Load packages
Load functions
Load data
Data processing
Descriptive data
Participants
| Characteristic |
N = 741 |
| Age |
41 (33, 53) |
| Ethnicity.simplified |
|
| Â Â Â Â Black |
369 (50%) |
| Â Â Â Â White |
372 (50%) |
| Country.of.residence |
|
| Â Â Â Â United States |
741 (100%) |
| Highest.education.level.completed |
|
| Â Â Â Â Doctorate degree (PhD/other) |
22 (3.0%) |
| Â Â Â Â Graduate degree (MA/MSc/MPhil/other) |
108 (15%) |
| Â Â Â Â High school diploma/A-levels |
175 (24%) |
| Â Â Â Â Secondary education (e.g. GED/GCSE) |
19 (2.6%) |
| Â Â Â Â Technical/community college |
115 (16%) |
| Â Â Â Â Undergraduate degree (BA/BSc/other) |
302 (41%) |
| Employment.status |
|
| Â Â Â Â DATA_EXPIRED |
156 (21%) |
| Â Â Â Â Due to start a new job within the next month |
4 (0.5%) |
| Â Â Â Â Full-Time |
329 (44%) |
| Â Â Â Â Not in paid work (e.g. homemaker', 'retired or disabled) |
72 (9.7%) |
| Â Â Â Â Other |
14 (1.9%) |
| Â Â Â Â Part-Time |
98 (13%) |
| Â Â Â Â Unemployed (and job seeking) |
68 (9.2%) |
Table over most important variables sorted on condition
##
## Descriptive statistics by group
## group: Control
## vars n mean sd min max range se
## empathic_reactions 1 159 5.57 1.46 1.3 7.0 5.7 0.12
## empathic_drivers 2 159 2.88 1.08 0.7 4.7 4.0 0.09
## empathic_beliefs 3 159 4.83 1.31 1.0 7.0 6.0 0.10
## donation 4 159 40.86 40.09 0.0 100.0 100.0 3.18
## rt_intervention 5 159 35.93 45.82 4.3 377.2 372.9 3.63
## rt_story 6 159 108.31 118.83 3.6 1039.8 1036.2 9.42
## ------------------------------------------------------------
## group: Limited
## vars n mean sd min max range se
## empathic_reactions 1 148 5.22 1.42 1.0 7.0 6.0 0.12
## empathic_drivers 2 148 2.79 1.03 0.7 4.7 4.0 0.08
## empathic_beliefs 3 148 4.73 1.34 1.0 7.0 6.0 0.11
## donation 4 148 40.28 38.32 0.0 100.0 100.0 3.15
## rt_intervention 5 148 46.27 58.89 3.8 439.0 435.2 4.84
## rt_story 6 148 99.14 85.93 2.7 544.1 541.4 7.06
## ------------------------------------------------------------
## group: Malleable
## vars n mean sd min max range se
## empathic_reactions 1 143 5.39 1.41 1.0 7.0 6.0 0.12
## empathic_drivers 2 143 2.90 1.10 0.7 4.7 4.0 0.09
## empathic_beliefs 3 143 4.95 1.35 1.7 7.0 5.3 0.11
## donation 4 143 40.49 38.37 0.0 100.0 100.0 3.21
## rt_intervention 5 143 59.92 90.80 5.1 911.9 906.8 7.59
## rt_story 6 143 87.83 66.08 1.9 493.2 491.3 5.53
## ------------------------------------------------------------
## group: Normative
## vars n mean sd min max range se
## empathic_reactions 1 149 5.45 1.34 1.0 7.0 6.0 0.11
## empathic_drivers 2 149 3.01 0.99 0.7 4.7 4.0 0.08
## empathic_beliefs 3 149 4.89 1.37 1.0 7.0 6.0 0.11
## donation 4 149 45.69 39.08 0.0 100.0 100.0 3.20
## rt_intervention 5 149 67.15 91.96 3.2 631.3 628.1 7.53
## rt_story 6 149 92.65 72.40 2.0 595.9 593.9 5.93
## ------------------------------------------------------------
## group: Unlimited
## vars n mean sd min max range se
## empathic_reactions 1 142 5.52 1.45 1.0 7.0 6.0 0.12
## empathic_drivers 2 142 2.91 1.08 0.7 4.7 4.0 0.09
## empathic_beliefs 3 142 5.11 1.26 2.0 7.0 5.0 0.11
## donation 4 142 40.18 37.65 0.0 100.0 100.0 3.16
## rt_intervention 5 142 43.34 44.18 1.6 377.3 375.7 3.71
## rt_story 6 142 100.02 148.58 1.6 1666.7 1665.1 12.47
Scatterplots for Empathy measures & Donation
