Sentence examples for binomial mixed regression model from inspiring English sources
Because number of drinks and frequency of abusive drinking are not normally distributed and because of over-dispersion (a minority may never drink), we used a negative binomial mixed regression model.
The hypothesis that interventions improved care was tested using general (normal error distribution and identity link function) or generalized (binomial error and logit link) linear mixed regression models (19).
We propose a Bayesian approach for the mixed-effects analysis of accuracy studies using mixed binomial regression models.
The ranking positions of hospitals were calculated for crude IDs and IDs adjusted by specialties and hospital type in mixed effect's negative binomial regression model.
For the meta-analytical data evaluation, we used an exact binomial rendition 15 of the bivariate, mixed effects regression model developed by van Houwelingen and colleagues 16 and modified for synthesis of diagnostic test data.
First, an unadjusted log binomial regression model was performed by regressing the prevalence of metabolic syndrome on prior service.
Risk factors satisfying a P-value criterion of P<0.20 in univariate log binomial regression models were included into a multivariate log binomial regression model.
By Vuong test, zero-inflated negative binomial regression model was not significantly better than negative binomial model (z = 1.14, p = 0.128), thus negative binomial model was chosen.
Generalised binomial linear regression models with mixed effects were used with sows (level 1) nested within farms (level 2) to account for the similarity of sows within farms.
