We found substantial variation in reaction norms between t of individuals in response to cover, as the model including random intercept and slope was superior to the model containing random intercept only (dAICc = 11.4).
All models contained random intercepts; additional random effects, such as random slopes, were tested using likelihood ratio tests.
These models contained random intercepts for camp and elephant to account for clustering, as multiple elephants were observed per camp, and multiple body regions were examined per elephant.
Size effect in concrete under tension is studied by Monte Carlo simulations of mesoscale finite element models containing random inclusions (aggregates and pores) with prescribed volume fractions, shapes and size distributions (called meso-structure controls).
The inhomogeneous universes are represented by Sweese-cheese models containing random and simple cubic lattices of mass-compensated voids.
We then ran mixed models containing random subject effects using SAS (version 8.02; SAS Institute, Cary, NC) to examine the impact of various personal characteristics on FENO.
Superior fit of models containing random intercepts between populations and random slopes between families indicated that also survival rates differed among populations, and that reaction norms of survival rates varied significantly among families, thus representing GxE interactions (Table 1).
Chi‐squared tests for trend in log odds ratios were conducted and the estimated odds ratios of prevalent ischaemic heart disease and stroke/transient ischaemic attack were examined for departure from linearity by testing the type 3 chi‐square for categorical random blood glucose, in a model that contained random blood glucose as a categorical and a continuous variable.
Primary inferential analyses consisted of random coefficient multilevel (i.e., HLM) models that contained random intercepts or random intercepts and slopes to model within-participant correlations of responses over time, providing a unified method to model both binary (i.e., nonadherence) and continuous outcomes (i.e., the coping measures).
The statistical model contained a random intercept, the outcome variable at baseline as a covariate and the fixed factors effects group affiliation, time and the interaction between time and group affiliation.
