急问：logit和xtlogit的区别？

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我要用面板数据做logistic模型，在stata里面该用什么命令呢？是logit还是xtlogit？它们有什么区别啊？
还有，要求边际效应的话用mfx命令，这个命令是不是只对logit有效，对xtlogit无效？
哪位高手帮忙回答一下吧，谢谢！

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关键词：xtlogit logit Log tlo Logistic模型 模型

有没有高手解答一下啊？

grace爱舒米 发表于 2011-8-23 10:24
有没有高手解答一下啊？

xtlogit適用於mutilevel的指令，logit 大多使用cross section的資料

logit    的回归结果是解释变量改变1个单位使被解释变量发生的可能性改变多少个标准差
xtlogit 的回归结果是解释变量改变1个单位使被解释变量发生的可能性改变多少百分点

用xtlogit比较容易解释回归结果。

谢谢分享。。。。。

lyw0318 发表于 2011-9-9 09:23
logit    的回归结果是解释变量改变1个单位使被解释变量发生的可能性改变多少个标准差
xtlogit 的回归结果 ...

logit结果不是你的这个解释


logit和xtlogit解释是一样的

Title
    [XT] xtlogit postestimation -- Postestimation tools for xtlogit

Description
    The following postestimation commands are available after xtlogit:
    Command          Description
    -----------------------------------------------------------------------------------------------------------
        contrast     contrasts and ANOVA-style joint tests of estimates
    (1) estat        AIC, BIC, VCE, and estimation sample summary
        estimates    cataloging estimation results
        hausman      Hausman's specification test
        lincom       point estimates, standard errors, testing, and inference for linear combinations of
                       coefficients
        lrtest       likelihood-ratio test
    (2) 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
        test         Wald tests of simple and composite linear hypotheses
        testnl       Wald tests of nonlinear hypotheses
    -----------------------------------------------------------------------------------------------------------
    (1) estat ic is not appropriate after xtlogit, pa.
    (2) The default prediction statistic for xtlogit, fe, pu1, cannot be correctly handled by margins; however,
        margins can be used after xtlogit, fe with the predict(pu0) option or the predict(xb) option.

Syntax for predict
    Random-effects model
        predict [type] newvar [if] [in] [, RE_statistic nooffset]
    Fixed-effects model
        predict [type] newvar [if] [in] [, FE_statistic nooffset]
    Population-averaged model
        predict [type] newvar [if] [in] [, PA_statistic nooffset]
    RE_statistic   Description
    -----------------------------------------------------------------------------------------------------------
    Main
      xb           linear prediction; the default
      pu0          probability of a positive outcome assuming the random effect is zero
      stdp         standard error of the linear prediction
    -----------------------------------------------------------------------------------------------------------
    FE_statistic   Description
    -----------------------------------------------------------------------------------------------------------
    Main
      pc1          probability of a positive outcome conditional on one positive outcome within group; the
                     default
      pu0          probability of a positive outcome assuming the fixed effect is zero
      xb           linear prediction
      stdp         standard error of the linear prediction
    -----------------------------------------------------------------------------------------------------------
    PA_statistic   Description
    -----------------------------------------------------------------------------------------------------------
    Main
      mu           probability of depvar; considers the offset()
      rate         probability of depvar
      xb           linear prediction
      stdp         standard error of the linear prediction
      score        first derivative of the log likelihood with respect to xb
    -----------------------------------------------------------------------------------------------------------
    These statistics are available both in and out of sample; type predict ... if e(sample) ... if wanted only
      for the estimation sample.
    The predicted probability for the fixed-effects model is conditional on there being only one outcome per
      group.  See [R] clogit for details.

Menu
    Statistics > Postestimation > Predictions, residuals, etc.

Options for predict
        +------+
    ----+ Main +-----------------------------------------------------------------------------------------------
    xb calculates the linear prediction.  This is the default for the random-effects model.
    pc1 calculates the predicted probability of a positive outcome conditional on one positive outcome within
        group.  This is the default for the fixed-effects model.
    mu and rate both calculate the predicted probability of depvar.  mu takes into account the offset(), and
        rate ignores those adjustments.  mu and rate are equivalent if you did not specify offset().  mu is the
        default for the population-averaged model.
    pu0 calculates the probability of a positive outcome, assuming that the fixed or random effect for that
        observation's panel is zero.  This may not be similar to the proportion of observed outcomes in the
        group.
    stdp calculates the standard error of the linear prediction.
    score calculates the equation-level score.
    nooffset is relevant only if you specified offset(varname) for xtlogit.  This option modifies the
        calculations made by predict so that they ignore the offset variable; the linear prediction is treated
        as xb rather than xb + offset.

Examples
    Setup
        . webuse union
    Fit random-effects model
        . xtlogit union age grade i.south
    Compute probability of positive outcome, assuming random effect is zero
        . predict prob, pu0
    Fit population-averaged model
        . xtlogit union age grade i.south, pa
    Compute predicted probability of union
        . predict unionpr, mu
    Compute average marginal effect of age on probability of union
        . margins, dydx(age)

use xtlogit for panel data

看看看

遇到类似的问题，margins出不来结果