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936 lines
36 KiB
Plaintext
936 lines
36 KiB
Plaintext
7 months ago
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{smcl}
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{* 08oct2009}{...}
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{hi:help estadd}{right:also see: {helpb esttab}, {helpb estout}, {helpb eststo}, {helpb estpost}}
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{right: {browse "http://repec.org/bocode/e/estout"}}
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{hline}
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{title:Title}
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{p 4 4 2}{hi:estadd} {hline 2} Add results to (stored) estimates
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{title:Syntax}
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{p 8 15 2}
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{cmd:estadd} {it:{help estadd##subcommands:subcommand}} [{cmd:,}
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{it:{help estadd##opts:options}} ] [ {cmd::} {it:namelist} ]
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where {it:namelist} is {cmd:_all} | {cmd:*} | {it:name} [{it:name} ...]
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{marker subcommands}
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{it:subcommands}{col 26}description
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{hline 64}
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Elementary
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{helpb estadd##local:{ul:loc}al} {it:name ...}{col 26}{...}
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add a macro
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{helpb estadd##scalar:{ul:sca}lar} {it:name} {cmd:=} {it:exp}{col 26}{...}
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add a scalar
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{helpb estadd##matrix:{ul:mat}rix} {it:name} {cmd:=} {it:mat}{col 26}{...}
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add a matrix
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{helpb estadd##rreturn:r({it:name})}{col 26}{...}
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add contents of {cmd:r(}{it:name}{cmd:)} (matrix or scalar)
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Statistics for each
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coefficient
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{helpb estadd##beta:beta}{col 26}{...}
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standardized coefficients
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{helpb estadd##vif:vif}{col 26}{...}
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variance inflation factors (after {cmd:regress})
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{helpb estadd##pcorr:pcorr}{col 26}{...}
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partial (and semi-partial) correlations
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{helpb estadd##expb:expb}{col 26}{...}
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exponentiated coefficients
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{helpb estadd##ebsd:ebsd}{col 26}{...}
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standardized factor change coefficients
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{helpb estadd##mean:mean}{col 26}{...}
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means of regressors
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{helpb estadd##sd:sd}{col 26}{...}
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standard deviations of regressors
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{helpb estadd##summ:summ}{col 26}{...}
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various descriptives of the regressors
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Summary statistics
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{helpb estadd##coxsnell:coxsnell}{col 26}{...}
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Cox & Snell's pseudo R-squared
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{helpb estadd##nagelkerke:nagelkerke}{col 26}{...}
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Nagelkerke's pseudo R-squared
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{helpb estadd##lrtest:lrtest} {it:model}{col 26}{...}
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likelihood-ratio test
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{helpb estadd##ysumm:ysumm}{col 26}{...}
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descriptives of the dependent variable
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Other
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{helpb estadd##margins:margins}{col 26}{...}
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add results from {cmd:margins} (Stata 11)
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{help estadd##spost:SPost}
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{helpb estadd##brant:brant}{col 26}{...}
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add results from {cmd:brant} (if installed)
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{helpb estadd##fitstat:fitstat}{col 26}{...}
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add results from {cmd:fitstat} (if installed)
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{helpb estadd##listcoef:listcoef}{col 26}{...}
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add results from {cmd:listcoef} (if installed)
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{helpb estadd##mlogtest:mlogtest}{col 26}{...}
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add results from {cmd:mlogtest} (if installed)
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{helpb estadd##prchange:prchange}{col 26}{...}
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add results from {cmd:prchange} (if installed)
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{helpb estadd##prvalue:prvalue}{col 26}{...}
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add results from {cmd:prvalue} (if installed)
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{helpb estadd##asprvalue:asprvalue}{col 26}{...}
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add results from {cmd:asprvalue} (if installed)
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{hline 64}
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{marker opts}
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{it:{help estadd##options:options}}{col 26}description
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{hline 64}
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{cmdab:r:eplace}{col 26}{...}
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permit overwriting existing {cmd:e()}'s
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{cmdab:p:refix(}{it:string}{cmd:)}{col 26}{...}
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specify prefix for names of added results
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{cmdab:q:uietly}{col 26}{...}
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suppress output from subcommand (if any)
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{it:subcmdopts}{col 26}{...}
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subcommand specific options
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{hline 64}
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{title:Description}
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{p 4 4 2}
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{cmd:estadd} adds additional results to the {cmd:e()}-returns of an
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estimation command (see help {help estcom}, help {helpb ereturn}). If no
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{it:namelist} is provided, then the results are added to the
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currently active estimates (i.e. the model fit last). If these
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estimates have been previously stored, the stored copy of the
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estimates will also be modified. Alternatively, if {it:namelist} is
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provided after the colon, results are added to all indicated sets of
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stored estimates (see help {helpb estimates store} or help
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{helpb eststo}). You may use the {cmd:*} and {cmd:?}
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wildcards in {it:namelist}. Execution is silent if {it:namelist} is
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provided.
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{p 4 4 2}
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Adding additional results to the {cmd:e()}-returns is useful, for example,
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if the estimates be tabulated by commands such as {helpb estout}
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or {helpb esttab}. See the {help estadd##examples:Examples} section below for
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illustration of the usage of {cmd:estadd}.
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{p 4 4 2}Technical note: Some of the subcommands below make use of the
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information contained in {cmd:e(sample)} to determine estimation sample.
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These subcommands return error if the estimates do not contain
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{cmd:e(sample)}.
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{title:Subcommands}
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{dlgtab:Elementary}
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{marker local}
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{p 4 8 2}
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{cmd:estadd} {cmdab:loc:al} {it:name ...}
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{p 8 8 2}
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adds in macro {cmd:e(}{it:name}{cmd:)} the specified contents (also
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see help {helpb ereturn}).
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{marker scalar}
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{p 4 8 2}
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{cmd:estadd} {cmdab:sca:lar} {it:name} {cmd:=} {it:exp}
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{p 8 8 2}
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adds in scalar {cmd:e(}{it:name}{cmd:)} the evaluation of {it:exp}
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(also see help {helpb ereturn}).
