library(tidyverse)
library(Rmisc)
library(psych)
library(emmeans)
library(afex)

experimentdata <- read_csv("Psy_120L Data_Firoz3.csv")

experimentdata$Prime <- case_when(experimentdata$Rich_prime_write == 0 ~ "Rich",
                                  experimentdata$Poor_prime_write == 0 ~ "Poor")



#Descriptive Statistics (frequencies, means, etc.)

table(experimentdata$Gender) #16 Male, 46 Female

table(experimentdata$Gender)/length(experimentdata$Gender) #26% Male, 74% Female


# 2x2 ANOVA on IV1 x Moderator on DV1
a1 <- aov_ez(experimentdata,
             id = "ID",
             dv = "AttractionScore",
             between = c("Gender", "Prime"))

a1

# 2x2 ANOVA on IV1 x Moderator on DV2
a2 <- aov_ez(experimentdata,
             id = "ID",
             dv = "LikabilityScore",
             between = c("Gender", "Prime"))

a2

# 2x2 ANOVA on IV2 x Moderator on DV1
a3 <- aov_ez(experimentdata,
             id = "ID",
             dv = "AttractionScore",
             between = c("Gender", "FaceCondition"))

a3

# 2x2 ANOVA on IV2 x Moderator on DV2
a4 <- aov_ez(experimentdata,
             id = "ID",
             dv = "LikabilityScore",
             between = c("Gender", "FaceCondition"))

a4

# 2x2 ANOVA on IV1 x IV2 on DV1
a5 <- aov_ez(experimentdata,
             id = "ID",
             dv = "AttractionScore",
             between = c("Prime", "FaceCondition"))

a5

# 2x2 ANOVA on IV1 x IV 2 on DV2
a6 <- aov_ez(experimentdata,
             id = "ID",
             dv = "LikabilityScore",
             between = c("Prime", "FaceCondition"))

a6

#Bar Plot
newdataset <- experimentdata %>%
  dplyr::group_by(Prime, FaceCondition) %>%
  dplyr::summarize(mean_attraction = CI(AttractionScore) ["mean"],
                   sem_attr = sd(AttractionScore)/sqrt(length(AttractionScore)-1))