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Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.
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Setting priors for bivariate regression
I would like to perform a bivariate MCMC regression with boldness scores as the continuous response variable, aggression ranks as the ordinal response variable, trial numbers as fixed effect and indiv …
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146
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Intercepts of repeated measures
I'm examining how boldness of individuals change with time. My data consists of individuals repeatedly measured across trials for boldness scores. First, I plotted each individual to see its mean and …
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Non-straight lines in random intercept random slope plots
I'm trying to see how boldness of individuals change over time. For this, I constructed a repeated measures random intercept random slope model with boldness scores (measured as latency to resume move …