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{p 4 8 2}
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{cmd:estadd} {cmdab:sca:lar} {cmd:r(}{it:name}{cmd:)}
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{p 8 8 2}
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adds in scalar {cmd:e(}{it:name}{cmd:)} the value of scalar {cmd:r(}{it:name}{cmd:)}.
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{p 4 8 2}
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{cmd:estadd} {cmdab:sca:lar} {it:name}
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{p 8 8 2}
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adds in scalar {cmd:e(}{it:name}{cmd:)} the the value of scalar {it:name}.
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{marker matrix}
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{p 4 8 2}
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{cmd:estadd} {cmdab:mat:rix} {it:name} {cmd:=} {it:matrix_expression}
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{p 8 8 2}
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adds in matrix {cmd:e(}{it:name}{cmd:)} the evaluation of {it:matrix_expression}
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(also see help {helpb matrix define}).
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{p 4 8 2}
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{cmd:estadd} {cmdab:mat:rix} {cmd:r(}{it:name}{cmd:)}
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{p 8 8 2}
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adds in matrix {cmd:e(}{it:name}{cmd:)} a copy of matrix {cmd:r(}{it:name}{cmd:)}.
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{p 4 8 2}
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{cmd:estadd} {cmdab:mat:rix} {it:name}
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{p 8 8 2}
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adds in matrix {cmd:e(}{it:name}{cmd:)} a copy of matrix {it:name}.
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{marker rreturn}
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{p 4 8 2}
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{cmd:estadd} {cmd:r(}{it:name}{cmd:)}
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{p 8 8 2}
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adds in {cmd:e(}{it:name}{cmd:)} the value of scalar {cmd:r(}{it:name}{cmd:)}
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or a copy of matrix {cmd:r(}{it:name}{cmd:)}, depending on the nature of
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{cmd:r(}{it:name}{cmd:)}.
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{dlgtab:Statistics for each coefficient}
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{marker beta}
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{p 4 8 2}
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{cmd:estadd} {cmd:beta}
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{p 8 8 2}
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adds in {cmd:e(beta)} the standardized beta coefficients.
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{marker vif}
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{p 4 8 2}
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{cmd:estadd} {cmd:vif} [{cmd:,} {cmdab:tol:erance} {cmdab:sqr:vif} ]
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{p 8 8 2}
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adds in {cmd:e(vif)} the variance inflation factors (VIFs) for the
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regressors (see help {helpb vif}). Note that {cmd:vif} only works
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with estimates produced by {helpb regress}. {cmd:tolerance}
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additionally adds the tolerances (1/VIF) in {cmd:e(tolerance)}.
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{cmd:sqrvif} additionally adds the square roots of the VIFs in
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{cmd:e(sqrvif)}.
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{marker pcorr}
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{p 4 8 2}
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{cmd:estadd} {cmd:pcorr} [{cmd:, semi} ]
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{p 8 8 2}
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adds the partial correlations (see help {helpb pcorr}) and,
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optionally, the semi-partial correlations between the dependent
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variable and the individual regressors (see, e.g., the {cmd:pcorr2}
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package from the SSC Archive). In the case of multiple-equations
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models, the results are computed for the first equation only. The
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partial correlations will be returned in {cmd:e(pcorr)} and, if
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{cmd:semi} is specified, the semi-partial correlations will be
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returned in {cmd:e(spcorr)}.
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{marker expb}
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{p 4 8 2}
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{cmd:estadd} {cmd:expb} [{cmd:,} {cmdab:nocons:tant} ]
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{p 8 8 2}
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adds in {cmd:e(expb)} the exponentiated coefficients (see the help
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{it:{help eform_option}}). {cmd:noconstant} excludes the constant
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from the added results.
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{marker ebsd}
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{p 4 8 2}
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{cmd:estadd} {cmd:ebsd}
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{p 8 8 2}
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adds in {cmd:e(ebsd)} the standardized factor change coefficients,
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i.e. exp(b_jS_j), where b_j is the raw coefficient and S_j is the
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standard deviation of regressor j, that are sometimes reported for
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logistic regression (see Long 1997).
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{marker mean}
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{p 4 8 2}
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{cmd:estadd} {cmd:mean}
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{p 8 8 2}
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adds in {cmd:e(mean)} the means of the regressors.
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{marker sd}
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{p 4 8 2}
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{cmd:estadd} {cmd:sd} [{cmd:,} {cmdab:nob:inary} ]
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{p 8 8 2}
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adds in {cmd:e(sd)} the standard deviations of the regressors.
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{cmd:nobinary} suppresses the computation of the standard deviation
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for 0/1 variables.
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{marker summ}
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{p 4 8 2}
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{cmd:estadd} {cmd:summ} [{cmd:,} {it:stats} ]
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{p 8 8 2}
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adds vectors of the regressors' descriptive statistics to the
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estimates. The following {it:stats} are available:
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{p_end}
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{marker stats}
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{it:stats}{col 26}description
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{hline 59}
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{cmdab:me:an}{col 26}mean
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{cmdab:su:m}{col 26}sum
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{cmdab:mi:n}{col 26}minimum
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{cmdab:ma:x}{col 26}maximum
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{cmdab:ra:nge}{col 26}range = max - min
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{cmd:sd}{col 26}standard deviation
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{cmdab:v:ar}{col 26}variance
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{cmd:cv}{col 26}coefficient of variation (sd/mean)
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{cmdab:sem:ean}{col 26}standard error of mean = sd/sqrt(n)
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{cmdab:sk:ewness}{col 26}skewness
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{cmdab:k:urtosis}{col 26}kurtosis
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{cmd:p1}{col 26}1st percentile
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{cmd:p5}{col 26}5th percentile
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{cmd:p10}{col 26}10th percentile
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{cmd:p25}{col 26}25th percentile
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{cmd:p50}{col 26}50th percentile
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{cmd:p75}{col 26}75th percentile
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{cmd:p90}{col 26}90th percentile
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{cmd:p95}{col 26}95th percentile
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{cmd:p99}{col 26}99th percentile
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{cmd:iqr}{col 26}interquartile range = p75 - p25
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{cmd:all}{col 26}all of the above
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{cmdab:med:ian}{col 26}equivalent to specifying "{cmd:p50}"
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{cmd:q}{col 26}equivalent to specifying "{cmd:p25 p50 p75}"
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{hline 59}
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{p 8 8 2}
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The default is {cmd:mean sd min max}. Alternatively, indicate the
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desired statistics. For example, to add information on the
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regressors' skewness and kurtosis, type
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{inp:. estadd summ, skewness kurtosis}
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{p 8 8 2}
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The statistics names are used as the names for the returned {cmd:e()}
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matrices. For example, {cmd:estadd summ, mean} will store the means
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of the regressors in {cmd:e(mean)}.
