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help for ^prchange^ - 1.6.5. - 2/24/01
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Discrete and marginal change for regression models for categorical and
count variables
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    ^prchange^ [varlist] [^if^ exp] [^in^ range] [, ^x(^variables_and_values^)^
        ^r^est^(^stat^)^ ^o^utcome^(^#^)^ ^f^romto ^b^rief ^noba^se ^nola^bel ^h^elp
        ^all^ ^unc^entered ^d^elta^(^#^)^ ]

where

    ^variables_and_values^ is an alternating list of variables and either
        numeric values or mean, median, min, max, upper, lower, previous

    ^stat^ is either mean, median, min, max, upper, lower, previous, grmean
        (group mean), grmedian, grmin, grmax

Description
-----------

^prchange^ computes discrete and marginal change for regression models for
categorical and count variables.  Marginal change is the partial derivative
of the predicted probability or predicted rate with respect to the
independent variables. Discrete change is the difference in the predicted
value as one independent variable changes values while all others are held
constant at specified values.

By default, the discrete and marginal change is calculated holding all other
variables at their mean.  Values for specific independent variables can be
set using the x() option after ^prchange^.  For example, to compute predicted
values when educ is 10 and age is 30, type ^prchange, x(educ=10 age=30)^.
Values for the unspecified independent variables can be set using the rest()
option, e.g., ^prchange, x(educ=10 age=30) rest(mean)^.  The ^if^ and ^in^
conditions specify conditions for computation of means, min, etc., that are
used with rest().

The discrete change is computed when a variable changes from its minimum to
its maximum (Min->Max), from 0 to 1 (0->1), from its specified value minus
.5 units to its specified value plus .5 (-+1/2), and from its specified
value minus .5 standard deviations to its value plus .5 standard deviations
(-+sd/2).

^prchange^ works with cloglog, cnreg, gologit, intreg, logistic, logit,
mlogit, nbreg, ologit, oprobit, poisson, probit, regress, tobit, zinb, and
zip.


Options
-------

^x()^ explicitly sets the values of specified independent variables.

^rest()^ sets the independent variables not specified in x() to their ^mean^
    (default), ^minimum^, ^maximum^, ^median^ when calculating predicted values.
    ^grmean^ sets these independent variables to the mean conditional on the
    variables and values specified in x().  If ^prvalue^ has already been run
    after the last estimate, ^previous^ will set unspecified variables to their
    prior values.  For models other than mlogit, ^upper^ and ^lower^ can be used
    to set independent variables to their minimum or maximum depending on
    which will yield the upper or lower extreme predicted value.

^outcome()^ specifies that changes will be printed only for the outcome
    indicated. For ^ologit^, ^oprobit^ and ^mlogit^, the default is to provide
    results for all outcomes. For the count models, the default is to
    present results with respect to the predicted rate; specifying an
    outcome number will provide changes in the probability of that outcome.

^delta()^ specifies the amount of the discrete change in the independent
    variable.  The default is a 1 unit change.

^fromto^ includes the pre- and post- probabilities in addition to the discrete
    change

^uncentered^ specifies that the uncentered discrete change rather than the
    centered discrete change is to be computed.

^all^ specifies that any calculations of means, medians, etc., should use
    the entire sample instead of the sample used to estimate the model.

^help^ presents guide to interpreting headings of output.

^nolabel^ uses values rather than value labels in output.

^nobase^ suppresses inclusion of the base values of x in the output.

^brief^ prints only limited output.

Examples
--------

To compute discrete and marginal change for ordered probit at base values
equal to the mean:

 . ^oprobit warm yr89 male white age ed prst^
 . ^prchange^

To compute discrete and marginal change for a specific set of base values:

 . ^prchange, x(male=1 white=1 age=30)^

 . ^prchange, x(male=1 white=1 age=30) rest(median)^

 . ^prchange, x(male=1 white=max age=min) rest(median)^

To compute the discrete change for a set of base values while holding other
variables constant to a group-specific median:

 . ^prchange if white == 1 & male == 0, x(white=1 male=0) rest(median)^

or

 . ^prchange, x(white=1 male=0) rest(grmedian)^


To list only the discrete change for specific variables:

 . ^prchange age, x(male=0 white=0) rest(median)^

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Authors: J. Scott Long and Jeremy Freese
         www.indiana.edu/~jslsoc/spost.htm
         spostsup@@indiana.edu
         
         
