Sentence examples for model count variables from inspiring English sources

Poisson regression analyses were used to model count variables under the assumption that the conditional means equal the conditional variances.

ZI models have been proposed to model count variables, dealing with an excess of zeros in several applications [ 26].

For example, CPT errors were modeled as count variables in this analysis, in contrast to previous studies that were not specific about how these errors were modeled but presumably used linear regression to model these outcomes (Jacobson and Jacobson 2003; Jacobson et al. 1992; Stewart et al. 2003, 2005).

Comparisons will comprise logistic regression models for binary outcomes and negative binomial regression modelling for count variables, adjusting for potential confounders.

The models for count variables had a better performance when predicting diseased animals and also had a similar performance between them.

Intervention effects were analyzed using General Estimate Equation (GEE) modeling for count variables using the intention-to-treat principle.

The treatment-by-time effect estimated in our Poisson models for count variables is, when exponentiated, a measure of the additional change in the outcome measure from baseline to follow-up that is attributable to Safety Counts.

We then used this model as our final model for all arrhythmia count variables.

A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables.

Two-stage hurdle models handle excess zero values in trip count variables and multi-level models deal with three-level data structure – household within station areas within regions.

The uncertainty around count variables were modeled by means of a Dirichlet distribution, the conjugate distribution of the multinomial distribution for modeling the probability of events [45].