     2 0.010591    0.751      4
## as.factor(IdeologyLibCons)                 1 0.311226   63.486      2
## Action                                     2 0.012336    0.875      4
## Source:as.factor(IdeologyLibCons)          2 0.013667    0.970      4
## Source:Action                              4 0.019710    0.702      8
## as.factor(IdeologyLibCons):Action          2 0.004469    0.316      4
## Source:as.factor(IdeologyLibCons):Action   4 0.053423    1.935      8
## Residuals                                282                         
##                                          den Df  Pr(>F)    
## Source                                      564 0.55782    
## as.factor(IdeologyLibCons)                  281 < 2e-16 ***
## Action                                      564 0.47852    
## Source:as.factor(IdeologyLibCons)           564 0.42329    
## Source:Action                               564 0.69023    
## as.factor(IdeologyLibCons):Action           564 0.86747    
## Source:as.factor(IdeologyLibCons):Action    564 0.05267 .  
## Residuals                                                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

ANOVA for Citizenship behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology (2) on Citizenship behaviours.

Citizenship_anova<-aov(CitizenshipPEB_Total ~ Source*as.factor(IdeologyLibCons)*Action, data=df_passed)

res<-papaja::apa_print(Citizenship_anova)
apa_table(res$table)

(#tab:unnamed-chunk-14) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	1.40	2	282	0.82	.247	.010
As factorIdeologyLibCons	116.66	1	282	0.82	< .001	.293
Action	0.88	2	282	0.82	.416	.006
Source \(\times\) As factorIdeologyLibCons	1.86	2	282	0.82	.158	.013
Source \(\times\) Action	0.57	4	282	0.82	.688	.008
As factorIdeologyLibCons \(\times\) Action	0.39	2	282	0.82	.680	.003
Source \(\times\) As factorIdeologyLibCons \(\times\) Action	1.31	4	282	0.82	.266	.018

ANOVA for Personal behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology (2) on Personal behaviours.

PersonalPEB_anova<-aov(PersonalPEB_Total ~ Source*as.factor(IdeologyLibCons)*Action, data=df_passed)

res<-papaja::apa_print(PersonalPEB_anova)
apa_table(res$table)

(#tab:unnamed-chunk-15) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	0.56	2	282	0.66	.572	.004
As factorIdeologyLibCons	23.27	1	282	0.66	< .001	.076
Action	0.10	2	282	0.66	.908	.001
Source \(\times\) As factorIdeologyLibCons	0.57	2	282	0.66	.567	.004
Source \(\times\) Action	0.30	4	282	0.66	.877	.004
As factorIdeologyLibCons \(\times\) Action	0.21	2	282	0.66	.810	.001
Source \(\times\) As factorIdeologyLibCons \(\times\) Action	1.79	4	282	0.66	.132	.025

Exploratory analysis using ALL participants and continuous ideology

This series of exploratory analysis uses continuous (rather than categorical ideology), as such participants who indicated that they are independent are included in the analysis. To begin, no manipulation checks are applied.

Investigate Petition Signing

Binomial logistic regression

Petition_analysis<-glm(Petition_RC ~ Source*Action, family="binomial", data=df)
tidy(Petition_analysis)

glance(Petition_analysis)

Pro-environmental behaviour

MANOVA for Pro-Environmental Behaviour

Because of the two measures of pro-envionmental behaviour are correlated. A MANOVA was conducted to investigate the effect of Source, Suggested Action, and Ideology on the two DVs. A single self-placement ideology measure was used in this analysis.

# Investigate Pro-Environmental Behaviour
manova_analysis<-manova(cbind(CitizenshipPEB_Total, PersonalPEB_Total) ~ Source*IdeologySingleItem*Action, data=df)
summary(manova_analysis)

##                                   Df   Pillai approx F num Df den Df
## Source                             2 0.013257    1.274      4    764
## IdeologySingleItem                 1 0.272141   71.227      2    381
## Action                             2 0.007824    0.750      4    764
## Source:IdeologySingleItem          2 0.004896    0.469      4    764
## Source:Action                      4 0.020676    0.998      8    764
## IdeologySingleItem:Action          2 0.005734    0.549      4    764
## Source:IdeologySingleItem:Action   4 0.032969    1.601      8    764
## Residuals                        382                                
##                                  Pr(>F)    
## Source                           0.2784    
## IdeologySingleItem               <2e-16 ***
## Action                           0.5580    
## Source:IdeologySingleItem        0.7587    
## Source:Action                    0.4364    
## IdeologySingleItem:Action        0.6997    
## Source:IdeologySingleItem:Action 0.1208    
## Residuals                                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

ANOVA for Citizenship behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology on Citizenship behaviours.

Citizenship_anova<-aov(CitizenshipPEB_Total ~ Source*IdeologySingleItem*Action, data=df)

res<-papaja::apa_print(Citizenship_anova)
apa_table(res$table)

(#tab:unnamed-chunk-18) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	1.51	2	382	0.87	.221	.008
IdeologySingleItem	139.61	1	382	0.87	< .001	.268
Action	1.27	2	382	0.87	.283	.007
Source \(\times\) IdeologySingleItem	0.90	2	382	0.87	.408	.005
Source \(\times\) Action	0.91	4	382	0.87	.460	.009
IdeologySingleItem \(\times\) Action	0.46	2	382	0.87	.632	.002
Source \(\times\) IdeologySingleItem \(\times\) Action	0.58	4	382	0.87	.674	.006

ANOVA for Personal behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology on Personal behaviours.

