help asroprobit postestimation dialogs: predict estat
also see: asroprobit
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Title
[R] asroprobit postestimation -- Postestimation tools for asroprobit
Description
The following postestimation commands are of special interest after
asroprobit:
command description
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estat alternatives alternative summary statistics
estat covariance variance-covariance matrix of the alternatives
estat correlation correlation matrix of the alternatives
estat facweights covariance factor weights matrix
estat mfx marginal effects
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The following standard postestimation commands are also available:
command description
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estat AIC, BIC, VCE, and estimation sample summary
estimates cataloging estimation results
lincom point estimates, standard errors, testing, and inference for
linear combinations of coefficients
lrtest likelihood-ratio test
nlcom point estimates, standard errors, testing, and inference for
nonlinear combinations of coefficients
predict predicted probabilities, estimated linear predictor and its
standard error
predictnl point estimates, standard errors, testing, and inference for
generalized predictions
test Wald tests of simple and composite linear hypotheses
testnl Wald tests of nonlinear hypotheses
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Special-interest postestimation commands
estat alternatives displays summary statistics about the alternatives in
the estimation sample. The command also provides a mapping between the
index numbers that label the covariance parameters of the model and their
associated values and labels for the alternative variable.
estat covariance computes the estimated variance-covariance matrix for
the alternatives. The estimates are displayed, and the
variance-covariance matrix is stored in r(cov).
estat correlation computes the estimated correlation matrix for the
alternatives. The estimates are displayed, and the correlation matrix is
stored in r(cor).
estat facweights displays the covariance factor weights matrix and stores
it in r(C).
estat mfx computes the marginal effects of a simulated probability of a
set of ranked alternatives. The probability is stored in r(pr), the
matrix of rankings is stored in r(ranks), and the matrix of
marginal-effect statistics is stored in r(mfx).
Syntax for predict
predict [type] newvar [if] [in] [, statistic altwise]
predict [type] {stub*|newvarlist} [if] [in] , scores
statistic description
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Main
pr probability of each ranking, by case; the default
pr1 probability that each alternative is preferred
xb linear prediction
stdp standard error of the linear prediction
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These statistics are available both in and out of sample; type predict
... if e(sample) ... if wanted only for the estimation sample.
Menu
Statistics > Postestimation > Predictions, residuals, etc.
Options for predict
+------+
----+ Main +-------------------------------------------------------------
pr, the default, calculates the probability of each ranking. For each
case, one probability is computed for the ranks in e(depvar).
pr1 calculates the probability that each alternative is preferred.
xb calculates the linear prediction for each alternative.
stdp calculates the standard error of the linear predictor.
altwise specifies that alternative-wise deletion be used when marking out
observations due to missing values in your variables. The default is
to use casewise deletion. The xb and stdp options always use
alternative-wise deletion.
scores calculates the scores for each coefficient in e(b). This option
requires a new variable list of length equal to the number of columns
in e(b). Otherwise, use the stub* option to have predict generate
enumerated variables with prefix stub.
Syntax for estat alternatives
estat alternatives
Menu
Statistics > Postestimation > Reports and statistics
Syntax for estat covariance
estat covariance [, format(string) border(string) left(#)]
Menu
Statistics > Postestimation > Reports and statistics
Options for estat covariance
format(string) sets the matrix display format. The default is
format(%9.0g).
border(string) sets the matrix display border style. The default is
border(all). See [P] matlist.
left(#) sets the matrix display left indent. The default is left(2).
See [P] matlist.
Syntax for estat correlation
estat correlation [, format(string) border(string) left(#)]
Menu
Statistics > Postestimation > Reports and statistics
Options for estat correlation
format(string) sets the matrix display format. The default is
format(%9.4f).
border(string) sets the matrix display border style. The default is
border(all). See [P] matlist.
left(#) sets the matrix display left indent. The default is left(2).
See [P] matlist.
Syntax for estat facweights
estat facweights [, format(string) border(string) left(#)]
Menu
Statistics > Postestimation > Reports and statistics
Options for estat facweights
format(string) sets the matrix display format. The default is
format(%9.0f).
border(string) sets the matrix display border style. The default is
border(all). See [P] matlist.
left(#) sets the matrix display left indent. The default is left(2).
