Compute effect size and VPC for PANGEA from quasif

PANGEA_quasif.R

## Load Raaijmakers 1999 data set from languageR
library(languageR)
data(quasif)

summary(quasif)

## Compute the variance of random effect
library(lme4)

## Parameters for the general effect size

cells_number <- nlevels(quasif$SOA)
contrast_means <- with(data = quasif, tapply(RT, SOA, mean))
contrast_code <- c(1, -1)
b_adj <- max(contrast_code)
a_adj <- min(contrast_code)
## Compute the variances for VPC
Raaijmakers1999_lm <- lmer(RT ~ SOA + (1|Item) + (1 + SOA|Subject), data = quasif)
## Compute Residual variance
VAR_Residual <- var(resid(Raaijmakers1999_lm))
## Compute Variances of subject intercepts and slopes
VAR_Subject <- apply(ranef(Raaijmakers1999_lm)$Subject,2,var)
## ComputeVariances of item intercepts
VAR_Item <- var(ranef(Raaijmakers1999_lm)$Item)

## Compute generalized effect size
ES <- t(contrast_code) %*% contrast_means*(b_adj - a_adj)/sum(contrast_code^2 * sqrt(sum(VAR_Residual, VAR_Subject, VAR_Item)))

ES

## Compute VPCs
VPC_Residual <- (VAR_Residual+VAR_Subject[1])/sum(VAR_Residual, VAR_Subject, VAR_Item)
VPC_Subject_Slope <- VAR_Subject[2]/sum(VAR_Residual, VAR_Subject, VAR_Item)
VPC_Item_Intercept <- VAR_Item/sum(VAR_Residual, VAR_Subject, VAR_Item)

print(c(VPC_Item_Intercept, VPC_Subject_Slope, VPC_Residual))