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Pairwise post hoc DIF analysis

Source: R/pairwiseDIF.R
pairwiseDIF.Rd

Conduct pairwise Wald follow-up tests after omnibus DIF analysis with three or more groups. The input can be a dif object returned by dif(), in which case DIF items are selected using adjusted omnibus p-values, or raw data plus user-specified DIF items and optional anchor items. plot() function can be used to draw grouped bar chart for DIF items.

Usage

pairwiseDIF(
  object = NULL,
  dat = NULL,
  Q = NULL,
  group = NULL,
  model = "GDINA",
  sequential = FALSE,
  dif.items = NULL,
  anchor.items = NULL,
  alpha.level = 0.05,
  p.adjust.methods = "holm",
  SE.type = NULL,
  ...
)

Arguments

object

an object returned by dif().

dat

item responses from two or more groups; missing data need to be coded as NA.

Q

Q-matrix specifying the association between items and attributes.

group

a factor or a vector indicating the group each individual belongs to.

model

model for each item.

sequential

Logical; whether a sequential model is fit to the data. Default is FALSE.

dif.items

which items are subject to pairwise DIF follow-up.

anchor.items

optional anchor items. If omitted, all non-DIF items are treated as shared across groups.

alpha.level

adjusted omnibus p-value cutoff used to flag DIF items when object is supplied.

p.adjust.methods

adjusted p-values for pairwise Wald tests within each item.

SE.type

Type of standard error estimation methods for the Wald test.

...

arguments passed to GDINA() for the final post hoc refit.

Value

A pairwiseDIF object containing the pairwise Wald test table and final post hoc fit.

See also

dif

Author

Wenchao Ma, The University of Minnesota, wma@umn.edu

Examples

if (FALSE) { # \dontrun{

set.seed(123456)
N <- 500
Q <- sim30GDINA$simQ
gs <- matrix(.2,ncol = 2, nrow = nrow(Q))
# By default, individuals are simulated from uniform distribution
# and deltas are simulated randomly
sim1 <- simGDINA(N,Q,gs.parm = gs,model="DINA")
sim2 <- simGDINA(N,Q,gs.parm = gs,model=c(rep("DINA",nrow(Q)-1),"DINO"))
sim3 <- simGDINA(N,Q,gs.parm = gs,model="DINA")
dat <- rbind(extract(sim1,"dat"),extract(sim2,"dat"),extract(sim3,"dat"))
gr <- rep(c("G1","G2","G3"),each=N)

# DIF using Wald test - omnibus test
dif.wald <- dif(dat, Q, group=gr, method = "Wald")
dif.wald
# pairwise comparison between all pair of groups
dif.pair = pairwiseDIF(dif.wald)
dif.pair
# draw plot to show the DIF
plot(dif.pair, withSE = TRUE)
} # }