mixed - Stata
mixed - Stata
mixed - Stata
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
2 <strong>mixed</strong> — Multilevel <strong>mixed</strong>-effects linear regression<br />
options<br />
Model<br />
mle<br />
reml<br />
pwscale(scale method)<br />
residuals(rspec)<br />
SE/Robust<br />
vce(vcetype)<br />
Reporting<br />
level(#)<br />
variance<br />
stddeviations<br />
noretable<br />
nofetable<br />
estmetric<br />
noheader<br />
nogroup<br />
nostderr<br />
nolrtest<br />
display options<br />
EM options<br />
emiterate(#)<br />
emtolerance(#)<br />
emonly<br />
emlog<br />
emdots<br />
Maximization<br />
maximize options<br />
matsqrt<br />
matlog<br />
coeflegend<br />
Description<br />
fit model via maximum likelihood; the default<br />
fit model via restricted maximum likelihood<br />
control scaling of sampling weights in two-level models<br />
structure of residual errors<br />
vcetype may be oim, robust, or cluster clustvar<br />
set confidence level; default is level(95)<br />
show random-effects and residual-error parameter estimates as variances<br />
and covariances; the default<br />
show random-effects and residual-error parameter estimates as standard<br />
deviations<br />
suppress random-effects table<br />
suppress fixed-effects table<br />
show parameter estimates in the estimation metric<br />
suppress output header<br />
suppress table summarizing groups<br />
do not estimate standard errors of random-effects parameters<br />
do not perform likelihood-ratio test comparing with linear regression<br />
control column formats, row spacing, line width, display of omitted<br />
variables and base and empty cells, and factor-variable labeling<br />
number of EM iterations; default is emiterate(20)<br />
EM convergence tolerance; default is emtolerance(1e-10)<br />
fit model exclusively using EM<br />
show EM iteration log<br />
show EM iterations as dots<br />
control the maximization process; seldom used<br />
parameterize variance components using matrix square roots; the default<br />
parameterize variance components using matrix logarithms<br />
display legend instead of statistics