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{dlgtab:Summary statistics}
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{marker coxsnell}
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{p 4 8 2}
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{cmd:estadd} {cmd:coxsnell}
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{p 8 8 2}
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adds in {cmd:e(coxsnell)} the Cox & Snell pseudo R-squared, which is
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defined as
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{p 12 12 2}
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r2_coxsnell = 1 - ( L0 / L1 )^(2/N)
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{p 8 8 2}
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where L0 is the likelihood of the model without regressors, L1 the
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likelihood of the full model, and N is the sample size.
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{marker nagelkerke}
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{p 4 8 2}
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{cmd:estadd} {cmd:nagelkerke}
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{p 8 8 2}
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adds in {cmd:e(nagelkerke)} the Nagelkerke pseudo R-squared (or Cragg
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& Uhler pseudo R-squared), which is defined as
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{p 12 12 2}
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r2_nagelkerke = r2_coxsnell / (1 - L0^(2/N))
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{marker lrtest}
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{p 4 8 2}
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{cmd:estadd} {cmd:lrtest} {it:model} [{cmd:,} {cmdab:n:ame:(}{it:string}{cmd:)}
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{it:{help lrtest:lrtest_options}} ]
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{p 8 8 2}
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adds the results from a likelihood-ratio test, where {it:model} is
|
||
|
|
the comparison model (see help {helpb lrtest}). Added are
|
||
|
|
{cmd:e(lrtest_chi2)}, {cmd:e(lrtest_df)}, and {cmd:e(lrtest_p)}. The
|
||
|
|
names may be modified using the {cmd:name()} option. Specify
|
||
|
|
{cmd:name(}{it:myname}{cmd:)} to add {cmd:e(}{it:myname}{cmd:chi2)},
|
||
|
|
{cmd:e(}{it:myname}{cmd:df)}, and {cmd:e(}{it:myname}{cmd:p)}. See
|
||
|
|
help {helpb lrtest} for the {it:lrtest_options}.
|
||
|
|
|
||
|
|
{marker ysumm}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd} {cmd:ysumm} [{cmd:,} {it:stats} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
adds descriptive statistics of the dependent variable. See the
|
||
|
|
{helpb estadd##summ:summ} subcommand above for a list of the available
|
||
|
|
{it:stats}. The default is {cmd:mean sd min max}. The default prefix
|
||
|
|
for the names of the added scalars is {cmd:y} (e.g. the mean of the
|
||
|
|
dependent variable will be returned in {cmd:e(ymean)}). Use
|
||
|
|
{cmd:estadd}'s {cmd:prefix()} option to change the prefix. If a model
|
||
|
|
has multiple dependent variables, results for the first variable will
|
||
|
|
be added.
|
||
|
|
|
||
|
|
{dlgtab:Other}
|
||
|
|
{marker margins}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd} {cmd:margins} [{it:marginlist}] [{it:if}] [{it:in}] [{it:weight}] [, {it:options} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
adds results from the {cmd:margins} command, which was introduced
|
||
|
|
in Stata 11. See help {helpb margins} for options. All results returned by
|
||
|
|
{cmd:margins} except {cmd:e(V)} are added using "{cmd:margins_}" as a default
|
||
|
|
prefix. For example, the margins are added in {cmd:e(margins_b)}. The
|
||
|
|
standard errors are added in {cmd:e(margins_se)}. Use the {helpb estadd##opts:prefix()}
|
||
|
|
option to change the default prefix.
|
||
|
|
|
||
|
|
{marker spost}
|
||
|
|
{dlgtab:SPost}
|
||
|
|
|
||
|
|
{p 4 4 2} The following subcommands are wrappers for
|
||
|
|
commands from Long and Freese's {helpb SPost} package (see
|
||
|
|
{browse "http://www.indiana.edu/~jslsoc/spost.htm":http://www.indiana.edu/~jslsoc/spost.htm}). Type
|
||
|
|
|
||
|
|
. {net "from http://www.indiana.edu/~jslsoc/stata":net from http://www.indiana.edu/~jslsoc/stata}
|
||
|
|
|
||
|
|
{p 4 4 2}
|
||
|
|
to obtain the latest {cmd:SPost} version (spost9_ado). {cmd:SPost} for Stata 8 (spostado) is not
|
||
|
|
supported.
|
||
|
|
|
||
|
|
{p 4 4 2}For examples on using the subcommands see
|
||
|
|
{browse "http://repec.org/bocode/e/estout/spost.html":http://repec.org/bocode/e/estout/spost.html}.
|
||
|
|
|
||
|
|
{marker brant}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd brant} [{cmd:,} {it:{help brant:brant_options}} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
applies {helpb brant} from Long and
|
||
|
|
Freese's {helpb SPost} package and adds the returned results to
|
||
|
|
{cmd:e()}. You may specify {it:brant_options} as described in
|
||
|
|
help {helpb brant}. The following results are added:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
Scalars
|
||
|
|
{cmd:brant_chi2} Chi-squared of overall Brant test
|
||
|
|
{cmd:brant_df} Degrees of freedom of overall Brant test
|
||
|
|
{cmd:brant_p} P-value of overall Brant test
|
||
|
|
|
||
|
|
Matrix
|
||
|
|
{cmd:brant} Test results for individual regressors
|
||
|
|
(rows: chi2, p<chi2)
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{p 4 4 2}To address the rows of {cmd:e(brant)} in {helpb estout}'s {cmd:cells()}
|
||
|
|
option type {cmd:brant[chi2]} and {cmd:brant[p<chi2]}.
