data = read.table("test.docx")
res = data[,1:10]
gender = data[,"gender"]

library("mirt")
people = nrow(res)
itemnum = ncol(res)
group = rep('0_male', people)
group[gender==1] = "1_female"

mg = multipleGroup(
  res,
  model = 1,
  group = group,
  itemtype = "gpcm",
  invariance = c('slopes', 'intercepts', 'free_var','free_means'),
  method = "EM",
  dentype = "Gaussian"
)
coef(mg, simplify=TRUE)



library("regDIF")
fit <- regDIF(item.data = res, pred.data = gender
              ,item.type="2pl", num.tau = 5,control=list(tol=1e-4)
              ,anchor=1:itemnum,tau=0)
fit$impact
fit$base