Hi, 

 

I’ve tried to find a general approach to my problem without any success,
although this might very well be due to my inexperience with R help
resources (and statistics in general).

 

My general problem is a straightforward 2 by 2 table (“Belonging to the
upper quartile” vs “not-belonging to the upper quartile”, intervention vs
non-intervention), but with a random effect addressing the hierarchical
structure of the individual data points. The different data points are
pseudoreplicated, some hailing from the same patients (some patients have
contributed with 1, while others as much as 7 – i.e. not constant). 

 

Naturally I would like to adjust for this clustering within patients, but I
have failed to see which model/approach that would be correct. Is there some
way to do a logistic regression with only a binary explanatory variable and
a added random effect adjusting for data entry nesting within patients,
preferentially giving an odds ratio with a confidence interval? I’ve tried
to use the lme function in the nlme package, but I feel this would be
stretching it a bit.

 

I’m terribly sorry if this problem is to obvious, but I would appreciate any
feedback and pointers in the right direction.

 

Sincerely,

Kjetil



Checked by AVG. 

07:04
 

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