25 апр. 2018 г. · Fitting single-level hurdle models is easy because you fit separate logit and zero-truncated Poisson or negative binomial models.

In this paper we propose to use the h-likelihood approach [5,6] to estimate and test the parameters of a hurdle model in a repeated measurements context. Our ...

26 июн. 2015 г. · I wondered if anyone had experience fitting multilevel hurdle models in STATA? I see from Long and Freese's text for non-clustered data they ...

9 мая 2022 г. · Create, manipulate, understand, analyze, interpret, and plot Bayesian hurdle regression models (and a custom hurdle Gaussian model!)

22 окт. 2024 г. · Zero-inflated Poisson and hurdle models have been proposed to perform a valid likelihood-based analysis to account for the surplus of zeros.

A hurdle model is a class of statistical models where a random variable is modelled using two parts, the first which is the probability of attaining value 0.

The multilevel zero-inflated and multilevel hurdle models are considered to handle unobserved heterogeneity that may occur at province level, and to model ...

We examine the h-likelihood estimation and inference framework for hurdle models with random effects for complex designs. We extend the h-likelihood procedures ...

23 авг. 2018 г. · If you want to include zeros, you can specify a hurdle model that looks at zero vs. above zero, and then looks at everything above zero—this is ...

23 июн. 2014 г. · Count data are collected repeatedly over time in many applications, such as biology, epidemiology, and public health.