latest analysis code

study_data/full_Study/trustFullAnalysis_6.12.2023.Rmd

@@ -16,6 +16,7 @@ library(patchwork)
 library(rstatix)
 library(effectsize)
 library(GPArotation)
+library(MASS)
 # environment to include the ss_psych450_rws3 platform
 load("ss_psych450_rws3")
 ```
@@ -93,11 +94,63 @@ results %>%
 
 
 
-ggsave(paste("complexity_dataType_interaction.pdf", sep=""))
+#ggsave(paste("complexity_dataType_interaction.pdf", sep=""))
 
 ```
 
 
+```{r}
+
+MinMeanSEMMax <- function(x) {
+  v <- c(min(x), mean(x) - sd(x)/sqrt(length(x)), mean(x), mean(x) + sd(x)/sqrt(length(x)), max(x))
+  names(v) <- c("ymin", "lower", "middle", "upper", "ymax")
+  v
+}
+
+results %>%
+  # group_by(complexity, isCovidData) %>%
+  ggplot(aes( x = vis.trust_6, y = 0, cex=1.5, colour = chartType)) +
+  scale_color_manual(values = c("purple", "orange")) +
+  ylim(-0.5, 0.5) +
+  geom_jitter(data = results, width = 0.3, height = 0.2, color = "light gray", alpha = 0.5) +
+  #stat_summary(fun.data=MinMeanSEMMax, geom="boxplot", colour="red") +
+
+  geom_boxplot(lwd = 1, fatten = NULL, width = 0.25, alpha = 0.5) +
+
+  geom_segment(data = results %>% 
+                group_by(complexity, chartType) %>%
+                summarize(n = n(), 
+                           mean = mean(vis.trust_6),
+            se = sd(vis.trust_6)/sqrt(n)), 
+              aes(x = mean, xend = mean, y = -.25, yend = .25,  colour = chartType), size = 1) +
+        # stat_summary(fun.data = "mean_cl_boot", colour = "red", size = 0.5, position = position_nudge(x=0.25, y=0), alpha=0.5) +
+
+  geom_text( data = results %>% 
+                group_by(complexity, chartType) %>%
+                summarize(n = n(), 
+                           mean = round(mean(vis.trust_6),digits=2),
+            se = round(sd(data.trust_6)/sqrt(n),digits=2),
+                          vis.trust_6 = mean(vis.trust_6)),
+            # aes(label = paste(mean, "[",mean-se,",",mean+se,"]"), x = 6.2, y = 0.43, fontface = 3), size=3, colour = "black")+
+              aes(label = paste(mean), x = mean, y = .35, fontface = 3), size=4, colour = "black")+
+
+  facet_grid(complexity ~ chartType) +
+  xlab("Trust in Visualization") +
+  theme_minimal() + 
+  theme(panel.spacing = unit(2, "lines"),
+        legend.position = "none",
+        axis.text.y = element_blank(),
+        axis.title.y = element_blank(),
+        axis.ticks.y = element_blank())
+
+
+
+ggsave(paste("complexity_chartType_interaction.pdf", sep=""))
+
+```
+
+
+
 ```{r}
 results %>%
   group_by(complexity, isCovidData) %>%
@@ -148,7 +201,7 @@ results %>%
         axis.title.y = element_blank(),
         axis.ticks.y = element_blank())
 
-ggsave(paste("complexity_interaction.pdf", sep=""))
+#ggsave(paste("complexity_interaction.pdf", sep=""))
 
 ```
 
@@ -164,9 +217,8 @@ results %>%
 ```
 
 ```{r}
-model <- lm(formula = vis.trust_6 ~ complexity  * chartType + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
-            data = results%>%filter(isCovidData == 1)
- filter(isCovidData ==1 ))
+model <- lm(formula = vis.trust_6 ~ complexity  * as.factor(isCovidData) * chartType + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
+            data = results)
 anova(model)
 ```
 ```{r}
@@ -196,15 +248,32 @@ anova(model)
 
 ```
 ```{r}
-# can change the predictor to bar.vis
-model<- manova(cbind(vis.trust_6, 
-                     vis.trust_5, 
-                     vis.trust_4, 
-                     vis.trust_3, 
-                     vis.trust_2, 
-                     vis.trust_1) ~ complexity  * chartType  + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
-               data = results %>%filter(isCovidData == 1))
+
+model<- manova( cbind(vis.trust_6,vis.trust_1,vis.trust_2,vis.trust_3,vis.trust_4,vis.trust_5,affect.science_1,affect.clarity_1,affect.aesthetic_1) ~ complexity  * as.factor(isCovidData) * chartType  + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
+               data = results)
+
+summary(model)
+eta_squared(model)
+
+summary.aov(model)
+
+
+
+```
+
+
+```{r}
+
+model<- manova( cbind(data.trust_6,data.trust_1,data.trust_2,data.trust_3,data.trust_4,data.trust_5) ~ complexity  * as.factor(isCovidData) * chartType  + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
+               data = results)
+
+anova(model)
+eta_squared(model)
+
 summary.aov(model)
+
+
+
 ```
 
 ```{r}
@@ -479,7 +548,7 @@ results %>%
 How does performance on VLAT questions predict trust?
 
 ```{r}
-model <- lm(formula = vis.trust_6 ~  assigned_vlat *
+model <- lm(formula = vis.trust_6 ~  assigned_vlat +
               Age + Gender + State_1 + Education + Parents_education + Language + 
               Ethnicity + Income + Religion + trust.in.science_7 + 
               need_for_cognition + interpersonal.trust_1,

study_data/replicationStudy/trustFullAnalysis_7.24.2023.Rmd

@@ -163,19 +163,33 @@ results %>%
 ```
 
 ```{r}
-model <- lm(formula = vis.trust_6 ~ complexity  * chartType + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
+model <- lm(formula = vis.trust_5 ~ complexity  * chartType + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
             data = results)
 anova(model)
 ```
 ```{r}
 model <- lm(formula = vis.trust_6 ~ complexity * chartType + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
-            data = results%>% filter(complexity !='moderatex'))
+            data = results)
 anova(model)
 
 
 ```
 
 
+```{r}
+
+model<- manova( cbind(vis.trust_6,vis.trust_1,vis.trust_2,vis.trust_3,vis.trust_4,vis.trust_5,affect.science_1,affect.clarity_1,affect.aesthetic_1) ~ complexity  * chartType  + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
+               data = results)
+
+anova(model)
+eta_squared(model)
+
+summary.aov(model)
+
+
+
+```
+
 ```{r}
 model <- lm(formula = vis.trust_6 ~ complexity  + chartType + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
             data = results)
@@ -186,6 +200,21 @@ anova(model)
 
 
 Linear Regression Model for trust in vis as a function of 
+
+```{r}
+# can change the predictor to bar.vis
+model<- manova(cbind(vis.trust_6,
+                    affect.science_1,
+                    affect.clarity_1,
+                    affect.aesthetic_1,
+                     vis.trust_3, 
+                     vis.trust_2, 
+                     vis.trust_1) ~ complexity* chartType  + Age + Gender + State_1 + Education + Parents_education + Language + Ethnicity + Income + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
+               data = results)
+summary(model)
+```
+
+
 ```{r}
 model <- lm(formula = vis.trust_6 ~ complexity *chartType  + Age + Gender + State_1 + Income + Education + Parents_education + Language + Ethnicity  + Religion + trust.in.science_7 + need_for_cognition + interpersonal.trust_1 ,
             data = results)