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Data were analyzed using a Generalized Linear Mixed Model that implements a generalization of the standard linear model allowing the incorporation of random effects [43].
Effects were tested using a generalized linear mixed effects model with a Poisson error distribution (log link).
Treatment differences were analyzed using a generalized linear mixed model.
Data was analyzed using a generalized linear mixed model, acknowledging the spatial distribution of data.
Because of the non-normal distribution of the data, even after transformations, we performed analysis using a generalized linear model with a single factor (i.e., species) using a Poisson distribution unless otherwise stated.
The influence of grazing intensity on change indicators was tested using a generalized linear regression.
The primary outcome will be modelled using a generalized linear mixed-model for repeated measures based on a participant-level analysis.
Using a generalized linear mixed model, we identified three significant variables: age-group, gender and direction of the fall.
Sapling density and the occurrence of debarking of saplings and trees were analyzed using a generalized linear mixed model (GLMM).
Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM).
The statistical analysis of the pre-processed BOLD signals was performed using a generalized linear model (GLM) approach.
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