-------------------------------------------------------------------------------
help for reformat                                         (author:  Tony Brady)
-------------------------------------------------------------------------------

Reformat regression output

        reformat [varlist] [, output([e][s][z][p][c][n]) cw(#) nocons lrtest
                 noisily eform sd iqr dpcoef(#) dpp(#) nfmt(%fmt) nobrackets
                 to(string) delimit(string) sort prefix(string)]


Description

The output from the last regression command is re-displayed in a more readable
format using variable and value labels for clarity. The columns to be displayed
can be controlled by the user and extra options to show the number of
observations or likelihood ratio P-value associated with each covariate is
provided. The command is particularly suited to regression output containing
dummy variables and interaction terms created by xi.

The reformatted output may also be copied into a spreadsheet or word-processor
to create near-publication quality tables. The best way to do this is using the
delimit(). Then copy and paste the output into a word processor and use a
`convert text to table' option in your word processor.

By default all terms fitted in the regression model are re-displayed, although
this can be restricted by specifying varlist. Auxillary parameters, such as the
second constant from nbreg or the cut points from ologit, are omitted.

reformat responds to two new variable characteristics (see char): [units] and
[mult]. The units characteristic is used to describe the measurement units of
continuous variables such as:

        . char age[units] years
        . char sbp[units] mmHg

The mult characteristic determines the unit multiplier for reporting the effect
size of a continuous variable. For instance:

        . char age[mult] 10

would request effects for age to be reported per decade.


Options

output(options) describes the columns to be displayed where options is one or
    more of:

        e     estimated coefficient
        s     standard error
        z     Z-value (or t-value if appropriate)
        p     P-value
        c     confidence interval
        n     number of observations

    Columns will be displayed in the order you specify.

cw(#) is the coefficient width. This is the number of characters allocated to
    describing the coefficients (22 by default). You may need to increase this
    value if you have attached long value labels to variables that appear in
    the model.

nocons suppresses the constant term (_cons).

lrtest replaces the usual Z-test P-values with likelihood ratio test P-values
    for each term (or group of related xi terms in the case of categorical
    variables) in the model. Note this option may take some time to process
    while the various models are being fitted. noisily displays the raw results
    of the likelihood ratio tests as they are produced.

eform reports the coefficients in exponentiated form. Useful after logit to
    show odds ratios and poisson to show incidence rate ratios.

sd and iqr report regression coefficients for continuous variables per standard
    deviation or interquartile range respectively. Useful when the variable has
    a large range of values so that the regression coefficient per unit is very
    small. These options have no effect on variables that have their [mult]
    characteristic set.

dpcoef(#) specifies the number of decimal places (3 by default) to use when
    reporting the coefficients, standard errors and CIs.

dpp(#) specifies the number of decimal places (3 by default) to use when
    reporting the z values and p-values.

nfmt(%fmt) alters the formatting applied to the number of observations. In
    particular the comma format %7.0fc might be of interest.

nobrackets suppresses the brackets placed around the CI estimates.

to(string) specifies the text to use between the lower CI and upper CI ("to" by
    default). Use no to suppress this text completely.

delimit(string) causes the output to be presented with the specified string
    between the columns instead of spacing. Useful when the output is to be
    copied into a word-processor and converted into a table.

sort re-arranges the variable list into ascending alphabetical order.  Useful
    after stepwise regression or when the same baseline variable is involved in
    more than one interaction. In these situations the variable list can become
    scrambled leading to unclear output.

prefix(string) should be used if you used the prefix() option in your xi
    command. By default reformat assumes your categorical variables are
    prefixed with _I or I (dependent on Stata version).


Examples

        . reformat
        . reformat, output(necp) nfmt(%7.0fc) lrtest
        . reformat, eform to(-) delim(;) dpcoef(2) dpp(2)

        . xi, prefix(_S): logistic resp i.gender i.ihd age fev1
        . reformat, prefix(_S)


Author

        Tony Brady, Sealed Envelope Ltd, U.K.
        tony@sealedenvelope.com


Also see

 Manual:  [U] 26 Estimation and post-estimation commands,
          [R] xi