*! version 1,0 2021.03.09
help uirt_sx2

Title

uirt_sx2 -- Postestimation command of uirt to compute S-X2 item-fit statistic

Syntax

uirt_sx2 [varlist] [,options]

varlist must include only variables that were declared in the main list of items of current uirt run.
If varlist is skipped or asterisk * is used, uirt_sx2 will either display the results that are currently stored in e(item_fit_SX2) matrix
or it will compute S-X2 item-fit statistic for all items declared in main list of items of current uirt run.
This behavior depends on whether S-X2 item-fit statistics were produced by current uirt run or not.

Options

minfreq(#) minimum expected number of observations in ability intervals (NP and NQ); default: minf(1)

Description

uirt_sx2 is a postestimation command of uirt that computes the classical S-X2 statistic proposed by Orlando and Thissen (2000).
It is available only for dichotomous items and it cannot be used in multigroup setting.
The number-correct score used for grouping is obtained from dichotomous items
- if polytomous items are present in data, they are ignored in computation of S-X2.
If a dichotomous item has missing responses it is also ignored in computation of S-X2. The results are stored in r(item_fit_SX2).

Options

minfreq(#) sets a minimum for both NP and NQ integrated over any ability interval, where:
N is the number of observations,
P is the expected item mean, and Q=(1-P).
Default value is minfreq(1).

Examples

Setup

. webuse masc2

Fit an IRT model with all items being 1PLM (1PLM is a dichotomous case of PCM)

. uirt q*,pcm(*)

Compute S-X2 item fit statistic for all items

. uirt_sx2

Re-fit the model with all items being 2PLM (the default for uirt), and compute S-X2 for all items under this model

. uirt q*

. uirt_sx2

Re-fit the model asking item q6 to be 3PLM, and compute S-X2 only for that item

. uirt q*,guess(q6,lr(1))

. uirt_sx2 q6

Stored results

uirt_sx2 stores the following in r():

Matrices

r(item_fit_SX2) item-fit results for S-X2 statistic

Author

Bartosz Kondratek
everythingthatcounts@gmail.com

References

Orlando, M., & Thissen, D. 2000.
Likelihood-based item-fit indices for dichotomous item response theory models.
Applied Psychological Measurement, 24, 50-64.