melogit health2013 ib(first).leeftijdscat_4 oplmet || nohouse_encr:, vce(robust) or
(predicting poor health from age and education taking account of nested structure (individuals within households))
Several things do not matter so much, robust or not, mean/variance or mode/curvature gauss-hermite, integration 7 or 50. At least, that is what I tested.
Below you see STATA and SPSS output from this multilevel logistic regression.
Are the differences in Odds ratios and random effect variance plausible? Particularly the difference regarding the random effect variance (0.539 in stata versus 0.113 in spss) worries me. As I am a STATA newbie, is above melogit command ok? Or did I make a mistake? Or is STATA estimation just better?
Thanks a lot for any advice.
Hans
STATA output
Mixed-effects logistic regression Number of obs = 1701
Group variable: nohouse_encr Number of groups = 1479
Obs per group: min = 1
avg = 1.2
max = 4
Integration method: mvaghermite Integration points = 7
Wald chi2(4) = 31.77
Log pseudolikelihood = -780.67238 Prob > chi2 = 0.0000
(Std. Err. adjusted for clustering on nohouse_encr)
----------------------------------------------------------------------------------
| Robust
health2013 | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
|
leeftijdscat_4 |
2 | 1.315458 .4699117 0.77 0.443 .6531427 2.649388
3 | 2.846147 .9623088 3.09 0.002 1.467095 5.521493
4 | 3.065375 1.048153 3.28 0.001 1.568302 5.991528
|
oplmet | .8663129 .0445488 -2.79 0.005 .7832548 .9581786
_cons | .1337556 .0501185 -5.37 0.000 .0641749 .2787781
-----------------+----------------------------------------------------------------
nohouse_encr |
var(_cons)| .5396133 .5581699 .0710574 4.097849
----------------------------------------------------------------------------------
SPSS output
leeftijd2 1.30 0.67-2.53
leeftijd3 2.68 1.47-4.91
leeftijd4 2.87 1.56-5.29
oplmet 0.88 0.80-0.96
cons 0.16 0.09-0.29
variance: 0.113 st.error: 0.201 p =0.57 95%CI 0.003-3.67
(predicting poor health from age and education taking account of nested structure (individuals within households))
Several things do not matter so much, robust or not, mean/variance or mode/curvature gauss-hermite, integration 7 or 50. At least, that is what I tested.
Below you see STATA and SPSS output from this multilevel logistic regression.
Are the differences in Odds ratios and random effect variance plausible? Particularly the difference regarding the random effect variance (0.539 in stata versus 0.113 in spss) worries me. As I am a STATA newbie, is above melogit command ok? Or did I make a mistake? Or is STATA estimation just better?
Thanks a lot for any advice.
Hans
STATA output
Mixed-effects logistic regression Number of obs = 1701
Group variable: nohouse_encr Number of groups = 1479
Obs per group: min = 1
avg = 1.2
max = 4
Integration method: mvaghermite Integration points = 7
Wald chi2(4) = 31.77
Log pseudolikelihood = -780.67238 Prob > chi2 = 0.0000
(Std. Err. adjusted for clustering on nohouse_encr)
----------------------------------------------------------------------------------
| Robust
health2013 | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
|
leeftijdscat_4 |
2 | 1.315458 .4699117 0.77 0.443 .6531427 2.649388
3 | 2.846147 .9623088 3.09 0.002 1.467095 5.521493
4 | 3.065375 1.048153 3.28 0.001 1.568302 5.991528
|
oplmet | .8663129 .0445488 -2.79 0.005 .7832548 .9581786
_cons | .1337556 .0501185 -5.37 0.000 .0641749 .2787781
-----------------+----------------------------------------------------------------
nohouse_encr |
var(_cons)| .5396133 .5581699 .0710574 4.097849
----------------------------------------------------------------------------------
SPSS output
leeftijd2 1.30 0.67-2.53
leeftijd3 2.68 1.47-4.91
leeftijd4 2.87 1.56-5.29
oplmet 0.88 0.80-0.96
cons 0.16 0.09-0.29
variance: 0.113 st.error: 0.201 p =0.57 95%CI 0.003-3.67
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