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Tidy a mirt model into a data frame of parameters

Source: R/tidy.R
tidy_mirt.Rd

Returns one row per estimated parameter, ready for dplyr, tables, and plotting. For unidimensional models the traditional IRT parameterization (discrimination a, difficulty b, guessing g, upper bound u) is used by default; multidimensional models are reported in slope-intercept form.

Usage

# S3 method for class 'SingleGroupClass'
tidy(
  x,
  IRTpars = TRUE,
  conf.int = FALSE,
  conf.level = 0.95,
  group_pars = FALSE,
  ...
)

# S3 method for class 'MultipleGroupClass'
tidy(
  x,
  IRTpars = TRUE,
  conf.int = FALSE,
  conf.level = 0.95,
  group_pars = TRUE,
  ...
)

Arguments

x

a model returned by mirt::mirt() or mirt::multipleGroup().

IRTpars

logical; use the traditional IRT parameterization when possible. Ignored (treated as FALSE) for multidimensional models.

conf.int

logical; add Wald confidence limits (needs standard errors, i.e. the model fitted with SE = TRUE).

conf.level

confidence level for conf.int.

group_pars

logical; also return latent mean and (co)variance parameters.

...

unused.

Value

A tibble with columns item, itemtype, term, estimate, and std.error (plus group, conf.low, conf.high when relevant).

Examples

mod <- mirt(expand.table(LSAT7), 1, SE = TRUE, verbose = FALSE)
tidy(mod)
#> # A tibble: 10 × 5
#>    item   itemtype term  estimate std.error
#>    <chr>  <chr>    <chr>    <dbl>     <dbl>
#>  1 Item.1 2PL      a        0.988     0.177
#>  2 Item.1 2PL      b       -1.88      0.264
#>  3 Item.2 2PL      a        1.08      0.169
#>  4 Item.2 2PL      b       -0.748     0.109
#>  5 Item.3 2PL      a        1.71      0.320
#>  6 Item.3 2PL      b       -1.06      0.115
#>  7 Item.4 2PL      a        0.765     0.134
#>  8 Item.4 2PL      b       -0.635     0.130
#>  9 Item.5 2PL      a        0.736     0.151
#> 10 Item.5 2PL      b       -2.52      0.446
tidy(mod, conf.int = TRUE)
#> # A tibble: 10 × 7
#>    item   itemtype term  estimate std.error conf.low conf.high
#>    <chr>  <chr>    <chr>    <dbl>     <dbl>    <dbl>     <dbl>
#>  1 Item.1 2PL      a        0.988     0.177    0.641     1.34 
#>  2 Item.1 2PL      b       -1.88      0.264   -2.40     -1.36 
#>  3 Item.2 2PL      a        1.08      0.169    0.750     1.41 
#>  4 Item.2 2PL      b       -0.748     0.109   -0.962    -0.533
#>  5 Item.3 2PL      a        1.71      0.320    1.08      2.33 
#>  6 Item.3 2PL      b       -1.06      0.115   -1.28     -0.832
#>  7 Item.4 2PL      a        0.765     0.134    0.502     1.03 
#>  8 Item.4 2PL      b       -0.635     0.130   -0.890    -0.380
#>  9 Item.5 2PL      a        0.736     0.151    0.440     1.03 
#> 10 Item.5 2PL      b       -2.52      0.446   -3.39     -1.65