Compute latent regression fixed effect expected values
Create expected values for fixed effects parameters in latent regression models.
fixef(x)
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi: 10.18637/jss.v048.i06
Chalmers, R. P. (2015). Extended Mixed-Effects Item Response Models with the MH-RM Algorithm. Journal of Educational Measurement, 52, 200-222. doi: 10.1111/jedm.12072
## Not run: #simulate data set.seed(1234) N <- 1000 # covariates X1 <- rnorm(N); X2 <- rnorm(N) covdata <- data.frame(X1, X2) Theta <- matrix(0.5 * X1 + -1 * X2 + rnorm(N, sd = 0.5)) #items and response data a <- matrix(1, 20); d <- matrix(rnorm(20)) dat <- simdata(a, d, 1000, itemtype = '2PL', Theta=Theta) #conditional model using X1 and X2 as predictors of Theta mod1 <- mirt(dat, 1, 'Rasch', covdata=covdata, formula = ~ X1 + X2) #latent regression fixed effects (i.e., expected values) fe <- fixef(mod1) head(fe) # with mixedmirt() mod1b <- mixedmirt(dat, covdata, 1, lr.fixed = ~ X1 + X2, fixed = ~ 0 + items) fe2 <- fixef(mod1b) head(fe2) ## End(Not run)
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