|
||
|
|
|
||
|
|
{marker fitstat}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd fitstat} [{cmd:,} {it:{help fitstat:fitstat_options}} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
applies {helpb fitstat} from Long and
|
||
|
|
Freese's {helpb SPost} package and adds the returned scalars to
|
||
|
|
{cmd:e()}. You may specify {it:fitstat_options} as described in
|
||
|
|
help {helpb fitstat}. Depending on model
|
||
|
|
and options, a selection of the following scalar statistics is added:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
{cmd:dev} Deviance (D)
|
||
|
|
{cmd:dev_df} Degrees of freedom of D
|
||
|
|
{cmd:lrx2} LR or Wald X2
|
||
|
|
{cmd:lrx2_df} Degrees of freedom of X2
|
||
|
|
{cmd:lrx2_p} Prob > LR or Wald X2
|
||
|
|
{cmd:r2_adj} Adjusted R2
|
||
|
|
{cmd:r2_mf} McFadden's R2
|
||
|
|
{cmd:r2_mfadj} McFadden's Adj R2
|
||
|
|
{cmd:r2_ml} ML (Cox-Snell) R2
|
||
|
|
{cmd:r2_cu} Cragg-Uhler(Nagelkerke) R2
|
||
|
|
{cmd:r2_mz} McKelvey & Zavoina's R2
|
||
|
|
{cmd:r2_ef} Efron's R2
|
||
|
|
{cmd:v_ystar} Variance of y*
|
||
|
|
{cmd:v_error} Variance of error
|
||
|
|
{cmd:r2_ct} Count R2
|
||
|
|
{cmd:r2_ctadj} Adj Count R2
|
||
|
|
{cmd:aic0} AIC
|
||
|
|
{cmd:aic_n} AIC*n
|
||
|
|
{cmd:bic0} BIC
|
||
|
|
{cmd:bic_p} BIC'
|
||
|
|
{cmd:statabic} BIC used by Stata
|
||
|
|
{cmd:stataaic} AIC used by Stata
|
||
|
|
{cmd:n_rhs} Number of rhs variables
|
||
|
|
{cmd:n_parm} Number of parameters
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{marker listcoef}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd listcoef} [{it:varlist}] [{cmd:,} {cmd:nosd} {it:{help listcoef:listcoef_options}} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
applies {helpb listcoef} from Long and
|
||
|
|
Freese's {helpb SPost} package and adds the returned results to
|
||
|
|
{cmd:e()}. You may specify {it:listcoef_options} as described in
|
||
|
|
help {helpb listcoef}. Furthermore, option {cmd:nosd} suppresses
|
||
|
|
adding the standard deviations of the variables in {cmd:e(b_sdx)}.
|
||
|
|
|
||
|
|
{p 8 8 2}Depending on the estimation command and options, several of the
|
||
|
|
following matrices are added:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
{cmd:b_xs} x-standardized coefficients
|
||
|
|
{cmd:b_ys} y-standardized coefficients
|
||
|
|
{cmd:b_std} Fully standardized coefficients
|
||
|
|
{cmd:b_fact} Factor change coefficients
|
||
|
|
{cmd:b_facts} Standardized factor change coefficients
|
||
|
|
{cmd:b_pct} Percent change coefficients
|
||
|
|
{cmd:b_pcts} Standardized percent change coefficients
|
||
|
|
{cmd:b_sdx} Standard deviation of the Xs
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{p 8 8 2}For nominal models ({helpb mlogit}, {helpb mprobit}) the
|
||
|
|
original parametrization of {cmd:e(b)} may not match the contrasts
|
||
|
|
computed by {cmd:listcoef}. To be able to tabulate standardized
|
||
|
|
coefficients along with the raw coefficients for the requested
|
||
|
|
contrasts, the following additional matrices are added for
|
||
|
|
these models:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
{cmd:b_raw} raw coefficients
|
||
|
|
{cmd:b_se} standard errors of raw coefficients
|
||
|
|
{cmd:b_z} z statistics
|
||
|
|
{cmd:b_p} p-values
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{marker mlogtest}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd mlogtest} [{it:varlist}] [{cmd:,} {it:{help mlogtest:mlogtest_options}} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
applies {helpb mlogtest} from Long and
|
||
|
|
Freese's {helpb SPost} package and adds the returned results to
|
||
|
|
{cmd:e()}. You may specify {it:mlogtest_options} as described in
|
||
|
|
help {helpb mlogtest}.
|
||
|
|
|
||
|
|
{p 8 8 2}Depending on the specified options, a selection of the following
|
||
|
|
returns are added:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
Scalars
|
||
|
|
{cmd:hausman_set}{it:#}{cmd:_chi2} Hausman IIA tests using {helpb hausman}
|
||
|
|
{cmd:hausman_set}{it:#}{cmd:_df}
|
||
|
|
{cmd:hausman_set}{it:#}{cmd:_p}
|
||
|
|
|
||
|
|
{cmd:suest_set}{it:#}{cmd:_chi2} Hausman IIA tests using {helpb suest}
|
||
|
|
{cmd:suest_set}{it:#}{cmd:_df}
|
||
|
|
{cmd:suest_set}{it:#}{cmd:_p}
|
||
|
|
|
||
|
|
{cmd:smhsiao_set}{it:#}{cmd:_chi2} Small-Hsiao IIA tests
|
||
|
|
{cmd:smhsiao_set}{it:#}{cmd:_df}
|
||
|
|
{cmd:smhsiao_set}{it:#}{cmd:_p}
|
||
|
|
|
||
|
|
{cmd:combine_}{it:#1}{cmd:_}{it:#2}{cmd:_chi2} Wald tests for combination of outcomes
|
||
|
|
{cmd:combine_}{it:#1}{cmd:_}{it:#2}{cmd:_df}
|
||
|
|
{cmd:combine_}{it:#1}{cmd:_}{it:#2}{cmd:_p}
|
||
|
|
|
||
|
|
{cmd:lrcomb_}{it:#1}{cmd:_}{it:#2}{cmd:_chi2} LR tests for combination of outcomes
|
||
|
|
{cmd:lrcomb_}{it:#1}{cmd:_}{it:#2}{cmd:_df}
|
||
|
|
{cmd:lrcomb_}{it:#1}{cmd:_}{it:#2}{cmd:_p}
|
||
|
|
|
||
|
|
{cmd:wald_set}{it:#}{cmd:_chi2} Wald tests for sets of independent
|
||
|
|
{cmd:wald_set}{it:#}{cmd:_df} variables
|
||
|
|
{cmd:wald_set}{it:#}{cmd:_p}
|
||
|
|
|
||
|
|
{cmd:lrtest_set}{it:#}{cmd:_chi2} LR tests for sets of independent
|
||
|
|
{cmd:lrtest_set}{it:#}{cmd:_df} variables
|
||
|
|
{cmd:lrtest_set}{it:#}{cmd:_p}
|
||
|
|
|
||
|
|
Matrices
|
||
|
|
{cmd:wald} Wald tests for individual variables
|
||
|
|
(rows: chi2, df, p)
|
||
|
|
{cmd:lrtest} LR tests for individual variables
|
||
|
|
(rows: chi2, df, p)
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{p 4 4 2}To address the rows of {cmd:e(wald)} and {cmd:e(lrtest)} in {helpb estout}'s
|
||
|
|
{cmd:cells()} option type the row names in brackets, for example, {cmd:wald[p]} or
|
||
|
|
{cmd:lrtest[chi2]}.
