[XT] xtreg postestimation -- Postestimation tools for xtreg
Description
The following postestimation commands are of special interest after xtreg:
command description
-----------------------------------------------------------------------------------------------------------
xttest0 Breusch and Pagan LM test for random effects
-----------------------------------------------------------------------------------------------------------
The following standard postestimation commands are also available:
command description
-----------------------------------------------------------------------------------------------------------
(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
margins marginal means, predictive margins, marginal effects, and average marginal effects
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
test Wald tests of simple and composite linear hypotheses
testnl Wald tests of nonlinear hypotheses
-----------------------------------------------------------------------------------------------------------
(1) estat ic is not appropriate with xtreg, be, xtreg, pa, or xtreg, re.
Special-interest postestimation commands
xttest0, for use after xtreg, re, presents the Breusch and Pagan Lagrange multiplier test for random
effects, a test that Var(v_i)=0.
statistic description
-----------------------------------------------------------------------------------------------------------
Main
xb xb, fitted values; the default
stdp calculate standard error of the fitted values
ue u_i + e_it, the combined residual
* xbu xb + u_i, prediction including effect
* u u_i, the fixed- or random-error component
* e e_it, the overall error component
-----------------------------------------------------------------------------------------------------------
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.
PA_statistic description
-----------------------------------------------------------------------------------------------------------
Main
mu probability of depvar; considers the offset()
rate probability of depvar
xb calculate linear prediction
stdp calculate 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.
Menu
Statistics > Postestimation > Predictions, residuals, etc.
Options for predict
+------+
----+ Main +-----------------------------------------------------------------------------------------------
xb calculates the linear prediction, that is, a + bx_it. This is the default for all except the
population-averaged model.
stdp calculates the standard error of the linear prediction. For the fixed-effects model, this excludes
the variance due to uncertainty about the estimate of u_i.
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.
ue calculates the prediction of u_it + e_it.
xbu calculates the prediction of a + bx_it + u_i, the prediction including the fixed or random component.
u calculates the prediction of u_i, the estimated fixed or random effect.
e calculates the prediction of e_it.
score calculates the equation-level score.
nooffset is relevant only if you specified offset(varname) for xtreg. It modifies the calculations made by
predict so that they ignore the offset variable; the linear prediction is treated as xb rather than xb
+ offset.
请问各位 在面板数据中 估计完方程后，怎么计算面板数据残差平方和
扫码加好友，拉您进群
全部版块
我的主页
收藏
