intreg_postestimation.hlp

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{smcl}
{* 25mar2005}{...}
{cmd:help intreg postestimation}{right:dialog:  {bf:{dialog intreg_p:predict}}}
{right:also see:  {helpb intreg}{space 1}}
{hline}

{title:Title}

{p2colset 5 34 36 2}{...}
{p2col :{hi:[R] intreg postestimation} {hline 2}}Postestimation tools for
intreg{p_end}
{p2colreset}{...}


{title:Description}

{pstd}
The following postestimation commands are available for {opt intreg}:

{synoptset 13 tabbed}{...}
{p2coldent :command}description{p_end}
{synoptline}
INCLUDE help post_adjust1star
INCLUDE help post_estat
INCLUDE help post_estimates
INCLUDE help post_lincom
INCLUDE help post_lrtest
INCLUDE help post_mfx
INCLUDE help post_nlcom
{synopt :{helpb intreg postestimation##predict:predict}}predictions, residuals, influence statistics, and other diagnostic measures{p_end}
INCLUDE help post_predictnl
INCLUDE help post_suest
INCLUDE help post_test
INCLUDE help post_testnl
{synoptline}
{p2colreset}{...}
{p 4 6 2}* {cmd:adjust} does not work with time-series operators.


{marker predict}{...}
{title:Syntax for predict}

{p 8 16 2}
{cmd:predict}
{dtype}
{newvar}
{ifin}
[{cmd:,} {it:statistic} {opt nooff:set}]

{p 8 16 2}
{cmd:predict}
{dtype}
{c -(}{it:stub*}{c |}{it:newvar_reg} {it:newvar_lnsigma}{c )-}
{ifin}
{cmd:,}
{opt sc:ores}

{synoptset 14 tabbed}{...}
{synopthdr :statistic}
{synoptline}
{syntab :Main}
{synopt :{opt xb}}xb, fitted values (the default){p_end}
INCLUDE help regstats
{synoptline}
{p2colreset}{...}
INCLUDE help esample

INCLUDE help whereab


{title:Options for predict}

{phang}
{opt xb}, the default, calculates the linear prediction.

{phang}
{opt pr(a,b)} calculates the
{bind:Pr({it:a} < xb + u < {it:b})}, the probability that y|x would be observed
in the interval ({it:a},{it:b}).

{pmore}
{it:a} and {it:b} may be specified as numbers or variable names;{break}
{cmd:pr(20,30)} calculates {bind:Pr(20 < xb + u < 30)};{break}
{cmd:pr(lb,ub)} calculates {bind:Pr(lb < xb + u < ub)}; and{break}
{cmd:pr(20,ub)} calculates {bind:Pr(20 < xb + u < ub)}.

{pmore}
{it:a} missing {bind:({it:a} {ul:>} .)} means minus infinity;
{cmd:pr(.,30)} calculates {bind:Pr(xb + u < 30)} and
{cmd:pr(lb,30)} calculates {bind:Pr(xb + u < 30)} in observations for which
{bind:lb {ul:>} .} (and calculates {bind:Pr(lb < xb + u < 30)} elsewhere).

{pmore}
{it:b} missing {bind:({it:b} {ul:>} .)} means plus infinity;
{cmd:pr(20,.)} calculates {bind:Pr(xb + u > 20)} and
{cmd:pr(20,ub)} calculates {bind:Pr(xb + u > 20)} in observations for which
{bind:ub {ul:>} .} (and calculates {bind:Pr(20 < xb + u < ub)} elsewhere).

{phang}
{opt e(a,b)} calculates
{bind:E(xb + u | {it:a} < xb + u < {it:b})}, the expected value of y|x
conditional on y|x being in the interval ({it:a},{it:b}), meaning that y|x is
censored.  {it:a} and {it:b} are specified as they are for {cmd:pr()}.

{phang}
{opt ystar(a,b)} calculates E(y*),
where {bind:y* = {it:a}} if {bind:xb + u {ul:<} {it:a}}, {bind:y* = {it:b}} if
{bind:xb + u {ul:>} {it:b}}, and {bind:y* = xb + u} otherwise, meaning that
y* is truncated.  {it:a} and {it:b} are specified as they are for
{cmd:pr()}.

{phang}
{opt stdp} calculates the standard error of the prediction, which can be
thought of as the standard error of the predicted expected value or mean for
the observation's covariate pattern.  This is also referred to as the standard
error of the fitted value.

{phang}
{opt stdf} calculates the standard error of the forecast, which is the
standard error of the point prediction for a single observation.  It is
commonly referred to as the standard error of the future or forecast value.
By construction, the standard errors produced by {opt stdf} are always larger
than those produced by {opt stdp}.

{phang}
{opt nooffset} is relevant only if you specified {opth offset(varname)}.  It
modifies the calculations made by {cmd:predict} so that they ignore the
offset variable; the linear prediction is treated as xb rather than xb +
offset.

{phang}
{opt scores} calculates equation-level score variables.{break}

{pmore}
The first new variable will contain the derivative of the log likelihood with
respect to the regression equation.

{pmore}
The second new variable will contain the derivative of the log likelihood with
respect to the scale equation ({hi:lnsigma}).


{title:Examples}

{phang}{cmd:. intreg inclow inchigh age gender exp expsq}{p_end}
{phang}{cmd:. predict lowwage, pr(., 20000)}{p_end}
{phang}{cmd:. predict expwage, e(inclow, inchigh)}{p_end}


{title:Also see}

{psee}
Manual:  {bf:[R] intreg postestimation}

{psee}
Online:  {helpb intreg};{break}
{helpb adjust},
{helpb lincom},
{helpb lrtest},
{helpb mfx},
{helpb nlcom},
{helpb predictnl},
{helpb suest},
{helpb test},
{helpb testnl}
{p_end}