See [P] matlist.
Syntax for estat mfx
estat mfx [if] [in] [, options]
options description
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Main
varlist(varlist) display marginal effects for varlist
at(median [atlist]) calculate marginal effects at these values
rank(ranklist) calculate marginal effects for the simulated
probability of these ranked alternatives
Options
level(#) set confidence interval level; default is
level(95)
nodiscrete treat indicator variables as continuous
noesample do not restrict calculation of the medians to
the estimation sample
nowght ignore weights when calculating medians
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Menu
Statistics > Postestimation > Reports and statistics
Options for estat mfx
+------+
----+ Main +-------------------------------------------------------------
varlist(varlist) specifies the variables for which to display marginal
effects. The default is all variables.
at(median [[alternative:variable = #] [variable = #] [...]]) specifies
the values at which the marginal effects are to be calculated. The
default is to compute the marginal effects at the medians of the
independent variables by using the estimation sample, at(median).
You can also specify specific values for variables. Values for
alternative-specific variables can be specified by alternative, or
you can specify one value for all alternatives. You can specify only
one value for case-specific variables. For example, in the wlsrank
dataset, female and score are case-specific variables, whereas high
and low are alternative-specific variables. The following would be a
legal syntax for estat mfx:
. estat mfx, at(median high=0 esteem:high=1 low=0 security:low=1
female=1)
When nodiscrete is not specified, at(median [atlist]) has no effect
on computing marginal effects for indicator variables, which are
calculated as the discrete change in the simulated probability as the
indicator variable changes from 0 to 1.
The median computations respect any if or in qualifiers, so you can
restrict the data over which the medians are computed. You can even
restrict the values to a specific case, e.g.,
. estat mfx if case==13
rank(alternative = # alternative = # [...]) specifies the ranks for the
alternatives. The default is to rank the calculated latent
variables. Alternatives excluded from rank() are omitted from the
analysis. You must therefore specify at least two alternatives in
rank(). You may have tied ranks in the rank specification. Only the
order in the ranks is relevant.
+---------+
----+ Options +----------------------------------------------------------
level(#) sets the confidence level; default is level(95).
nodiscrete specifies that indicator variables be treated as continuous
variables. An indicator variable is one that takes on the value 0 or
1 in the estimation sample. By default, the discrete change in the
simulated probability is computed as the indicator variable changes
from 0 to 1.
noesample specifies that the whole dataset be considered instead of only
those marked in the e(sample) defined by the asroprobit command.
nowght specifies that weights be ignored when calculating the medians.
Examples
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Setup
. webuse travel
Fit alternative-specific rank-ordered probit model
. asroprobit choice travelcost termtime, casevars(income) case(id)
alternatives(mode)
Obtain correlation matrix of the alternatives
. estat correlation
Obtain variance-covariance matrix of the alternatives
. estat covariance
Calculate probability alternative is chosen
. predict p
Calculate marginal effects for the case-specific variable income and the
alternative-specific variables termtime and travelcost
. estat mfx, at(air: termtime=50 travelcost=100 income=60)
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Setup
. webuse travel, clear
Fit alternative-specific rank-ordered probit model
. asroprobit choice travelcost termtime, casevars(income) case(id)
alternatives(mode)
Store estimation results
. estimates store unstructured
Fit second alternative-specific rank-ordered probit model
. asroprobit choice travelcost termtime, casevars(income) case(id)
alternatives(mode) correlation(independent)
Perform likelihood-ratio test to compare models
. lrtest unstructured.
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Saved results
estat mfx saves the following in r():
Scalars
r(pr) scalar containing the computed probability of the ranked
alternatives.
Matrices
r(ranks) column vector containing the alternative ranks. The
rownames of e(ranks) identifies the alternatives.
r(mfx) matrix containing the computed marginal effects and associated
statistics. Column 1 of the matrix contains the marginal
effects; column 2, their standard errors; column 3, their z
statistics; and columns 4 and 5, the confidence intervals.
Column 6 contains the values of the independent variables used to
compute the probabilities r(pr).
Also see
Manual: [R] asroprobit postestimation
Help: [R] asroprobit, [R] asmprobit
