[R] GEE Modelle in Stata und R

From: Christian Bieli <christian.bieli_at_unibas.ch>
Date: Thu 09 Feb 2006 - 04:17:44 EST


Hall Christian

Ich habe Dir hier den Output desselben Models mir den selben Daten mit R und mit Stata gerechnet angehängt.
Wie Du siehst sind die Unterschiede nicht unbeträchtlich. Da Du bestimmt schon ähnliche Erfahrungen gemacht hast, wollte ich Dich fragen, ob diese Unterschiede im Rahmen dessen sind, wie man sie zwischen zwei verschiedenen packages erwarten kann, oder nicht.

Für eine kurze Antwort wäre ich Dir sehr dankbar. Liebe Grüsse
Christian

R output:

     GEE:  GENERALIZED LINEAR MODELS FOR DEPENDENT DATA
     gee S-function, version 4.13 modified 98/01/27 (1998)

    Model:
     Link:                      Logit
     Variance to Mean Relation: Binomial
     Correlation Structure:     Exchangeable

    Call:
    gee(formula = y ~ Var1 * Var2 + Var3, id = Var4,

        data = mydata, family = binomial, corstr = "exchangeable",
        scale.fix = TRUE)

    Summary of Residuals:
            Min          1Q      Median          3Q         Max

-0.16457139 -0.10916961 -0.05774320 -0.01334249 0.98519918

    Coefficients:

                       Estimate Naive S.E.     Naive z Robust S.E.    
    Robust z
    (Intercept)     -2.02946378  0.6152142 -3.29879234   0.6276423 

-3.23347186
Var1med -0.06978758 0.8108207 -0.08607031 0.8280726
-0.08427713
Var1hi 0.08988940 0.9738316 0.09230487 0.9851523 0.09124417 Var2yes -2.16869738 1.2386945 -1.75079278 1.4269696
-1.51979227
Var3yes -0.10520805 0.5724176 -0.18379597 0.6881670

-0.15288157

    Var1med:Var2yes 1.58088457 1.3503015 1.17076411 1.3682419     1.15541309
    Var1hi:Var2yes 2.48367129 1.4694804 1.69016976 1.4707481     1.68871291

    Estimated Scale Parameter: 1

Stata Output:

    xi: xtgee y i.Var1*i.Var2 Var3, family(binomial) link(logit) i(Var4)

    GEE population-averaged model                   Number of obs     
    =       309
    Group variable:                       Var4      Number of groups  
    =       215
    Link:                                logit      Obs per group: min
    =         1
    Family:                           binomial                     avg
    =       1.4
    Correlation:                  exchangeable                     max
    =         8
                                                    Wald chi2(6)      
    =      7.68
    Scale parameter:                         1      Prob > chi2       

               y | Coef. Std. Err. z P>|z| [95% Conf.     Interval]
-------------+----------------------------------------------------------------

           _cons | -1.938584 .8662878 -2.24 0.025 -3.636477
-.2406913

        _IVar1_2 | -.0610133 .8087995 -0.08 0.940
-1.646231 1.524205

        _IVar1_3 | .0944082 .9720986 0.10 0.923
-1.81087 1.999686

        _IVar2_2 | -2.178428 1.240422 -1.76 0.079
-4.60961 .2527538

            Var3 | -.0977918 .5719084 -0.17 0.864
-1.218712 1.023128

    _IVarXVa~2_2 |   1.575095   1.351553     1.17   0.244   

-1.073901 4.22409
_IVarXVa~3_2 | 2.483814 1.470152 1.69 0.091
-.3976316 5.36526
------------------------------------------------------------------------------

Christian

-- 
Christian Bieli, project assistant
Institute of Social and Preventive Medicine
University of Basel, Switzerland
Steinengraben 49
CH-4051 Basel
Tel.: +41 61 270 22 12
Fax:  +41 61 270 22 25
christian.bieli@unibas.ch
www.unibas.ch/ispmbs

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Received on Thu Feb 09 05:35:59 2006

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