Fitting Models to Your Experimental Data When They Are Counts or Proportions. An Introduction to Generalized Linear Mixed Models.Mark West
We analysed the scratching frequency using a Generalised Linear Mixed Model (GLMM; see Methods). The full model, which included condition (fortunate, unfortunate, control) as the key predictor along with control variables, explained significantly more variance than the null model containing only contro...
According to our main hypothesis, if dogs rely on their body size representation, they would prefer the shortcut over the detour, but only if the door was large enough for them. Here the alternative hypothesis suggested that dogs will always prefer the shorter route, thus they will at first ...
A Generalised Linear Mixed Model (GLMM) was applied to estimate the effects of the zebra crossing, eHMI, and the number of encounters on pedestrians' head-turning frequency, in yielding trials (N = 357), before the crossing initiation. As discussed in the Introduction, pedestrians will need ...
Data were analyzed using the mixed model, generalized linear model, and correlation procedures of the SAS statistical program (version 9.4; SAS Institute). Myofiber CSA, total myonuclear abundance, myonuclear domain size, Pax7+ satellite cell abundance, BrdU+ myonuclear abundance, and IGF system ...
Analyses of condition effects (plagiarismvs.other cheating) on dichotomous dependent variables were conducted using McNemar’s method and exact binomial tests for testing hypotheses. For all other analyses, data were analyzed using generalized linear mixed models with random intercepts for participants and...
We used a Generalized Linear Mixed Model (GLMM) with binary logistic regression link to assess accuracy in listeners' body size estimates. The dependent variable was the binary response (correct vs. incorrect estimation of relative body size). Sightedness (early blind, late blind, sighted) and ...
Results A linear mixed model was used to account for the non-independence of the two product evaluations across the same participant (i.e. random intercept for participants, 546 F. VAN HOREN ET AL. Cameron and Trivedi 2005). As all the interactions including product were insignificant (ps...
Therefore, we use a mixed effect model, with only the intercept allowed to vary between crop groups, keeping the slope constant. The results indicate a statistically significant positive main effect of LF-NPC potential to yield gaps. Despite the positive coefficient, it is important to note that...
We analyzed whether children’s belief revision differed across the linguistic groups, age, and condition using a generalized linear mixed model (GLMM) with binomial error distribution because we had a binary response measure (whether children revised their initial beliefs) in a within-participants des...