{smcl} {* *! version 1,0 2021.03.09}{...} {viewerjumpto "Syntax" "uirt_sx2##syntax"}{...} {viewerjumpto "Description" "uirt_sx2##description"}{...} {viewerjumpto "Options" "uirt_sx2##options"}{...} {viewerjumpto "Examples" "uirt_sx2##examples"}{...} {viewerjumpto "Stored results" "uirt_sx2##results"}{...} {viewerjumpto "References" "uirt_sx2##references"}{...} {cmd:help uirt_sx2} {hline} {title:Title} {phang} {bf:uirt_sx2} {hline 2} Postestimation command of {helpb uirt} to compute S-X2 item-fit statistic {marker syntax}{...} {title:Syntax} {p 8 17 2} {cmd:uirt_sx2} [{varlist}] [{cmd:,}{it:{help uirt_sx2##options:options}}] {pmore} {it:varlist} must include only variables that were declared in the main list of items of current {cmd:uirt} run. If {it:varlist} is skipped or asterisk * is used, {cmd:uirt_sx2} will either display the results that are currently stored in {cmd: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 {cmd:uirt} run. This behavior depends on whether S-X2 item-fit statistics were produced by current uirt run or not. {synoptset 24 tabbed}{p2colset 7 32 34 4} {marker options}{...} {synopthdr :Options} {synoptline} {synopt:{opt minf:req(#)}} minimum expected number of observations in ability intervals (NP and NQ); default: minf(1){p_end} {synoptline} {marker description}{...} {title:Description} {pstd} {cmd:uirt_sx2} is a postestimation command of {helpb 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 {cmd:r(item_fit_SX2)}. {marker options}{...} {title:Options} {phang} {opt minf:req(#)} 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 {opt minf:req(1)}. {marker examples}{...} {title:Examples} {pstd}Setup{p_end} {phang2}{cmd:. webuse masc2} {p_end} {pstd}Fit an IRT model with all items being 1PLM (1PLM is a dichotomous case of PCM) {p_end} {phang2}{cmd:. uirt q*,pcm(*)} {p_end} {pstd}Compute S-X2 item fit statistic for all items {p_end} {phang2}{cmd:. uirt_sx2 } {p_end} {pstd}Re-fit the model with all items being 2PLM (the default for {cmd:uirt}), and compute S-X2 for all items under this model {p_end} {phang2}{cmd:. uirt q*} {p_end} {phang2}{cmd:. uirt_sx2 } {p_end} {pstd}Re-fit the model asking item q6 to be 3PLM, and compute S-X2 only for that item {p_end} {phang2}{cmd:. uirt q*,guess(q6,lr(1))} {p_end} {phang2}{cmd:. uirt_sx2 q6} {p_end} {marker results}{...} {title:Stored results} {syntab: {cmd: uirt_sx2} stores the following in r():} {p2col 5 17 21 2: Matrices}{p_end} {synopt:{cmd:r(item_fit_SX2)}}item-fit results for S-X2 statistic{p_end} {title:Author} Bartosz Kondratek everythingthatcounts@gmail.com {marker references}{...} {title:References} {phang} Orlando, M., & Thissen, D. 2000. Likelihood-based item-fit indices for dichotomous item response theory models. {it:Applied Psychological Measurement}, 24, 50{c -}64.