能用什么命令，你看帮助。下面是logit回归完以后可以用的命令
没有你写的那个，当然不能执行了


Title

    [R] logit postestimation -- Postestimation tools for logit


Description

    The following postestimation commands are of special interest after logit:

    Command               Description
    ---------------------------------------------------------------------------------------------------------------------
    estat classification  report various summary statistics, including the classification table
    estat gof             Pearson or Hosmer-Lemeshow goodness-of-fit test
    lroc                  compute area under ROC curve and graph the curve
    lsens                 graph sensitivity and specificity versus probability cutoff
    ---------------------------------------------------------------------------------------------------------------------
    These commands are not appropriate after the svy prefix.

    The following standard postestimation commands are also available:

    Command           Description
    ---------------------------------------------------------------------------------------------------------------------
        contrast      contrasts and ANOVA-style joint tests of estimates
        estat         AIC, BIC, VCE, and estimation sample summary
        estat (svy)   postestimation statistics for survey data
        estimates     cataloging estimation results
        lincom        point estimates, standard errors, testing, and inference for linear combinations of coefficients
        linktest      link test for model specification
    (1) lrtest        likelihood-ratio test
        margins       marginal means, predictive margins, marginal effects, and average marginal effects
        marginsplot   graph the results from margins (profile plots, interaction plots, etc.)
        nlcom         point estimates, standard errors, testing, and inference for nonlinear combinations of coefficients
        predict       predictions, residuals, influence statistics, and other diagnostic measures
        predictnl     point estimates, standard errors, testing, and inference for generalized predictions
        pwcompare     pairwise comparisons of estimates
        suest         seemingly unrelated estimation
        test          Wald tests of simple and composite linear hypotheses
        testnl        Wald tests of nonlinear hypotheses
    ---------------------------------------------------------------------------------------------------------------------
    (1) lrtest is not appropriate with svy estimation results.


Syntax for predict

        predict [type] newvar [if] [in] [, statistic nooffset rules asif]

    statistic       Description
    ---------------------------------------------------------------------------------------------------------------------
    Main
      pr            probability of a positive outcome; the default
      xb            linear prediction
      stdp          standard error of the prediction
    * dbeta         Pregibon (1981) Delta-Beta influence statistic
    * deviance      deviance residual
    * dx2           Hosmer and Lemeshow (2000) Delta chi-squared influence statistic
    * ddeviance     Hosmer and Lemeshow (2000) Delta-D influence statistic
    * hat           Pregibon (1981) leverage
    * number        sequential number of the covariate pattern
    * residuals     Pearson residuals; adjusted for number sharing covariate pattern
    * rstandard     standardized Pearson residuals; adjusted for number sharing covariate pattern
      score         first derivative of the log likelihood with respect to xb
    ---------------------------------------------------------------------------------------------------------------------
    Unstarred statistics are available both in and out of sample; type predict ... if e(sample) ... if wanted only for
      the estimation sample.  Starred statistics are calculated only for the estimation sample, even when if e(sample) is
      not specified.
    pr, xb, stdp, and score are the only options allowed with svy estimation results.

极大似然估计没有R2

楼主我也遇到了同样的问题 伤脑筋中。。。。

楼主解决了吗？同问

这里也没有能检验多重共线性的啊，应该是multiple collinearity这个词吧……