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Keywords: variance components
Search: (1) Official help files, FAQs, Examples, SJs, and STBs
Search of official help files, FAQs, Examples, SJs, and STBs
[R] loneway . . . . . Large one-way ANOVA, random effects, and reliability
(help loneway)
[R] regress postestimation . . . . . . . Postestimation tools for regress
(help regress postestimation)
Example . . . . . . . . . . . . . . . Stata web books: Regression with Stata
. . Chen, Ender, Mitchell & Wells (UCLA Academic Technology Services)
7/06 web book Regression with Stata by (in alphabetical
order) Xiao Chen, Philip B. Ender, Michael Mitchell
& Christine Wells
http://www.ats.ucla.edu/stat/stata/webbooks/reg/
SJ-6-1 st0095 . . . . . . . . . . . Estimating variance components in Stata
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Marchenko
Q1/06 SJ 6(1):1--21 (no commands)
describes using xtmixed to estimate variance components
in linear models
SJ-6-1 gn0031 . . Review of Multilevel and Longitudinal Modeling Using Stata
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Wolfe
Q1/06 SJ 6(1):138--143 (no commands)
book review of Multilevel and Longitudinal Modeling
Using Stata by Rabe-Hesketh and Skrondal
SJ-4-4 st0077 . . CIs for the variance comp. of random-effects linear models
(help xtvc if installed) . . . . . . . . . . M. Bottai and N. Orsini
Q4/04 SJ 4(4):429--435
confidence intervals for the variance components of
random-effects linear regression models.
STB-60 sg160 . . . . . . . . . . . . On boundary-value likelihood-ratio tests
. . . . . . . . . . . . R. G. Gutierrez, S. Carter, and D. M. Drukker
3/01 pp.15--18; STB Reprints Vol 10, pp.269--273 (no commands)
discusses likelihood-ratio boundary tests (such as tests for
the presence of overdispersion or random effects) which are
based on a mixture of a point mass at zero and a chi-squared
distribution
Nick
[email protected]
Lijun Song
> I am running variance component models using both loneway and xtreg.
>
> Could we use both of them to deal with all kinds of variables
> including continuous, categorical and discrete dependent variables?
>
> I have this question because when we run random
> intercept/slope models, we can only use xtreg to analyze
> Continuous outcomes but use gllamm to analyze categorial or
> discrete variables, right?
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