help rrlogit                                  also see:  rrlogit postestimation
-------------------------------------------------------------------------------

Title

    rrlogit -- Logistic regression for randomized response data


Syntax

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

    options                     Description
    -------------------------------------------------------------------------
    Model
      pwarner(#|varname)        probability of non-negated question in
                                  Warner's model; default is pwarner(1)
      pyes(#|varname)           probability of a surrogate "yes"; default is
                                  pyes(0)
      pno(#|varname)            probability of a surrogate "no"; default is
                                  pno(0)
      noconstant                suppress constant term
      offset(varname)           include varname in model with coefficient
                                  constrained to 1
      asis                      retain perfect predictor variables
      constraints(constraints)  apply specified linear constraints

    SE/Robust
      vce(vcetype)              vcetype may be oim, robust, opg, bootstrap,
                                  or jackknife
      robust                    synonym for vce(robust)
      cluster(varname)          adjust standard errors for intragroup
                                  correlation

    Reporting
      level(#)                  set confidence level; default is level(95)
      or                        report odds ratios

    Max options
      maximize_options          control the maximization process; seldom used
    -------------------------------------------------------------------------
    depvar and indepvars may contain time-series operators; see tsvarlist.
    bootstrap, by, jackknife, rolling, statsby, stepwise, and xi are allowed;
      see prefix.
    fweights, iweights, and pweights are allowed; see weight.
    See rrlogit postestimation for features available after estimation.


Description

    rrlogit fits a maximum-likelihood logistic regression for randomized
    response data following (see, e.g., Maddala 1983:54-56). depvar=0
    indicates a negative outcome (a "no" answer); depvar!=0 & depvar<.
    (typically depvar=1) indicates a positive outcome (a "yes" answer).

    rrlogit is suited for the analysis of data from Warner's RRT scheme, the
    forced-response RRT, or the unrelated-question RRT with a known
    distribution for the non-sensitive question (see, e.g., Fox and Tracy
    1986).


Options

        +-------+
    ----+ Model +------------------------------------------------------------

    pwarner(#|varname) specifies the probability of the non-negated question
        in Warner's RRT scheme. # must be in [0,1] and may not be 0.5. The
        default is pwarner(1). Individually varying probabilities may be
        specified by pwarner(varname), where varname holds the individual
        probabilities.

        pwarner() is conditional on not being directed to the surrogate "yes"
        or "no". That is, the overall probability of the non-negated question
        is (1-pyes-pno)*pwarner.

    pyes(#|varname) specifies the probability of a surrogate "yes" answer. #
        must be in [0,1]. The default is pyes(0). Individually varying
        probabilities may be specified by pyes(varname), where varname holds
        the individual probabilities.

    pno(#|varname) specifies the probability of a surrogate "no" answer. #
        must be in [0,1]. The default is pno(0). Individually varying
        probabilities may be specified by pno(varname), where varname holds
        the individual probabilities.

        pyes() and pno() are unconditional (overall) probabilities.  For
        example, in an unrelated-question RRT where the probability to be
        directed to the non-sensitive question is 0.4 (i.e. the probability
        to answer the sensitive question is 60%) and the probability to
        answer "yes" to the non-sensitive question is known to be, say, 0.75,
        the overall probability of a surrogate "yes" is 0.4*0.75 = 0.3.
        Likewise, the overall probability of a surrogate "no" is 0.4*(1-0.75)
        = 0.1.

    noconstant, offset(varname); see estimation options.

    asis forces retention of perfect predictor variables and their associated
        perfectly predicted observations and may produce instabilities in
        maximization; see probit.

    constraints(constraints); see estimation options.

        +-----------+
    ----+ SE/Robust +--------------------------------------------------------

    vce(vcetype); see vce_option.

    robust, cluster(varname); see estimation options.

        +-----------+
    ----+ Reporting +--------------------------------------------------------

    level(#); see estimation options.

    or reports the estimated coefficients transformed to odds ratios, i.e.,
        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.

        +-------------+
    ----+ Max options +------------------------------------------------------

    maximize_options:  difficult, technique(algorithm_spec), iterate(#),
        [no]log, trace, hessian, gradient, showstep, tolerance(#),
        ltolerance(#), gtolerance(#), nrtolerance(#), nonrtolerance,
        from(init_specs); see maximize.  These options are seldom used.


Examples

        . rrlogit infidelity male age, pyes(0.5)


References

    Fox, James Alan, and Paul E. Tracy. 1986. Randomized response: A method
        for sensitive surveys. London: Sage.

    Maddala, G. S. 1983. Limited Dependent and Qualitative Variables in
        Econometrics. Cambridge: Cambridge University Press.


Author

    Ben Jann, Institute of Sociology, University of Bern, jann@soz.unibe.ch


Also see

    Online:  rrlogit postestimation;
             constraint, logistic, logit, rrreg (if installed)