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121 lines
4.1 KiB
Plaintext
121 lines
4.1 KiB
Plaintext
7 months ago
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{smcl}
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{* 20Oct2009 version 1.7.6 jsl}{...}
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{cmd:help mlogtest}: Help for tests for the multinomial logit model - 2009-10-20
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{hline}
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{p2colset 4 14 14 2}{...}
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{title:Overview}
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{p 4 4 2 78}
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The command {cmd:mlogtest} computes a variety of tests for the multinomial logit model.
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The user selects the tests they want by specifying the appropriate options. For each
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independent variable, {cmd:mlogtest} can perform either a LR or Wald test of the
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null hypothesis that the coefficients of the variable equal zero across all equations.
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{cmd:mlogtest} can also perform Wald or LR tests of whether any pair of outcome
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categories can be combined. In addition, {cmd:mlogtest} computes the Hausman and
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Small-Hsiao tests of the assumption of the independence of irrelevance alternatives (IIA)
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for each possible omitted category.
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{title:Syntax}
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{p 8 13 2}
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{cmd:mlogtest} [{it:varlist}]
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[{cmd:,} {it:options}]
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{synoptset 15 tabbed}{...}
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{synopthdr}
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{synoptline}
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{syntab:{it:Tests of variables}}
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{synopt:{opt varlist}}Selects variables to test with the wald or lr options.
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By default, all variables in the model are tested.{p_end}
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{synopt:{opt w:ald}}Use Wald tests for each variable.{p_end}
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{synopt:{opt lr}}Use LR test for each variable.{p_end}
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{synopt:{opt set}{bf:(}{it:varlist} [{bf:\} {it:varlist}]{bf:)}}
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Specify a set of variables is to be tested with {cmd:lrtest} or
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{cmd:lr}. The slash {bf:\} specifies multiple sets of variables.
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This option is particularly useful when a categorical variable is
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included as a set of dummy variables, allowing that the coefficients for
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all of the dummy variables are zero across all equations.{p_end}
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{syntab:{it:Tests for combining categories}}
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{synopt:{opt c:ombine}}Compute Wald tests of whether two outcomes can be
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combined.{p_end}
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{synopt:{opt lrc:ombine}}Compute LR tests of whether two outcomes can be
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combined.{p_end}
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{syntab:{it:Tests of IIA}}
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{synopt:{opt h:ausman}} Compute Hausman-McFadden tests using Stata's {cmd:hausman}
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command.{p_end}
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{synopt:{opt d:etail}}Detailed results for {cmd:hausman} option are given.{p_end}
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{synopt:{opt sm:hsiao}}Compute Small-Hsiao tests{p_end}
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{synopt:{opt su:est}}Compute Hausman-McFadden tests using Stata's {cmd:suest}
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command.{p_end}
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{synopt:{opt i:ia}}All of the IIA tests should be computed.{p_end}
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{synopt:{opt b:ase}}Conduct IIA test omitting the base category of the original
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{cmd:mlogit} estimation. This is done by re-estimating the model using the largest
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remaining category as the base category. The original estimates are
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restored to memory.{p_end}
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{syntab:{it:Other}}
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{synopt:{opt a:ll}}All tests should be performed.{p_end}
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{synoptline}
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{title:Examples}
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{bf: . mlogit whoclass income dad_educ male black hispanic asian}
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{bf: . * compute all tests}
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{bf: . mlogtest, all}
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{bf: . mlogit whoclass income dad_educ male black hispanic asian singlpar}
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{bf: > stepmommlogit whoclass income dad_educ male black hispanic asian}
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{bf: . * teset groups of dummy variables}
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{bf: . mlogtest, lr set(black hispanic asian \ singlpar stepmom stepdad)}
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{title:Returned matrices}
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{p 4 4}
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{bf:r(combine)}: results of Wald tests to combine categories. Rows represent all
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contrasts among categories; columns indicates the categories contrasted, the
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chisq, df, and p of test.
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{p 4 4}
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{bf:r(lrcomb)}: results of LR tests to combine categories. Rows represent all
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contrasts among categories; columns indicates the categories contrasted, the
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chisq, df, and p of test.
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{p 4 4}
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{bf:r(hausman)}: results of Hausman tests of IIA assumption. Each row is one test.
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Columns indicate the omitted category of a given test, the chisq, df, and p.
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{p 4 4}
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{bf:r(smhsiao)}: results of Small-Hsiao tests of IIA assumption.
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{p 4 4}
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{bf:r(wald)}: results of Wald test that all coefficients of an independent variable
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equals zero
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{p 4 4}
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{bf:r(lrtest)}: results of likelihood-ratio test that all coefficients of an
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independent variable equals zero
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{title:Acknowledgment}
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{p 4 4}
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The code used for the Small-Hsiao test is based on a program by Nick Winter.
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INCLUDE help spost_footer
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