|
||
|
|
|
||
|
|
{marker prchange}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd prchange} [{it:varlist}] [{cmd:if} {it:exp}] [{cmd:in} {it:range}] [{cmd:,}
|
||
|
|
{cmdab:pa:ttern(}{it:typepattern}{cmd:)} {cmdab:b:inary(}{it:type}{cmd:)} {cmdab:c:ontinuous(}{it:type}{cmd:)}
|
||
|
|
[{cmd:no}]{cmdab:a:vg} {cmd:split}[{cmd:(}{it:prefix}{cmd:)}] {it:{help prchange:prchange_options}} ]
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
applies {helpb prchange} from Long and
|
||
|
|
Freese's {helpb SPost} package and adds the returned results to
|
||
|
|
{cmd:e()}. You may specify {it:prchange_options} as described in
|
||
|
|
help {helpb prchange}. In particular, the {cmd:outcome()} option may be
|
||
|
|
used with models for count, ordered, or nominal outcomes
|
||
|
|
to request results for a specific outcome. Further options are:
|
||
|
|
|
||
|
|
{p 8 12 2}{cmd:pattern(}{it:typepattern}{cmd:)}, {cmd:binary(}{it:type}{cmd:)}, and
|
||
|
|
{cmd:continuous(}{it:type}{cmd:)} to determine which types of discrete change
|
||
|
|
effects are added as the main results. The default is to add the 0 to 1
|
||
|
|
change effect for binary variables and the standard deviation change effect
|
||
|
|
for continuous variables. Use {cmd:binary(}{it:type}{cmd:)} and
|
||
|
|
{cmd:continuous(}{it:type}{cmd:)} to change these defaults. Available
|
||
|
|
types are:
|
||
|
|
|
||
|
|
{it:type} Description
|
||
|
|
{hline 48}
|
||
|
|
{cmdab:mi:nmax} minimum to maximum change effect
|
||
|
|
{cmdab:0:1} 0 to 1 change effect
|
||
|
|
{cmdab:d:elta} {cmd:delta()} change effect
|
||
|
|
{cmdab:s:d} standard deviation change effect
|
||
|
|
{cmdab:m:argefct} marginal effect (some models only)
|
||
|
|
{hline 48}
|
||
|
|
|
||
|
|
{p 12 12 2}Use {cmd:pattern(}{it:typepattern}{cmd:)} if you want to determine the
|
||
|
|
type of the added effects individually for each regressor. For example,
|
||
|
|
{bind:{cmd:pattern(minmax sd delta)}} would add {cmd:minmax} for the first regressor,
|
||
|
|
{cmd:sd} for the second, and {cmd:delta} for the third, and then proceed
|
||
|
|
using the defaults for the remaining variables.
|
||
|
|
|
||
|
|
{p 8 12 2}{cmd:avg} to request that only the average results over
|
||
|
|
all outcomes are added if applied to ordered
|
||
|
|
or nominal models ({helpb ologit}, {helpb oprobit}, {helpb slogit}, {helpb mlogit}, {helpb mprobit}). The
|
||
|
|
default is to add the average results as well as the individual results for
|
||
|
|
the different outcomes (unless {helpb prchange}'s {cmd:outcome()} option is
|
||
|
|
specified, in which case only results for the indicated outcome are
|
||
|
|
added). Furthermore, specify {cmd:noavg} to suppress the average results
|
||
|
|
and only add the outcome-specific results. {cmd:avg} cannot be combined with {cmd:split}
|
||
|
|
or {cmd:outcome()}.
|
||
|
|
|
||
|
|
{p 8 12 2}{cmd:split}[{cmd:(}{it:prefix}{cmd:)}] to save
|
||
|
|
each outcome's results in a separate estimation set if applied to ordered
|
||
|
|
or nominal models ({helpb ologit}, {helpb oprobit}, {helpb slogit}, {helpb mlogit},
|
||
|
|
{helpb mprobit}). The estimation sets are named
|
||
|
|
{it:prefix}{it:#}, where {it:#} is the value of the outcome at hand. If no
|
||
|
|
{it:prefix} is provided, the name of the estimation set followed by an
|
||
|
|
underscore is used as the prefix. If the estimation set has no name
|
||
|
|
(because it has not been stored yet) the name of the estimation command
|
||
|
|
followed by an underscore is used as the prefix (e.g. {cmd:ologit_}). The
|
||
|
|
estimation sets stored by the {cmd:split} option are intended for
|
||
|
|
tabulation only and should not be used with other post-estimation
|
||
|
|
commands.
|
||
|
|
|
||
|
|
{p 8 8 2}Depending on model and options, several of the following matrices
|
||
|
|
and scalars are added:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
Scalars
|
||
|
|
{cmd:centered} {cmd:1} if effects are centered, {cmd:0} else
|
||
|
|
{cmd:delta} Value of {cmd:delta()}
|
||
|
|
{cmd:predval}[{it:#}] Prediction(s) at the base values
|
||
|
|
{cmd:outcome} Outcome value ({cmd:outcome()}/{cmd:split} only)
|
||
|
|
|
||
|
|
Matrices
|
||
|
|
{cmd:dc} Discrete change effects (rows: main, minmax,
|
||
|
|
01, delta, sd [, margefct])
|
||
|
|
{cmd:pattern} Types of effects in the main row of {cmd:e(dc)}
|
||
|
|
{cmd:X} Base values and descriptive statistics
|
||
|
|
(rows: X, SD, Min, Max)
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{p 8 8 2}The {cmd:e(dc)} and {cmd:e(X)} matrices have multiple rows. The
|
||
|
|
{cmd:e(dc)} matrix contains the main results as determined by
|
||
|
|
{cmd:pattern()}, {cmd:binary()}, and {cmd:continuous()} in the first row.
