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We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise.
Lazarus et. al. [ 26] use a generalized linear mixed model based on four years of data from ambulatory health encounters.
It is customary to use a generalized linear (mixed) model (GL(M M) to analyse binary or categorical data [ 23].
Instead, we use a generalized linear mixed-model, which allows for probability distribution other than a normal distribution using a link function to transform the outcome variable.
To estimate the additive genetic variance (and thus the heritability) of different kinds of traits, biologists and animal breeders often use a generalized linear mixed model (GLMM), called an animal model.
We use a generalized linear model with negative binomial response distribution and bivariate smoothing approach [ 15] to estimate the number of contacts during a day in age class i by participants in age class j [ 6, 7, 10, 11].
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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.
In the first step, we used a generalized linear mixed-effects model to assess the variables that influence macroptery.
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