Scatterplots for Empathic reactions & Donation
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
## `geom_smooth()` using formula = 'y ~ x'
Scatterplots for Empathic drivers & Donation
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
## `geom_smooth()` using formula = 'y ~ x'
Scatterplots for Empathic beliefs & Donation
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
## `geom_smooth()` using formula = 'y ~ x'
Correlation matrix for Empathy measures, Donation & Reaction
time for Outgroup
Correlation matrix for Control
Correlation matrix for Limited
Correlation matrix for Unlimitied
Correlation matrix for Malleable
Correlation matrix for Normative
Cronbach’s Alpha for Empathy measures
Cronbach’s Alpha for Empathic reactions
##
## Cronbach's alpha for the 'empathic_reactions_df' data-set
##
## Items: 3
## Sample units: 741
## alpha: 0.932
Cronbach’s Alpha for Empathic drivers
##
## Cronbach's alpha for the 'empathic_drivers_df' data-set
##
## Items: 3
## Sample units: 741
## alpha: 0.812
Cronbach’s Alpha for Empathic beliefs
##
## Cronbach's alpha for the 'empathic_beliefs_df' data-set
##
## Items: 3
## Sample units: 741
## alpha: 0.524
H1a - For Empathic reactions we hypothesize the following
directional relationships: Malleable == Unlimited > Social Norm >
Limited == Control.
BRMS model for Empathic reactions
## Family: gaussian
## Links: mu = identity; sigma = identity
## Formula: empathic_reactions_z ~ 0 + condition
## Data: outgroup (Number of observations: 741)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## conditionControl 0.10 0.08 -0.06 0.26 1.00 5514 3620
## conditionLimited -0.15 0.08 -0.31 0.01 1.00 5117 3085
## conditionMalleable -0.03 0.09 -0.20 0.13 1.00 6112 2982
## conditionNormative 0.01 0.08 -0.15 0.17 1.00 5344 2984
## conditionUnlimited 0.06 0.08 -0.10 0.22 1.00 5419 3175
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 1.00 0.03 0.95 1.05 1.00 5242 3205
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
## Warning: Dropping 'draws_df' class as required metadata was removed.
## b_conditionControl b_conditionLimited b_conditionMalleable
## 2.5% -0.05633176 -0.3112300 -0.1959837
## 97.5% 0.25645408 0.0134272 0.1343403
## b_conditionNormative b_conditionUnlimited
## 2.5% -0.1503170 -0.1017799
## 97.5% 0.1736095 0.2193096
Mean difference difference Unlimited vs Control
## [1] -0.04080836
Quantile interval
## 2.5% 97.5%
## -0.2657870 0.1744936
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Control and Unlimitied for Empathic
reactions
Mean difference for Malleable vs Control
## [1] -0.1306114
Quantile interval
## 2.5% 97.5%
## -0.35906435 0.09170377
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Malleable and Unlimitied for Empathic
reactions
Mean difference for Normative vs Control
## [1] -0.1306114
Quantile interval
## 2.5% 97.5%
## -0.3116156 0.1273544
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Normative and Unlimitied for Empathic
reactions
H1b - For Empathic drivers we hypothesize the following directional
relationships: Malleable == Unlimited > Social Norm > Limited ==
Control.