|
||
|
|
The second and following rows contain the separate results for each type of
|
||
|
|
effect using the labels provided by {cmd:prchange} as row names. Type
|
||
|
|
{cmd:dc[}{it:#}{cmd:]} or {cmd:dc[}{it:rowname}{cmd:]} to address the rows
|
||
|
|
in {helpb estout}'s {cmd:cells()} option, where {it:#} is the row number
|
||
|
|
or {it:rowname} is the
|
||
|
|
row name. For example, type {cmd:dc[-+sd/2]} to address the centered
|
||
|
|
standard deviation change effects. To tabulate the main results (1st row),
|
||
|
|
simply type {cmd:dc}. {cmd:e(pattern)} indicates the types of effects
|
||
|
|
contained in the main row of {cmd:e(dc)} using numeric codes. The codes are 1
|
||
|
|
for the minimum to maximum change effect, 2 for the 0 to 1 change effect, 3
|
||
|
|
for the {cmd:delta()} change effect, 4 for the standard deviation change
|
||
|
|
effect, and 5 for the marginal effect. {cmd:e(X)} has four rows
|
||
|
|
containing the base values, standard deviations, minimums, and maximums. If
|
||
|
|
the {cmd:fromto} option is specified, two additional matrices,
|
||
|
|
{cmd:e(dcfrom)} and {cmd:e(dcto)} are added.
|
||
|
|
|
||
|
|
{marker prvalue}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd prvalue} [{cmd:if} {it:exp}] [{cmd:in} {it:range}] [{cmd:,} {cmdab:lab:el:(}{it:string}{cmd:)}
|
||
|
|
{it:{help prvalue:prvalue_options}} ]
|
||
|
|
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd prvalue} {cmd:post} [{it:name}] [{cmd:,} {cmdab:t:itle:(}{it:string}{cmd:)} {cmd:swap} ]
|
||
|
|
|
||
|
|
{p 8 8 2} applies {helpb prvalue} from Long and Freese's {helpb SPost}
|
||
|
|
package and adds the returned results to {cmd:e()}. The procedure is to
|
||
|
|
first collect a series of predictions by repeated calls to
|
||
|
|
{cmd:estadd prvalue} and then apply {cmd:estadd prvalue post} to prepare the results
|
||
|
|
for tabulation as in the following example:
|
||
|
|
|
||
|
|
{com}. logit lfp k5 k618 age wc hc lwg inc
|
||
|
|
. estadd prvalue, x(inc 10) label(low inc)
|
||
|
|
. estadd prvalue, x(inc 20) label(med inc)
|
||
|
|
. estadd prvalue, x(inc 30) label(high inc)
|
||
|
|
. estadd prvalue post
|
||
|
|
. estout{txt}
|
||
|
|
|
||
|
|
{p 8 8 2} You may specify {it:prvalue_options} with {cmd:estadd prvalue} as
|
||
|
|
described in help {helpb prvalue}. For example, use {cmd:x()} and
|
||
|
|
{cmd:rest()} to set the values of the independent variables. Use
|
||
|
|
{cmd:label()} to label the single calls. "pred#" is used as label if
|
||
|
|
{cmd:label()} is omitted, where # is the number of the call. Labels may
|
||
|
|
contain spaces but they will be trimmed to a maximum
|
||
|
|
length of 30 characters and some characters ({cmd::},
|
||
|
|
{cmd:.}, {cmd:"}) will be replaced by underscore. The results
|
||
|
|
from the single calls are collected in matrix {cmd:e(_estadd_prvalue)}
|
||
|
|
(predictions) and matrix {cmd:e(_estadd_prvalue_x)} (x-values). Specify
|
||
|
|
{cmd:replace} to drop results from previous calls.
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
{cmd:estadd prvalue post} posts the collected predictions in {cmd:e(b)}
|
||
|
|
so that they can be tabulated. The following results are saved:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
Scalars
|
||
|
|
{cmd:N} number of observations
|
||
|
|
|
||
|
|
Macros
|
||
|
|
{cmd:depvar} name of dependent variable
|
||
|
|
{cmd:cmd} {cmd:estadd_prvalue}
|
||
|
|
{cmd:model} model estimation command
|
||
|
|
{cmd:properties} {cmd:b}
|
||
|
|
|
||
|
|
Matrices
|
||
|
|
{cmd:b} predictions
|
||
|
|
{cmd:se} standard errors
|
||
|
|
{cmd:LB} lower confidence interval bounds
|
||
|
|
{cmd:UB} upper confidence interval bounds
|
||
|
|
{cmd:Category} outcome values
|
||
|
|
{cmd:Cond} conditional predictions (some models only)
|
||
|
|
{cmd:X} values of predictors (for each prediction)
|
||
|
|
{cmd:X2} second equation predictors (some models only)
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{p 8 8 2} {cmd:estadd prvalue post} replaces the current model unless
|
||
|
|
{it:name} is specified, in which case the results are stored under {it:name} and the model
|
||
|
|
remains active. However, if the model has a name
|
||
|
|
(because it has been stored), the name of the model is used as a prefix.
|
||
|
|
If, for example, the model has been stored as {cmd:model1}, then
|
||
|
|
{cmd:estadd prvalue post} stores its results under {cmd:model1}{it:name}.
|
||
|
|
Use {cmd:title()} to specify a title for the stored results.
|
||
|
|
|
||
|
|
{p 8 8 2}The default for {cmd:estadd prvalue post} is to arrange
|
||
|
|
{cmd:e(b)} in a way so that predictions are grouped by outcome (i.e. outcome labels are used
|
||
|
|
as equations). Alternatively, specify {cmd:swap} to group predictions by
|
||
|
|
{cmd:prvalue} calls (i.e. to use the prediction labels as equations).
