{smcl}
{* 15jan2003}{...}
{hline}
help for {hi:mvppred}{right:Cappellari and Jenkins (31oct2002)}
{hline}
{title:Predictions from multivariate probit models estimated by SML}
{p 4 12}{cmd:mvppred} {it:newvarname_prefix} [{cmd:if} {it:exp}]
[{cmd:in} {it:range}] [{cmd:,} {it:statistic}]
where {it:statistic} is one of
{p 4 12}{cmdab:xb}{space 5}the linear prediction for each equation;
the default.{p_end}
{p 4 12}{cmdab:stdp}{space 3}the standard error of the linear
predictions for each equation.{p_end}
{p 4 12}{cmdab:pm:arg}{space 2}the marginal success probability for
each equation.{p_end}
{p 4 12}{cmdab:pa:ll}{space 3}the joint probabilities:
(i) Pr(depvar_{it:i} = 1, all {it:i}) and (ii) Pr(depvar_{it:i} = 0,
all {it:i}), for equations {it:i} = 1,...,{it:M}.{p_end}
{p}These statistics are available both in and out of sample; type
"{cmd:predict} {it:...} {cmd:if e(sample)} {it:...}" if wanted only for the
estimation sample. If no statistic is specified, the default is {cmdab:xb}.
{title:Description}
{p}{cmd:mvppred} provides predictions following estimation of an
{it:M}-equation probit model by the method of simulated maximum
likelihood (SML) using the program {cmd:mvp7}. See {help mvp7}.
Predictions provided for each equation are the fitted index values,
the standard errors of the fitted index values for each equation, the
predicted marginal success probabilities, and two predicted joint
probabilities. These are: (i) Pr(depvar_{it:i} = 1, all {it:i}) and
(ii) Pr(depvar_{it:i} = 0, all {it:i}), for equations {it:i} =
1,...,{it:M}. (Additional joint probabilities and conditional
probabilities have not been provided because the number of such
probabilities increases substantially as {it:M} increases.) The
multivariate normal distributions used to calculate the joint
probabilities are derived by simulation using the GHK simulator,
with the seed and number of random draws the same as used by {cmd:mvp7}
to derive the parameter estimates.
{title:Options}
{p 0 4}{cmd:xb}, the default, calculates the linear prediction (Xb) for
each equation. Results are stored in the variables {it:newvarname_prefixi},
for equations {it:i} = 1,...,{it:M}.
{p 0 4}{cmd:stdp} calculates the standard error of the linear prediction
(Xb) for each equation. Results are stored in the variables
{it:newvarname_prefixi}, for equations {it:i} = 1,...,{it:M}.
{p 0 4}{cmd:pmarg} calculates the marginal probit predicted probability
of success for each outcome, Pr(depvar{it:i}) = 1, for each equation
{it:i} = 1,...,{it:M}. Results are stored in the variables
{it:newvarname_prefixi}, for equations {it:i} = 1,...,{it:M}.
{p 0 4}{cmd:pall} calculates (i) the probit predicted joint probability of
success in every outcome, Pr(depvar{it:i}) = 1, for all {it:i} = 1,...,{it:M},
and (ii) the probit joint probability of failure in every outcome,
Pr(depvar{it:i}) = 0, for all {it:i} = 1,...,{it:M}. Results are stored in
the variables {it:newvarname_prefix1s} for predicted probability (i) and
{it:newvarname_prefix0s} for predicted probability (ii).
{title:Examples}
{p 8 12}{inp:. use http://www.stata-press.com/data/r7/school.dta, clear}
{p 8 12}{inp:. mvp7 (private = years logptax loginc) (vote = years logptax loginc) }
{p 8 12}{inp:. mvppred xb}
{p 8 12}{inp:. mvppred pall, pall}
{p 8 12}{inp:. mvppred pmarg, pmarg}
{p 8 12}{inp:. mvppred stdp, stdp}
{p 8 12}{inp:. sum xb1, xb2, pmarg1, pmarg2, stdp1, stdp2, pall1s pall0s}
{title:Authors}
{p 4 4}Lorenzo Cappellari, Universita del Piemonte-Orientale, Italy{break}
{p 4 4}Stephen P. Jenkins, ISER, University of Essex, U.K.{break}
{title:Also see}
{p 1 14}Manual: {hi:[U] 23 Estimation and post-estimation commands},{p_end}
{p 10 14}{hi:[U] 29 Overview of model estimation in Stata},{p_end}
{p 0 19}On-line: help for {help mvp7}, {help postest}, and
{help predict}.{p_end}