This is a modified version of the stepAIC() function from the R package MASS which uses AICc (Akaike's corrected information criterion) rather than AIC to select the predictor to add at each step.
In a binary choice panel data framework, probabilities of the outcomes of several individuals depend on the correlation of the unobserved heterogeneity. I propose a random effects estimator that model
Light foraging by trees is a fundamental process shaping forest communities. In heterogeneous light environments this behavior is expressed as plasticity of tree growth and the development of structur