|
||
|
|
|
||
|
|
{p 8 8 2}{cmd:e(X)} contains one row for each independent variable. To address the rows in
|
||
|
|
{helpb estout}'s {cmd:cells()} option type {cmd:X[}{it:varname}{cmd:]}, where {it:varname} is
|
||
|
|
the name of the variable of interest. {cmd:e(X2)}, if provided, is analogous to {cmd:e(X)}.
|
||
|
|
|
||
|
|
{marker asprvalue}
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd asprvalue} [{cmd:,} {cmdab:lab:el:(}{it:string}{cmd:)}
|
||
|
|
{it:{help asprvalue:asprvalue_options}} ]
|
||
|
|
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:estadd asprvalue} {cmd:post} [{it:name}] [{cmd:,} {cmdab:t:itle:(}{it:string}{cmd:)} {cmd:swap} ]
|
||
|
|
|
||
|
|
{p 8 8 2} applies {helpb asprvalue} from Long and Freese's {helpb SPost}
|
||
|
|
package and adds the returned results to {cmd:e()}. The procedure is to
|
||
|
|
first collect a series of predictions by repeated calls to
|
||
|
|
{cmd:estadd asprvalue} and then apply {cmd:estadd asprvalue post} to prepare the results
|
||
|
|
for tabulation as in the following example:
|
||
|
|
|
||
|
|
{com}. clogit choice train bus time invc, group(id)
|
||
|
|
. estadd asprvalue, cat(train bus) label(at means)
|
||
|
|
. estadd asprvalue, cat(train bus) rest(asmean) label(at asmeans)
|
||
|
|
. estadd asprvalue post
|
||
|
|
. estout{txt}
|
||
|
|
|
||
|
|
{p 8 8 2} You may specify {it:asprvalue_options} with {cmd:estadd asprvalue} as
|
||
|
|
described in help {helpb asprvalue}. For example, use {cmd:x()} and
|
||
|
|
{cmd:rest()} to set the values of the independent variables. Use
|
||
|
|
{cmd:label()} to label the single calls. "pred#" is used as label if
|
||
|
|
{cmd:label()} is omitted, where # is the number of the call. Labels may
|
||
|
|
contain spaces but they will be trimmed to a maximum
|
||
|
|
length of 30 characters and some characters ({cmd::},
|
||
|
|
{cmd:.}, {cmd:"}) will be replaced by underscore. The results
|
||
|
|
from the single calls are collected in matrices {cmd:e(_estadd_asprval)}
|
||
|
|
(predictions), {cmd:e(_estadd_asprval_asv)} (values of alternative-specific
|
||
|
|
variables), and {cmd:e(_estadd_asprval_csv)} (values of case-specific
|
||
|
|
variables). Specify {cmd:replace} to drop results from previous calls.
|
||
|
|
|
||
|
|
{p 8 8 2}
|
||
|
|
{cmd:estadd asprvalue post} posts the collected predictions in {cmd:e(b)}
|
||
|
|
so that they can be tabulated. The following results are saved:
|
||
|
|
|
||
|
|
{cmd:e(}{it:...}{cmd:)} Contents
|
||
|
|
{hline 60}
|
||
|
|
Scalars
|
||
|
|
{cmd:N} number of observations
|
||
|
|
|
||
|
|
Macros
|
||
|
|
{cmd:depvar} name of dependent variable
|
||
|
|
{cmd:cmd} {cmd:estadd_asprvalue}
|
||
|
|
{cmd:model} model estimation command
|
||
|
|
{cmd:properties} {cmd:b}
|
||
|
|
|
||
|
|
Matrices
|
||
|
|
{cmd:b} predictions
|
||
|
|
{cmd:asv} alternative-specific variables (if available)
|
||
|
|
{cmd:csv} case-specific variables (if available)
|
||
|
|
{hline 60}
|
||
|
|
|
||
|
|
{p 8 8 2} {cmd:estadd asprvalue post} replaces the current model unless
|
||
|
|
{it:name} is specified, in which case the results are stored under
|
||
|
|
{it:name} and the model remains active. However, if the model has a name
|
||
|
|
(because it has been stored), the name of the model is used as a prefix.
|
||
|
|
If, for example, the model has been stored as {cmd:model1}, then
|
||
|
|
{cmd:estadd asprvalue post} stores its results under {cmd:model1}{it:name}.
|
||
|
|
Use {cmd:title()} to specify a title for the stored results.
|
||
|
|
|
||
|
|
{p 8 8 2}The default for {cmd:estadd asprvalue post} is to arrange
|
||
|
|
{cmd:e(b)} in a way so that predictions are grouped by outcome (i.e. outcome labels are used
|
||
|
|
as equations). Alternatively, specify {cmd:swap} to group predictions by
|
||
|
|
{cmd:prvalue} calls (i.e. to use the prediction labels as equations).
|
||
|
|
|
||
|
|
{p 8 8 2}{cmd:e(asv)} and {cmd:e(csv)} contain one row for each variable.
|
||
|
|
To address the rows in {helpb estout}'s {cmd:cells()} option type
|
||
|
|
{cmd:asv[}{it:varname}{cmd:]} or {cmd:csv[}{it:varname}{cmd:]}, where
|
||
|
|
{it:varname} is the name of the variable of interest.
|
||
|
|
|
||
|
|
{marker options}
|
||
|
|
{title:Options}
|
||
|
|
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:replace} permits {cmd:estadd} to overwrite existing {cmd:e()}
|
||
|
|
macros, scalars, or matrices.
|
||
|
|
|
||
|
|
{p 4 8 2}
|
||
|
|
{cmd:prefix(}{it:string}{cmd:)} denotes a prefix for the names of the
|
||
|
|
added results. The default prefix is an empty string. For example, if
|
||
|
|
{cmd:prefix(}{it:string}{cmd:)} is specified, the {cmd:beta}
|
||
|
|
subcommand will return the matrix {cmd:e(}{it:string}{cmd:beta)}.
|
||
|
|
|
||
|
|
{p 4 8 2}{cmd:quietly} suppresses the output from the called subcommand and displays only
|
||
|
|
the list of added results. Note that many of {cmd:estadd}'s subcommands do not generate
|
||
|
|
output, in which case {cmd:quietly} has no effect.
