A question about the invariance() in multigroup()

[Yingbin Zhang]

Hi Phil,

I'm trying to compare factor scores between two groups via multipleGroup().
I constrained all parameters except latent means equaI across two groups with the following syntax:

  model.mnrm<-mirt.model("F1=1-8
                         F2=1-8
                         COV=F1*F2")

  multipleGroup(mse, model.mnrm, itemtype = 'gpcm', gpcm_mats = mats,
                         group = group, invariance=c('slopes', 'intercepts', 'free_means') )

However, the results shown that the covariance between factor 1 and factor 2 was not constrained equal across groups:

$Group1
.....

$means
F1 F2 
 0  0 

$cov
     F1 F2
F1  1.0 NA
F2 -0.2  1


$Group2
...

$means
   F1    F2 
1.422 0.180 

$cov
      F1 F2
F1 1.000 NA
F2 0.075  1

How can I set the covariance equal across groups?
Thank you very much.

Best,
Yingbin

[Phil Chalmers]

It might seem a little odd, but the group-level parameters as stored as the (J + 1)th item internally. So in your case with the mirt.model syntax you can specify constraints with the index of 9. Here's and example with J = 15 items:

set.seed(12345)

a <- matrix(abs(rnorm(15,1,.3)), ncol=1)

d <- matrix(rnorm(15,0,.7),ncol=1)

itemtype <- rep('2PL', nrow(a))

N <- 1000

dataset1 <- simdata(a, d, N, itemtype)

dataset2 <- simdata(a, d, N, itemtype, mu = .1, sigma = matrix(1.5))

dat <- rbind(dataset1, dataset2)

group <- c(rep('D1', N), rep('D2', N))

model <-  model.mnrm<-mirt.model("F1=1-15

                         F2=1-15

                         COV=F1*F2

CONSTRAINB = (16, COV_21")

mod_configural <- multipleGroup(dat, model, group = group) #completely separate analyses

coef(mod_configural, simplify=TRUE)

If you didn't know that COV_21 was the correct parameter, check the starting value names first by passing multipleGroup(..., pars = 'values'). HTH.

Phil

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[Yingbin Zhang]

Thank you very much. The "CONSTRAINB" works.

Best,
Yingbin


在 2018年2月19日星期一 UTC+8下午9:43:43，Phil Chalmers写道：

Phil

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