help for fmlogit postestimation

Title

fmlogit postestimation -- Postestimation tools for
fmlogit

Description

The following standard postestimation commands are also available:

command description

predict predictions

For older versions of Stata (< 11):

dfmlogit displays discrete changes and
marginal effects after fmlogit. For more recent versions of Stata use margins
instead.

Syntax for predict

predict [type] newvar [if] [in]
[, statistic
outcome(varname)
equation(eqno)
]

statistic

xb xb, the linear predictor

stdp standard error of the prediction

pr proportion

score first derivative of the log likelihood with respect
to the linear predictor.

Options for predict

outcome(varname) specifies the outcome. This option may only be used
with the pr option.

equation(#) specifies the equation, as in predict. This option
may only be used with the xb, stdp, and score options.

dfmlogitit: displaying discrete changes and marginal effects from fmlogit output for Stata version < 11

Syntax

dfmlogit
[,
at(variables_and_values)
]

Description

dfmlogit displays the change in predicted dependent variable
for three types of discrete changes in explanatory variable and the marginal
effects:

Discrete Changes

Min --> Max shows the change in predicted dependent variable
when the explanatory variable changes from its minimum value to its maximum
value, while keeping all other explanatory variables at their specified
values (by default the mean). This is the only effect shown for dummy
variables (variables with only two distinct values).

+-SD/2 shows the change in predicted dependent variable when the
explanatory variable moves from half a standard deviation below its specified
value (by default the mean) to half a standard deviation above its specified
value, while keeping all other variables at their specified values. In other
words: It shows the effect of a standard deviation change in explanatory
variable, centered around the specified value, on the predicted dependent
variable.

+-1/2 shows the change in predicted dependent variable when the
explanatory variable moves from half a unit below its specified value to half
a unit above its specified value, while keeping all other variables at their
specified values. In other words: It shows the effect of a unit change in
explanatory variable, centered around the specified value, on the predicted
dependent variable.

Marginal Effects

MFX at x shows the marginal effect of each (non dummy) variable,
while keeping all variables at their specified values. The marginal effect is
the change in predicted dependent variable for a unit change in the explanatory
variable, assuming that the effect doesn't change over that interval.

Options

at(variables_and_values) allow the user to specify at
which values of the explanatory variables the effects are calculated.
variables_and_values is an alternating list of variables and either numeric
values or mean, median, min, max, p1, p5, p10 p25, p50, p75, p90, p95, p99. The
default is mean for all variables. The statistics p1, p5, ..., p99, are the 1st,
5th, ..., 99th percentile.

Examples

use http://fmwww.bc.edu/repec/bocode/c/citybudget.dta, clear

fmlogit governing safety education recreation social urbanplanning, ///
eta(minorityleft noleft houseval popdens)

dfmlogit, at(minorityleft 0 noleft 0 )

Also see

Online: help for fmlogit, estimates, lincom,
lrtest, margins, nlcom, predictnl,
suest, test, testnl