|
||
|
|
|
||
|
|
{p 4 8 2}
|
||
|
|
{it:subcmdopts} are subcommand specific options. See the descriptions
|
||
|
|
of the subcommands above.
|
||
|
|
|
||
|
|
{marker examples}
|
||
|
|
{title:Examples}
|
||
|
|
|
||
|
|
{p 4 4 2}Example 1: Add {cmd:r()}-returns from other programs to the
|
||
|
|
current estimates
|
||
|
|
|
||
|
|
{com}. sysuse auto
|
||
|
|
{txt}(1978 Automobile Data)
|
||
|
|
|
||
|
|
{com}. quietly regress price mpg weight
|
||
|
|
{txt}
|
||
|
|
{com}. test mpg=weight
|
||
|
|
|
||
|
|
{txt} ( 1) {res}mpg - weight = 0
|
||
|
|
|
||
|
|
{txt} F( 1, 71) ={res} 0.36
|
||
|
|
{txt}{col 13}Prob > F ={res} 0.5514
|
||
|
|
{txt}
|
||
|
|
{com}. estadd scalar p_diff = r(p)
|
||
|
|
|
||
|
|
{txt}added scalar:
|
||
|
|
e(p_diff) = {res}.55138216
|
||
|
|
{txt}
|
||
|
|
{com}. estout, stats(p_diff)
|
||
|
|
{res}
|
||
|
|
{txt}{hline 25}
|
||
|
|
{txt} b
|
||
|
|
{txt}{hline 25}
|
||
|
|
{txt}mpg {res} -49.51222{txt}
|
||
|
|
{txt}weight {res} 1.746559{txt}
|
||
|
|
{txt}_cons {res} 1946.069{txt}
|
||
|
|
{txt}{hline 25}
|
||
|
|
{txt}p_diff {res} .5513822{txt}
|
||
|
|
{txt}{hline 25}
|
||
|
|
|
||
|
|
|
||
|
|
{p 4 4 2}Example 2: Add means and standard deviations of the model's regressors
|
||
|
|
to the current estimates
|
||
|
|
|
||
|
|
{com}. quietly logit foreign price mpg
|
||
|
|
{txt}
|
||
|
|
{com}. estadd summ, mean sd
|
||
|
|
|
||
|
|
{txt}added matrices:
|
||
|
|
e(sd) : {res}1 x 3
|
||
|
|
{txt}e(mean) : {res}1 x 3
|
||
|
|
{txt}
|
||
|
|
{com}. estout, cells("mean sd") drop(_cons)
|
||
|
|
{res}
|
||
|
|
{txt}{hline 38}
|
||
|
|
{txt} mean sd
|
||
|
|
{txt}{hline 38}
|
||
|
|
{txt}price {res} 6165.257 2949.496{txt}
|
||
|
|
{txt}mpg {res} 21.2973 5.785503{txt}
|
||
|
|
{txt}{hline 38}
|
||
|
|
|
||
|
|
|
||
|
|
{p 4 4 2}
|
||
|
|
Example 3: Add standardized beta coefficients to stored estimates
|
||
|
|
|
||
|
|
{com}. eststo: quietly regress price mpg
|
||
|
|
{txt}({res}est1{txt} stored)
|
||
|
|
|
||
|
|
{com}. eststo: quietly regress price mpg foreign
|
||
|
|
{txt}({res}est2{txt} stored)
|
||
|
|
|
||
|
|
{com}. estadd beta: *
|
||
|
|
{txt}
|
||
|
|
{com}. estout, cells(beta) drop(_cons)
|
||
|
|
{res}
|
||
|
|
{txt}{hline 38}
|
||
|
|
{txt} est1 est2
|
||
|
|
{txt} beta beta
|
||
|
|
{txt}{hline 38}
|
||
|
|
{txt}mpg {res} -.4685967 -.5770712{txt}
|
||
|
|
{txt}foreign {res} .2757378{txt}
|
||
|
|
{txt}{hline 38}
|
||
|
|
|
||
|
|
|
||
|
|
{p 4 4 2}See
|
||
|
|
{browse "http://repec.org/bocode/e/estout":http://repec.org/bocode/e/estout}
|
||
|
|
for additional examples.
|
||
|
|
|
||
|
|
|
||
|
|
{title:Writing one's own subcommands}
|
||
|
|
|
||
|
|
{p 4 4 2}
|
||
|
|
A program providing a new {cmd:estadd} subcommand should be called
|
||
|
|
{cmd:estadd_}{it:mysubcommand} (see help {helpb program} for advice
|
||
|
|
on defining programs). {it:mysubcommand} will be available to {cmd:estadd} as a new
|
||
|
|
{it:subcommand} after the program definition has been executed or
|
||
|
|
saved to a file called "estadd_{it:mysubcommand}.ado" in either the
|
||
|
|
current directory or somewhere else in the {cmd:adopath}
|
||
|
|
(see help {helpb sysdir}).
|
||
|
|
|
||
|
|
{p 4 4 2}
|
||
|
|
Use the subcommands provided within "estadd.ado" as a starting
|
||
|
|
point for writing new subcommands. See
|
||
|
|
{browse "http://repec.org/bocode/e/estout/estadd.html#estadd007":http://repec.org/bocode/e/estout/estadd.html#estadd007}
|
||
|
|
for an example.
|
||
|
|
|
||
|
|
|
||
|
|
{title:Author}
|
||
|
|
|
||
|
|
{p 4 4 2} Ben Jann, ETH Zurich, jannb@ethz.ch
|
||
|
|
|
||
|
|
|
||
|
|
{title:Also see}
|
||
|
|
|
||
|
|
Manual: {hi:[R] estimates}
|
||
|
|
|
||
|
|
{p 4 13 2}Online: help for
|
||
|
|
{helpb estimates},
|
||
|
|
{helpb ereturn},
|
||
|
|
{helpb program},
|
||
|
|
{helpb esttab},
|
||
|
|
{helpb estout},
|
||
|
|
{helpb eststo},
|
||
|
|
{helpb estpost}
|
||
|
|
{p_end}
|