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用什么命令，就要查看那个命令的帮助文件或者manual文件。
才能知道这个命令到底能提供什么。
你查xtlogit，看帮助的最后，已经列出一些保留值（一些屏幕是不显示的，所以需要查帮助文件），
其中fe里面是有pseudo R-squared.
Title
[XT] xtlogit -- Fixed-effects, random-effects, and population-averaged logit models
Syntax
Random-effects (RE) model
xtlogit depvar [indepvars] [if] [in] [weight] [, re RE_options]
Conditional fixed-effects (FE) model
xtlogit depvar [indepvars] [if] [in] [weight] , fe [FE_options]
Population-averaged (PA) model
xtlogit depvar [indepvars] [if] [in] [weight] , pa [PA_options]
Examples
Setup
. webuse union
Random-effects logit model
. xtlogit union age grade i.not_smsa south##c.year
Equal-correlation population-averaged logit model
. xtlogit union age grade i.not_smsa south##c.year, pa
Population-averaged logit model with robust variance
. xtlogit union age grade i.not_smsa south##c.year, pa vce(robust)
Fixed-effects logit model
. xtlogit union age grade i.not_smsa south##c.year, fe
Stored results
xtlogit, fe stores the following in e():
Scalars
e(N) number of observations
e(N_g) number of groups
e(N_drop) number of observations dropped because of all positive or all negative outcomes
e(N_group_drop) number of groups dropped because of all positive or all negative outcomes
e(k) number of parameters
e(k_eq) number of equations in e(b)
e(k_eq_model) number of equations in overall model test
e(k_dv) number of dependent variables
e(df_m) model degrees of freedom
e(r2_p) pseudo R-squared
e(ll) log likelihood
e(ll_0) log likelihood, constant-only model
e(chi2) chi-squared
e(g_min) smallest group size
e(g_avg) average group size
e(g_max) largest group size
e(p) significance
e(rank) rank of e(V)
e(ic) number of iterations
e(rc) return code
e(converged) 1 if converged, 0 otherwise
Macros
e(cmd) clogit
e(cmd2) xtlogit
e(cmdline) command as typed
e(depvar) name of dependent variable
e(ivar) variable denoting groups
e(model) fe
e(wtype) weight type
e(wexp) weight expression
e(title) title in estimation output
e(offset) linear offset variable
e(chi2type) LR; type of model chi-squared test
e(vce) vcetype specified in vce()
e(vcetype) title used to label Std. Err.
e(group) name of group() variable
e(multiple) multiple if multiple positive outcomes within groups
e(opt) type of optimization
e(which) max or min; whether optimizer is to perform maximization or minimization
e(ml_method) type of ml method
e(user) name of likelihood-evaluator program
e(technique) maximization technique
e(properties) b V
e(predict) program used to implement predict
e(marginsok) predictions allowed by margins
e(marginsnotok) predictions disallowed by margins
e(asbalanced) factor variables fvset as asbalanced
e(asobserved) factor variables fvset as asobserved
Matrices
e(b) coefficient vector
e(Cns) constraints matrix
e(ilog) iteration log
e(gradient) gradient vector
e(V) variance-covariance matrix of the estimators
Functions
e(sample) marks estimation sample
xtlogit, pa stores the following in e():
Scalars
e(N) number of observations
e(N_g) number of groups
e(df_m) model degrees of freedom
e(chi2) chi-squared
e(p) significance
e(df_pear) degrees of freedom for Pearson chi-squared
e(chi2_dev) chi-squared test of deviance
e(chi2_dis) chi-squared test of deviance dispersion
e(deviance) deviance
e(dispers) deviance dispersion
e(phi) scale parameter
e(g_min) smallest group size
e(g_avg) average group size
e(g_max) largest group size
e(rank) rank of e(V)
e(tol) target tolerance
e(dif) achieved tolerance
e(rc) return code
Macros
e(cmd) xtgee
e(cmd2) xtlogit
e(cmdline) command as typed
e(depvar) name of dependent variable
e(ivar) variable denoting groups
e(tvar) variable denoting time within groups
e(model) pa
e(family) binomial
e(link) logit; link function
e(corr) correlation structure
e(scale) x2, dev, phi, or #; scale parameter
e(wtype) weight type
e(wexp) weight expression
e(offset) linear offset variable
e(chi2type) Wald; type of model chi-squared test
e(vce) vcetype specified in vce()
e(vcetype) title used to label Std. Err.
e(nmp) nmp, if specified
e(properties) b V
e(predict) program used to implement predict
e(marginsnotok) predictions disallowed by margins
e(asbalanced) factor variables fvset as asbalanced
e(asobserved) factor variables fvset as asobserved
Matrices
e(b) coefficient vector
e(R) estimated working correlation matrix
e(V) variance-covariance matrix of the estimators
Functions
e(sample) marks estimation sample
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