st: GLLAMM: logitic regression interaction non signficant but lincom gives signficant result

[Abdelouahid Tajar <a_tajar@hotmail.co.uk>]

Hi,

I run the following random-intercept logistic regression model for an outcome
with binomial distribution using gllamm with an interaction between the two covariates in the model: group (binary variable:1/0) and time, treated as continuous, (4 8 12 16 20 24)


 y is the number of success out of the number of trials : total_y

 
 I got result from the interaction term to be non significant (beta=.0453183,p= 0.169), time effect for reference group (group=0) non signficant (0.032,p=0.196), while the lincom result gives a significant slope for group=1 (.0773718,p<0.001). Please see results below, data presented on the log scale.

 This may not necessary be related to gllamm and could have another explanation,but I can not find a raison for this confusion at the moment, I would be thankful for any comments or suggestions from the list.

 
 Abdelouahid
*-------------------------Gllamm model---------------*

 

 xi: gllamm y i.group*time,i(id_n) link(logit) family(binomial) denom(total_y) nip(30) adapt

 

 *--------results for fixed effects---------* 







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

 _group_1       .2725252     .8026569   0.34    0.734    -1.300653 1.845704

 time           .0320535     .0248062   1.29    0.196    -.0165658 .0806729
  
 _IgroupXtime_1 .0453183      .0329514   1.38    0.169    -.0192653 .1099019

_cons          -5.649017     .6287469  -8.98    0.000    -6.881338 -4.416696

 
 *-------------------lincom to obtian the slpoe of time for group=1---*

 
lincom time + _groupXtime_1

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

 
 (1)   .0773718     .0216926       3.57    0.000    .034855 .1198886 		 	   		  
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