BRMS model empathic drivers
## Family: gaussian
## Links: mu = identity; sigma = identity
## Formula: empathic_reactions_z ~ 0 + condition
## Data: outgroup (Number of observations: 741)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## conditionControl 0.10 0.08 -0.06 0.26 1.00 5514 3620
## conditionLimited -0.15 0.08 -0.31 0.01 1.00 5117 3085
## conditionMalleable -0.03 0.09 -0.20 0.13 1.00 6112 2982
## conditionNormative 0.01 0.08 -0.15 0.17 1.00 5344 2984
## conditionUnlimited 0.06 0.08 -0.10 0.22 1.00 5419 3175
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 1.00 0.03 0.95 1.05 1.00 5242 3205
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
## Warning: Dropping 'draws_df' class as required metadata was removed.
## b_conditionControl b_conditionLimited b_conditionMalleable
## 2.5% -0.1702859 -0.26659882 -0.1605880
## 97.5% 0.1407791 0.05476715 0.1671147
## b_conditionNormative b_conditionUnlimited
## 2.5% -0.05879902 -0.1469587
## 97.5% 0.26525970 0.1753830
Mean difference for Unlimited vs Control
## [1] 0.02863183
Quantile interval
## 2.5% 97.5%
## -0.1986312 0.2564561
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Control and Unlimitied for Empathic
drivers
Mean difference for Malleable vs Control
## [1] 0.01720522
Quantile interval
## 2.5% 97.5%
## -0.2068777 0.2415954
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Malleable and Unlimitied for Empathic
drivers
Mean difference for Normative vs Control
## [1] 0.1181297
Quantile interval
## 2.5% 97.5%
## -0.1093017 0.3505581
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Normative and Unlimitied for Empathic
drivers
H1c - For Donated money we hypothesize the following directional
relationships: Malleable == Unlimited > Social Norm > Limited ==
Control.
BRMS model empathic drivers
## Family: gaussian
## Links: mu = identity; sigma = identity
## Formula: donation_z ~ 0 + condition
## Data: outgroup (Number of observations: 741)
## Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
## total post-warmup draws = 4000
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## conditionControl -0.01 0.08 -0.17 0.14 1.00 5571 2979
## conditionLimited -0.03 0.08 -0.19 0.13 1.00 5159 2871
## conditionMalleable -0.03 0.08 -0.19 0.14 1.00 5463 2672
## conditionNormative 0.11 0.08 -0.05 0.28 1.00 5427 3302
## conditionUnlimited -0.03 0.08 -0.20 0.13 1.00 5833 3185
##
## Family Specific Parameters:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sigma 1.00 0.03 0.95 1.05 1.00 6963 3278
##
## Draws were sampled using sample(hmc). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
## Warning: Dropping 'draws_df' class as required metadata was removed.
## b_conditionControl b_conditionLimited b_conditionMalleable
## 2.5% -0.1688229 -0.1938809 -0.1880629
## 97.5% 0.1423076 0.1282579 0.1353247
## b_conditionNormative b_conditionUnlimited
## 2.5% -0.04986123 -0.1968648
## 97.5% 0.27561948 0.1319767
Mean difference for Unlimited vs Control
## [1] -0.01859229
Quantile interval
## 2.5% 97.5%
## -0.2371990 0.2159797
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Control and Unlimitied for Donation
Mean difference for Malleable vs Control
## [1] -0.01199492
Quantile interval
## 2.5% 97.5%
## -0.2417528 0.2144014
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Malleable and Unlimitied for Donation
Mean difference for Normative vs Control
## [1] 0.1228901
Quantile interval
## 2.5% 97.5%
## -0.1005301 0.3581822
The HDI does not exclude zero, so we conclude no hypothesized
difference between condition Normative and Unlimitied for Donation