PersonalPEB_anova<-aov(PersonalPEB_Total ~ Source*IdeologySingleItem*Action, data=df)

res<-papaja::apa_print(PersonalPEB_anova)
apa_table(res$table)

(#tab:unnamed-chunk-19) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	1.57	2	382	0.65	.209	.008
IdeologySingleItem	40.06	1	382	0.65	< .001	.095
Action	0.14	2	382	0.65	.868	.001
Source \(\times\) IdeologySingleItem	0.52	2	382	0.65	.596	.003
Source \(\times\) Action	1.01	4	382	0.65	.403	.010
IdeologySingleItem \(\times\) Action	0.51	2	382	0.65	.602	.003
Source \(\times\) IdeologySingleItem \(\times\) Action	1.63	4	382	0.65	.167	.017

Exploratory analysis using continuous ideology and manipulation checks.

Finally, this series of exploratory analysis uses continuous (rather than categorical ideology), as such participants who indicated that they are independent are included in the analysis. In this series of analyses only participants who have passed both manipulation checks are included.

Investigate Petition Signing

Binomial logistic regression

Petition_analysis<-glm(Petition_RC ~ Source*Action, family="binomial", data=df_passed_explor)
tidy(Petition_analysis)

glance(Petition_analysis)

Pro-environmental behaviour

MANOVA for Pro-Environmental Behaviour

Because of the two measures of pro-envionmental behaviour are correlated. A MANOVA was conducted to investigate the effect of Source, Suggested Action, and Ideology on the two DVs. A single self-placement ideology measure was used in this analysis.

# Investigate Pro-Environmental Behaviour
manova_analysis<-manova(cbind(CitizenshipPEB_Total, PersonalPEB_Total) ~ Source*IdeologySingleItem*Action, data=df_passed_explor)
summary(manova_analysis)

##                                   Df  Pillai approx F num Df den Df
## Source                             2 0.01255    0.928      4    588
## IdeologySingleItem                 1 0.32540   70.666      2    293
## Action                             2 0.01106    0.817      4    588
## Source:IdeologySingleItem          2 0.01129    0.835      4    588
## Source:Action                      4 0.02554    0.951      8    588
## IdeologySingleItem:Action          2 0.00316    0.233      4    588
## Source:IdeologySingleItem:Action   4 0.05118    1.930      8    588
## Residuals                        294                               
##                                   Pr(>F)    
## Source                           0.44710    
## IdeologySingleItem               < 2e-16 ***
## Action                           0.51452    
## Source:IdeologySingleItem        0.50334    
## Source:Action                    0.47394    
## IdeologySingleItem:Action        0.92009    
## Source:IdeologySingleItem:Action 0.05322 .  
## Residuals                                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

ANOVA for Citizenship behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology on Citizenship behaviours.

Citizenship_anova<-aov(CitizenshipPEB_Total ~ Source*IdeologySingleItem*Action, data=df_passed_explor)

res<-papaja::apa_print(Citizenship_anova)
apa_table(res$table)

(#tab:unnamed-chunk-22) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	1.67	2	294	0.81	.190	.011
IdeologySingleItem	131.20	1	294	0.81	< .001	.309
Action	0.90	2	294	0.81	.409	.006
Source \(\times\) IdeologySingleItem	1.62	2	294	0.81	.200	.011
Source \(\times\) Action	0.83	4	294	0.81	.507	.011
IdeologySingleItem \(\times\) Action	0.31	2	294	0.81	.737	.002
Source \(\times\) IdeologySingleItem \(\times\) Action	0.76	4	294	0.81	.553	.010

ANOVA for Personal behaviours

An ANOVA was conducted to test the effect of Source (3) x Suggested Action (3) x Ideology on Personal behaviours.

PersonalPEB_anova<-aov(PersonalPEB_Total ~ Source*IdeologySingleItem*Action, data=df_passed_explor)

res<-papaja::apa_print(PersonalPEB_anova)
apa_table(res$table)

(#tab:unnamed-chunk-23) **

Effect	\(F\)	\(\mathit{df}_1\)	\(\mathit{df}_2\)	\(\mathit{MSE}\)	\(p\)	\(\hat{\eta}^2_G\)
Source	0.47	2	294	0.65	.625	.003
IdeologySingleItem	28.25	1	294	0.65	< .001	.088
Action	0.01	2	294	0.65	.992	.000
Source \(\times\) IdeologySingleItem	0.53	2	294	0.65	.591	.004
Source \(\times\) Action	0.45	4	294	0.65	.776	.006
IdeologySingleItem \(\times\) Action	0.03	2	294	0.65	.972	.000
Source \(\times\) IdeologySingleItem \(\times\) Action	1.78	4	294	0.65	.132	.024

US Data Analysis

All liberal and conservative participants

Investigate Petition Signing

Frequency of signing behaviour by group

Binomial logistic regression

Pro-environmental behaviour

Descriptives Citizenship Behaviour by Cell

Descriptives Independent Behaviour by Cell

MANOVA for Pro-Environmental Behaviour

ANOVA for Citizenship behaviours

ANOVA for Personal behaviours

Dataset that passed all manipulation checks

Investigate Petition Signing

Frequency of signing behaviour by group

Binomial logistic regression

Pro-environmental behaviour

Descriptives Citizenship Behaviour by Cell

Descriptives Independent Behaviour by Cell

MANOVA for Pro-Environmental Behaviour

ANOVA for Citizenship behaviours

ANOVA for Personal behaviours

Exploratory analysis using ALL participants and continuous ideology

Investigate Petition Signing

Binomial logistic regression

Pro-environmental behaviour

MANOVA for Pro-Environmental Behaviour

ANOVA for Citizenship behaviours

ANOVA for Personal behaviours

Exploratory analysis using continuous ideology and manipulation checks.

Investigate Petition Signing

Binomial logistic regression

Pro-environmental behaviour

MANOVA for Pro-Environmental Behaviour

ANOVA for Citizenship behaviours

ANOVA for Personal behaviours