Google Presentation

Author

Sierra Semko Krouse

Published

January 30, 2025

Libraries

library(psych)
library(tidyverse)
library(ggpubr)

ggplot Theme

library(showtext)
font_add_google(name="Poppins", family="Poppins")
font_add_google(name="DM Serif Text", family="DM Serif Text")

theme_ssk <- function() {
    ggplot2::theme_bw() +
    ggplot2::theme(
    axis.text = element_text(colour = "#0c4846",  family = "Poppins", size = 12),
    axis.title = element_text(colour = "#0c4846", family = "DM Serif Text", size = 14),
    legend.title = element_text(colour = "#0c4846", family = "Poppins", size = 13),
    legend.text = element_text(colour = "#0c4846", family = "Poppins", size = 12),
    plot.title = element_text(colour = "#0c4846", family = "Poppins", size = 13, face = "bold"),
    plot.subtitle = element_text(colour = "#0c4846", family = "Poppins", size = 13, face = "italic"),
    strip.text = element_text(colour = "#0c4846", family = "Poppins", size = 13)) +
    ggplot2::theme(panel.background = element_rect(fill = "#fffbef", color = "#0e0d0d"),
                   plot.background = element_rect(fill = "#fffbef"))
}

stat_sum_df <- function(fun, geom="crossbar", ...) {
  stat_summary(fun.data=fun, colour="black", geom=geom, width=.5,  ...)
}

Data

data <- read.csv("clean_workplace_data_20240910.csv")

Relationships

summary(lm(relationships ~ Condition + wave, data))

Call:
lm(formula = relationships ~ Condition + wave, data = data)

Residuals:
    Min      1Q  Median      3Q     Max 
-4.2672 -1.1105  0.3787  1.3787  2.3787 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)          4.1843     0.4671   8.958 4.87e-15 ***
ConditionTreatment   0.6459     0.3064   2.108   0.0371 *  
wave                 0.4370     0.3120   1.401   0.1639    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.688 on 121 degrees of freedom
  (91 observations deleted due to missingness)
Multiple R-squared:  0.05737,   Adjusted R-squared:  0.04179 
F-statistic: 3.682 on 2 and 121 DF,  p-value: 0.02804
relation_plot <- data %>% 
  filter(!is.na(Condition)) %>% 
  ggplot(aes(Condition, relationships, fill=Condition)) + 
  geom_bar(stat="summary", fun.y="mean", position="dodge") +
  geom_jitter(color = "#301934", alpha = 0.5) +
  stat_summary(fun.data = mean_se, geom = "errorbar", position= position_dodge(.9), conf.int = .68, width = 0.5, color = "#0c4846") +
  expand_limits(y = c(1,7)) +
  scale_y_continuous(breaks = c(1:7)) +
  labs(x = "Intervention Condition",
       y = "Value of Relationships") +
  scale_fill_manual(values = c("#d3c3fd", "#b390f7")) +
  theme_ssk() +
  theme(legend.position = "none") 

relation_plot

Complexity

summary(lm(complexity ~ Condition + wave, data))

Call:
lm(formula = complexity ~ Condition + wave, data = data)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.5192 -0.5192  0.2041  0.4808  0.5149 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)         4.55342    0.15982  28.491  < 2e-16 ***
ConditionTreatment  0.27662    0.10485   2.638  0.00943 ** 
wave               -0.03416    0.10674  -0.320  0.74950    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.5775 on 121 degrees of freedom
  (91 observations deleted due to missingness)
Multiple R-squared:  0.05441,   Adjusted R-squared:  0.03878 
F-statistic: 3.481 on 2 and 121 DF,  p-value: 0.03388
complex_plot <- data %>% 
  filter(!is.na(Condition)) %>% 
  ggplot(aes(Condition, complexity, fill=Condition)) + 
  geom_bar(stat="summary", fun.y="mean", position="dodge") +
  geom_jitter(color = "#004080", alpha = 0.5) +
  stat_summary(fun.data = mean_se, geom = "errorbar", position= position_dodge(.9), conf.int = .68, width = 0.5, color = "#0c4846") +
  expand_limits(y = c(1,5)) +
  scale_y_continuous(breaks = c(1:5)) +
  labs(x = "Intervention Condition",
       y = "Complexity of Coworkers") +
  scale_fill_manual(values = c("#c7e6f8", "#67b5ff")) +
  theme_ssk() +
  theme(legend.position = "none") 

complex_plot

Perspective-Taking

summary(lm(pt_s1 ~ Condition + wave, data))

Call:
lm(formula = pt_s1 ~ Condition + wave, data = data)

Residuals:
    Min      1Q  Median      3Q     Max 
-2.3983 -0.3983 -0.1082  0.6017  0.8918 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)         4.01887    0.22230  18.079   <2e-16 ***
ConditionTreatment  0.29005    0.14584   1.989    0.049 *  
wave                0.08935    0.14847   0.602    0.548    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.8032 on 121 degrees of freedom
  (91 observations deleted due to missingness)
Multiple R-squared:  0.0377,    Adjusted R-squared:  0.0218 
F-statistic:  2.37 on 2 and 121 DF,  p-value: 0.09778
pt_s1_plot <- data %>% 
  filter(!is.na(Condition)) %>% 
  ggplot(aes(Condition, pt_s1, fill=Condition)) + 
  geom_bar(stat="summary", fun.y="mean", position="dodge") +
  geom_jitter(color = "#BA8E23", alpha = 0.5) +
  stat_summary(fun.data = mean_se, geom = "errorbar", position= position_dodge(.9), conf.int = .68, width = 0.5, color = "#0c4846") +
  expand_limits(y = c(1,5)) +
  scale_y_continuous(breaks = c(1:5)) +
  labs(x = "Intervention Condition",
       y = "Perspective-Taking",
       title = "Session 1") +
  scale_fill_manual(values = c("#ffeec1", "#FFC931")) +
  theme_ssk() +
  theme(legend.position = "none") 

pt_s1_plot

summary(lm(pt_s2 ~ Condition + wave, data))

Call:
lm(formula = pt_s2 ~ Condition + wave, data = data)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.5846 -0.3948 -0.1454  0.4154  0.8546 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)          4.2648     0.2316  18.412  < 2e-16 ***
ConditionTreatment   0.4392     0.1529   2.873  0.00561 ** 
wave                -0.0597     0.1518  -0.393  0.69544    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.5856 on 60 degrees of freedom
  (152 observations deleted due to missingness)
Multiple R-squared:  0.1217,    Adjusted R-squared:  0.09246 
F-statistic: 4.158 on 2 and 60 DF,  p-value: 0.02036
pt_s2_plot <- data %>% 
  filter(!is.na(Condition)) %>% 
  ggplot(aes(Condition, pt_s2, fill=Condition)) + 
  geom_bar(stat="summary", fun.y="mean", position="dodge") +
  geom_jitter(color = "#cb416b", alpha = 0.5) +
  stat_summary(fun.data = mean_se, geom = "errorbar", position= position_dodge(.9), conf.int = .68, width = 0.5, color = "#0c4846") +
  expand_limits(y = c(1,5)) +
  scale_y_continuous(breaks = c(1:5)) +
  labs(x = "Intervention Condition",
       y = "Perspective-Taking",
       title = "Session 2") +
  scale_fill_manual(values = c("#facdcd", "#f48382")) +
  theme_ssk() +
  theme(legend.position = "none") 

pt_s2_plot