Purpose Study “Next Stage Purpose” Results

Sense of Identity (taken from APSI; Jaffe, 1998)

setwd("/Users/levibrackman/Desktop/Adult_study")
data_pre <- read.csv("pre.csv")
data_post <- read.csv("post.csv")

table(data_pre$GROUP, dnn = "group")

## group
##  0  1 
## 35 32

data <- merge(data_pre, data_post, by = "ID", all = TRUE)
library(psych)
library(lattice)
# T1 APSI
items <- grep("APSI[0-8]*.x", names(data), value = TRUE)
scaleKey <- c(1, 1, 1, 1, 1, -1, 1, 1)
data$meanT1APSI <- scoreItems(scaleKey, items = data[, items], delete = FALSE)$score
# T2 APSI
items <- grep("APSI[0-8]*.y", names(data), value = TRUE)
scaleKey <- c(1, 1, 1, 1, 1, -1, 1, 1)
data$meanT2APSI <- scoreItems(scaleKey, items = data[, items], delete = FALSE)$score
# All APSI
data$T1APSI <- apply(data[, c("APSI1.x", "APSI2.x", "APSI3.x", "APSI4.x", "APSI5.x", 
    "APSI6.x", "APSI7.x", "APSI8.x", "meanT1APSI")], 1, mean, na.rm = TRUE)
data$T2APSI <- apply(data[, c("APSI1.y", "APSI2.y", "APSI3.y", "APSI4.y", "APSI5.y", 
    "APSI6.y", "APSI7.y", "APSI8.y", "meanT2APSI")], 1, mean, na.rm = TRUE)

plot(data$T1APSI, data$T2APSI, ylab = "Pre", xlab = "Post", main = "Identity")

# pre test plots
bwplot(GROUP.x ~ T1APSI, ylab = "GROUP", xlab = "APSI", main = "Pre test", data = data)

# post test plots
bwplot(GROUP.x ~ T2APSI, ylab = "Group", xlab = "APSI", main = "Post test", 
    data = data)

# Pre test
t.test(T1APSI ~ GROUP.x, data = data)

## 
##  Welch Two Sample t-test
## 
## data:  T1APSI by GROUP.x
## t = 1.301, df = 57.29, p-value = 0.1986
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.07827  0.36850
## sample estimates:
## mean in group 0 mean in group 1 
##           3.929           3.784

t.test(T2APSI ~ GROUP.x, data = data)

## 
##  Welch Two Sample t-test
## 
## data:  T2APSI by GROUP.x
## t = -1.4, df = 59.67, p-value = 0.1668
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.28662  0.05066
## sample estimates:
## mean in group 0 mean in group 1 
##           4.096           4.214

# Ancova, Model for APSI
APSI_ANCOVA <- lm(T2APSI ~ as.factor(GROUP.x) + T1APSI, data = data)
# check assumptions visually
plot(APSI_ANCOVA)

# see results
summary(APSI_ANCOVA)

## 
## Call:
## lm(formula = T2APSI ~ as.factor(GROUP.x) + T1APSI, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.9368 -0.2054  0.0387  0.2094  0.6555 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)           2.8890     0.3557    8.12    2e-11 ***
## as.factor(GROUP.x)1   0.1626     0.0805    2.02    0.048 *  
## T1APSI                0.3073     0.0894    3.44    0.001 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.325 on 64 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.18,   Adjusted R-squared:  0.154 
## F-statistic: 7.01 on 2 and 64 DF,  p-value: 0.00177