help riflogithttp://github.com/benjann/riflogit/

Title

riflogit -- Unconditional logistic regression

Syntax

riflogit depvar [indepvars] [if] [in] [weight]
[,
options
]

predict [type] newvar [if] [in]
[,
predict_options
]

options

Main
noconstant suppress constant term

hascons has user-supplied constant

SE/Robust
vce(vcetype) vcetype may be
ols, robust, cluster clustvar,
bootstrap, jackknife, hc2, or hc3

Reporting
level(#) set confidence level; default is level(95)

or report odds ratios

noheader suppress table header

notable suppress table of results

display_options standard display option

coeflegend display legend instead of statistics

indepvars may contain factor variables; see fvvarlist.

svy and mi are allowed; see prefix.

pweights, fweights, and iweights are allowed; see help
weight.

predict_options

Main
xb linear prediction; the default

stdp standard error of the linear prediction

residuals residuals

* rif recentered influence function

score score

Options
nolabel do not label the newly created variable

Unstarred statistics are available both in and out of sample.

Description

riflogit fits an unconditional logistic regression by applying
least-squares estimation to the RIF (recentered influence function) of
the marginal log odds of a positive outcome. depvar equal to nonzero
and nonmissing (typically depvar equal to one) indicates a positive
outcome, whereas depvar equal to zero indicates a negative outcome. The
exponents of the coefficients have an (approximate) marginal odds ratio
interpretation. See Firpo et al. (2009)
for methodological background on RIF regression. For details on
unconditional logistic regression and marginal odds ratios see
Jann and Karlson (2023).

Options

noconstant suppresses the constant term (intercept) in the model.

hascons indicates that a user-defined constant or its equivalent is
specified among the independent variables in indepvars. See regress
for further explanations.

vce(vcetype) specifies the type of standard error reported,
which includes types that are derived from asymptotic theory
(ols), that are robust to some kinds of misspecification
(robust), that allow for intragroup correlation (cluster clustvar),
and that use bootstrap or jackknife methods (bootstrap,
jackknife); see vce_option. Allowed are also hc2 and hc3
which provide alternative bias corrections for the robust variance calculation; see
regress.

The default is vce(robust), unless iweights are specified, in which
case the default is vce(ols).

level(#) specifies the confidence level, as a percentage, for
confidence intervals. The default is level(95) or as
set by set level.

or reports the estimated coefficients transformed to odds ratios,
that is, exp(b) rather than b. Standard errors and confidence intervals are
similarly transformed. This option affects how results are displayed, not
how they are estimated. or may be specified at estimation or when
replaying previously estimated results. When applying multiple imputation,
specify or as option to mi estimate, not as option to
riflogit.

noheader suppresses the display of the table header.

notable suppresses the display of the table of results.

display_options are usual display options as documented in
[R] Estimation options.

coeflegend specifies that the legend of the coefficients and how to
specify them in an expression be displayed rather
than displaying the statistics for the coefficients.

Examples

. webuse lbw
. logit low i.smoke age lwt i.race ptl ht ui, or vce(robust)
. riflogit low i.smoke age lwt i.race ptl ht ui, or vce(robust)

Stored results

See regress for information on stored results. riflogit
updates macros e(cmd), e(predict), and e(title), and
removes macro e(estat_cmd).

References

Firpo, Sergio, Nicole M. Fortin, Thomas Lemieux. 2009. Unconditional
Quantile Regressions. Econometrica
77(3):953–973. DOI: 10.3982/ECTA6822

Jann, Ben, Kristian Bernt Karlson. 2023. Estimation of marginal odds ratios. University
of Bern Social Sciences Working Papers 44. Available from
https://ideas.repec.org/p/bss/wpaper/44.html.

Author

Ben Jann, University of Bern, ben.jann@unibe.ch

Thanks for citing this software as follows:

Jann, B. (2022). riflogit: Stata module to fit unconditional logistic regression. Available from
http://github.com/benjann/riflogit/.

Also see

Online: help for
regress, logit, ipwlogit (if installed),
lnmor (if installed)