Given an estimated model from any of mirt's model fitting functions this function will convert
the model parameters into the design data frame of starting values and other parameter
characteristics (similar to using the pars = 'values' for obtaining starting values).
mod2values(x)an estimated model x from the mirt package
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
# \donttest{
dat <- expand.table(LSAT7)
mod <- mirt(dat, 1)
values <- mod2values(mod)
values
#> group item class name parnum value lbound ubound est
#> 1 all Item.1 dich a1 1 0.9879254 -Inf Inf TRUE
#> 2 all Item.1 dich d 2 1.8560605 -Inf Inf TRUE
#> 3 all Item.1 dich g 3 0.0000000 0e+00 1 FALSE
#> 4 all Item.1 dich u 4 1.0000000 0e+00 1 FALSE
#> 5 all Item.2 dich a1 5 1.0808847 -Inf Inf TRUE
#> 6 all Item.2 dich d 6 0.8079786 -Inf Inf TRUE
#> 7 all Item.2 dich g 7 0.0000000 0e+00 1 FALSE
#> 8 all Item.2 dich u 8 1.0000000 0e+00 1 FALSE
#> 9 all Item.3 dich a1 9 1.7058006 -Inf Inf TRUE
#> 10 all Item.3 dich d 10 1.8042187 -Inf Inf TRUE
#> 11 all Item.3 dich g 11 0.0000000 0e+00 1 FALSE
#> 12 all Item.3 dich u 12 1.0000000 0e+00 1 FALSE
#> 13 all Item.4 dich a1 13 0.7651853 -Inf Inf TRUE
#> 14 all Item.4 dich d 14 0.4859966 -Inf Inf TRUE
#> 15 all Item.4 dich g 15 0.0000000 0e+00 1 FALSE
#> 16 all Item.4 dich u 16 1.0000000 0e+00 1 FALSE
#> 17 all Item.5 dich a1 17 0.7357980 -Inf Inf TRUE
#> 18 all Item.5 dich d 18 1.8545127 -Inf Inf TRUE
#> 19 all Item.5 dich g 19 0.0000000 0e+00 1 FALSE
#> 20 all Item.5 dich u 20 1.0000000 0e+00 1 FALSE
#> 21 all GROUP GroupPars MEAN_1 21 0.0000000 -Inf Inf FALSE
#> 22 all GROUP GroupPars COV_11 22 1.0000000 1e-04 Inf FALSE
#> prior.type prior_1 prior_2
#> 1 none NaN NaN
#> 2 none NaN NaN
#> 3 none NaN NaN
#> 4 none NaN NaN
#> 5 none NaN NaN
#> 6 none NaN NaN
#> 7 none NaN NaN
#> 8 none NaN NaN
#> 9 none NaN NaN
#> 10 none NaN NaN
#> 11 none NaN NaN
#> 12 none NaN NaN
#> 13 none NaN NaN
#> 14 none NaN NaN
#> 15 none NaN NaN
#> 16 none NaN NaN
#> 17 none NaN NaN
#> 18 none NaN NaN
#> 19 none NaN NaN
#> 20 none NaN NaN
#> 21 none NaN NaN
#> 22 none NaN NaN
#use the converted values as starting values in a new model, and reduce TOL
mod2 <- mirt(dat, 1, pars = values, TOL=1e-5)
# }