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Re: st: Wald test in Random Coefficient Model


From   Joerg Luedicke <joerg.luedicke@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Wald test in Random Coefficient Model
Date   Thu, 24 Feb 2011 17:04:26 -0500

On Thu, Feb 24, 2011 at 4:44 PM, Shikha Sinha <shikha.sinha414@gmail.com> wrote:
> Thank you very much for your response. It is WHO "Health Behaviour in
> school-aged children " data.
>
> May I also ask you the interpretation of "LR test vs. logistic
> regression:     chi2(3) =  2132.55   Prob > chi2 = 0.0000". in the
> following output.
>
> ------------------------------------------------------------------------------
>  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
> -----------------------------+------------------------------------------------
> wp5: Unstructured            |
>                   var(drel) |    .037479   .0209765      .0125136    .1122521
>                  var(_cons) |   .1952712   .0515963      .1163391    .3277558
>             cov(drel,_cons) |  -.0052752   .0251633     -.0545943    .0440439
> ------------------------------------------------------------------------------
> LR test vs. logistic regression:     chi2(3) =  2132.55   Prob > chi2 = 0.0000

this is a test of the multilevel model against a complete pooled
model, i.e. the logistic regression without any random effects. If you
have more than 1 random effect it basically comes down to another sort
of omnibus test and is most often not very useful. you can check it
out:

---Example---

/*get some data*/
sysuse auto, clear

/*artificially creating 10 clusters*/
xtile level2= price, n(10)

/*getting a binary dep var*/
gen mile=mpg>20

/*fitting conventional logit*/
logit  mile headroom
est sto m1

/*fitting multilevel model with varying intercept and slope*/
xtmelogit  mile headroom || level2: headroom
est sto m2

/*comparing fit in terms of the likelihood (aka chi2 difference test)*/
di 2*(40.648143  - 39.082619)

---End---

J.

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