Rscript.R

In michaelkardas/behavioralwrappers: Wrappers and other functions for the behavioral sciences

################################ SETUP #####################################
# Load the devtools package, or install devtools if this package is not already installed
if(!require(devtools)){install.packages("devtools"); library(devtools)}

# Install and load the behavioralwrappers package
install_github("michaelkardas/behavioralwrappers")
library(behavioralwrappers)

# Load the sample data set
bdata <- behavioralwrappers::bdata

################################ SAMPLE CODE #####################################
### Functions For Data Cleaning ###
# Splitting bdata Frames
wrap.split(df = bdata, iv1 = IV1)
wrap.split(df = bdata, iv1 = IV1, iv2 = IV2)

# Merging Columns
wrap.merge(df = bdata)

# Generating Columns
wrap.generate(df = bdata, string1 = "T1", string2 = "T2", operation = "difference")
wrap.generate(df = bdata, string1 = "T1", string2 = "T2", operation = "sum")
wrap.generate(df = bdata, string1 = "T1", string2 = "T2", operation = "mean")

### Functions For Data Analysis ###
# Descriptive Statistics
wrap.desc(dv1 = bdata$DV1)
wrap.desc(dv1 = bdata$DV1, iv1 = bdata$IV2)

# T Tests (One Sample)
wrap.t.one(dv1 = bdata$DV1, mu = 5)

# T Tests (Independent Samples)
wrap.t.ind(dv1 = bdata$DV1, iv1 = bdata$IV1)

# T Tests (Paired Samples)
wrap.t.pair(dv1 = bdata$DV1, dv2 = bdata$DV2)

# ANOVA (Main Effects & Interaction Effects)
wrap.anova.main(dv1 = bdata[c(4, 5)])
wrap.anova.main(dv1 = bdata$DV1, iv1 = bdata$IV1, iv2 = bdata$IV2)
wrap.anova.main(dv1 = bdata[c(4, 5)], iv1 = bdata$IV1, iv2 = bdata$IV2)

# ANOVA (Planned Contrasts)
wrap.anova.planned(dv1 = bdata$DV1, iv1 = bdata$IV2, levels = c("PhotoA", "PhotoB"), weights = c(-1, 1))
wrap.anova.planned(dv1 = bdata$DV1, iv1 = bdata$IV2, levels = c("PhotoA", "PhotoB", "PhotoC"), weights = c(-1, 0.5, 0.5))

# ANOVA (Simple Main Effects)
wrap.anova.simple(dv1 = bdata$DV1, iv1 = bdata$IV1, iv2 = bdata$IV2)

# Linear Regression
wrap.lm(model = bdata$DV3 ~ bdata$DV1 * bdata$DV2, standardized = FALSE)
wrap.lm(model = bdata$DV3 ~ bdata$DV1 * bdata$DV2, standardized = TRUE)

# Correlation Tests
wrap.cor(dv1 = bdata$DV1, dv2 = bdata$DV2)

# Chi-Square Tests
wrap.chi(dv1 = bdata$DV9)
wrap.chi(dv1 = bdata$DV9, iv1 = bdata$IV2)

### Functions For Data Visualization ###
# Bar Plots
wrap.bar(dv1 = bdata[c(4,6)])
wrap.bar(dv1 = bdata$DV1, iv1 = bdata$IV1, iv2 = bdata$IV2)
wrap.bar(dv1 = bdata[c(4,6)], iv1 = bdata$IV1, iv2 = bdata$IV3)

# Line Plots
wrap.line(dv1 = bdata[c(4:6)], iv1 = bdata$IV1, iv2 = bdata$IV2)

# Histograms
wrap.hist(dv1 = bdata$DV8, likert = FALSE)
wrap.hist(dv1 = bdata$DV1, likert = TRUE)