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help for {cmd:difd} {right:(April 11, 2011)}
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{cmd:*** Please note that as of May 2015 we recommend -difdetect- from SSC over this program. ***

{title:Detection of differential item function (DIF).}

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{cmd:difd} {it: varlist} {cmd:,}
{cmd:ABility}{it:(varlist)} {cmd:GRoups}{it:(varlist)}    {break}  
 [{cmdab:CATegorical}{cmd:}{it:(varlist)}{cmd:}
{cmdab:RUnname}{cmd:}{it:(str)}{cmd:} 	{cmdab:NUL}{cmd:}{it:(#)}{cmd:}
{cmdab:NUP}{cmd:}{it:(#)}{cmd:} 		{cmdab:NUPValue}{cmd:}{it:(#)}{cmd:}
{cmdab:UBeta}{cmd:}{it:(#)}{cmd:}		{cmdab:UBP}{cmd:}{it:(#)}{cmd:}
{cmdab:ULPV}{cmd:}{it:(#)}{cmd:}		{cmdab:UP}{cmd:}{it:(#)}{cmd:}
{cmdab:UPPValue}{cmd:}{it:(#)}{cmd:}	{cmdab:ITemsub}{cmd:}{it:(#)}{cmd:}]

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where:

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{it:varlist} is the list of variables (items, blocks) to be tested for DIF

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{it:id} is the subject id variable.

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{it:ability} is the ability variable(s).

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{it:groups} is the list of grouping variables.  Continuous ‘grouping’ variables are permitted.

{title:Options}

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{cmdab:categorical} is the list of any group variables that are categorical and have more than 2 levels.  Note that it is simpler to omit dichotomous variables from this list.  Default is none (all continuous or dichotomous).

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{cmdab:runname} names the log file DIFdRUnname.log.  Default is DIFd.log.

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{cmdab:nul} indicates whether the log-likelihood test will be used as a criterion for non-uniform DIF.  Default is yes (1).  Nul(0) will omit this criterion.

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{cmdab:nup} indicates whether the Wald test for the interaction term will be used as a criterion for non-uniform DIF.  Default is no (0).  Nup(1) will include this criterion.

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{cmdab:nupvalue} is the p-value for testing non-uniform DIF.  Default is 0.05.

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{cmdab:ubeta} indicates whether the change in the ability coefficient will be used as a criterion for uniform DIF.  Default is yes (1).  UBeta(0) will omit this criterion.

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{cmdab:ubp} is percent change in the ability coefficient for determining uniform DIF.  Default is .10.  A positive change indicates an increase in the relationship between ability and the outcome with a higher value of the grouping variable.

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{cmdab:ul} indicates whether the log-likelihood test will be used as a criterion for uniform DIF.  Default is no (0).  UL(1) will include this criterion.

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{cmdab:ulpvalue} is the p-value for testing uniform DIF with the log-likelhood method.  Default is 0.05.

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{cmdab:up} indicates whether the Wald test for the group term will be used as a criterion for uniform DIF.  Default is no (0).  UP(1) will include this criterion.

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{cmdab:ulpvalue} is the p-value for testing uniform DIF with the Wald test.  Default is 0.05.

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{cmdab:itemsub} subtracts the item value from the ability measure.  Default is no (0).  ITemsub(1) will include this feature.  

{title:Remarks}

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Sends DIF results to DIFd{it:runname}.log.  

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DIF results for categorical grouping variables will be in terms of the ordered values of group.  For example, if {it:ethnic} has 3 levels, 3 sets of DIF results will be reported: {it:ethnic12, ethnic13, ethnic23}, 
where {it:ethnic12} compares the 2 lowest values of 
{it:ethnic}, {it:ethnic13} the lowest and highest, etc.

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Generates an output data set, DIFd.dta, which includes individual model results, with Brant test p-values for ordinal items and Hosmer-Lemeshow p-values for binary items.  [The relevance of the fit statistics has not been established for DIF.]  

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Displays warning messages when models do not converge, collinearity problems are observed, models are completely determined, standard errors are large, or Brant tests are not possible. 

{title:Examples}

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difd item1-item13, id(id) ru(gender0) ab(theta0) gr(g) 

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difd apple - item13, id(id) ab(theta0) gr(eth) cat(eth) nupv(0.01) ul(1) ulpv(.01) 


{title:Authors}

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Paul Crane, Laura Gibbons, Lance Jolley, and Gerald van Belle.  University of Washington, Copyright 2005.{break}
Email: {browse mailto: gibbonsl@u.washington.edu}

{title:Also see}

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{cmd:difdetect}