Logic regression is an adaptive regression
method which searches for Boolean (logic) combinations of binary variables that
best explain the variability in the outcome, and thus, it reveals interaction
effects which are associated with the response. In this study, we extended
logic regression to longitudinal data with binary response and proposed
“Transition Logic Regression Method” to find interactions related to response.
In this method, interaction effects over time were found by Annealing Algorithm
with AIC (Akaike Information Criterion) as the score function of the model.
Also, first and second orders Markov dependence were allowed to capture the
correlation among successive observations of the same individual in
longitudinal binary response. Performance of the method was evaluated with
simulation study in various conditions. Proposed method was used to find
interactions of SNPs and other risk factors related to low HDL over time in
data of 329 participants of longitudinal TLGS study.
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