mixed - Stata
mixed - Stata
mixed - Stata
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
44 <strong>mixed</strong> — Multilevel <strong>mixed</strong>-effects linear regression<br />
Stored results<br />
<strong>mixed</strong> stores the following in e():<br />
Scalars<br />
e(N)<br />
number of observations<br />
e(k)<br />
number of parameters<br />
e(k f)<br />
number of fixed-effects parameters<br />
e(k r)<br />
number of random-effects parameters<br />
e(k rs)<br />
number of variances<br />
e(k rc)<br />
number of covariances<br />
e(k res)<br />
number of residual-error parameters<br />
e(N clust)<br />
number of clusters<br />
e(nrgroups)<br />
number of residual-error by() groups<br />
e(ar p)<br />
AR order of residual errors, if specified<br />
e(ma q)<br />
MA order of residual errors, if specified<br />
e(res order)<br />
order of residual-error structure, if appropriate<br />
e(df m)<br />
model degrees of freedom<br />
e(ll)<br />
log (restricted) likelihood<br />
e(chi2) χ 2<br />
e(p)<br />
significance<br />
e(ll c)<br />
log likelihood, comparison model<br />
e(chi2 c)<br />
χ 2 , comparison model<br />
e(df c)<br />
degrees of freedom, comparison model<br />
e(p c)<br />
significance, comparison model<br />
e(rank)<br />
rank of e(V)<br />
e(rc)<br />
return code<br />
e(converged)<br />
1 if converged, 0 otherwise<br />
Macros<br />
e(cmd)<br />
<strong>mixed</strong><br />
e(cmdline)<br />
command as typed<br />
e(depvar)<br />
name of dependent variable<br />
e(wtype)<br />
weight type (first-level weights)<br />
e(wexp)<br />
weight expression (first-level weights)<br />
e(fweightk)<br />
fweight expression for kth highest level, if specified<br />
e(pweightk)<br />
pweight expression for kth highest level, if specified<br />
e(ivars)<br />
grouping variables<br />
e(title)<br />
title in estimation output<br />
e(redim)<br />
random-effects dimensions<br />
e(vartypes)<br />
variance-structure types<br />
e(revars)<br />
random-effects covariates<br />
e(resopt)<br />
residuals() specification, as typed<br />
e(rstructure)<br />
residual-error structure<br />
e(rstructlab)<br />
residual-error structure output label<br />
e(rbyvar)<br />
residual-error by() variable, if specified<br />
e(rglabels)<br />
residual-error by() groups labels<br />
e(pwscale)<br />
sampling-weight scaling method<br />
e(timevar)<br />
residual-error t() variable, if specified<br />
e(chi2type) Wald; type of model χ 2 test<br />
e(clustvar)<br />
name of cluster variable<br />
e(vce)<br />
vcetype specified in vce()<br />
e(vcetype)<br />
title used to label Std. Err.<br />
e(method)<br />
ML or REML<br />
e(opt)<br />
type of optimization<br />
e(optmetric)<br />
matsqrt or matlog; random-effects matrix parameterization<br />
e(emonly)<br />
emonly, if specified<br />
e(ml method)<br />
type of ml method<br />
e(technique)<br />
maximization technique<br />
e(properties)<br />
b V<br />
e(estat cmd)<br />
program used to implement estat<br />
e(predict)<br />
program used to implement predict<br />
e(asbalanced)<br />
factor variables fvset as asbalanced<br />
e(asobserved)<br />
factor variables fvset as asobserved