This paper investigates the performance of three types of random coefficients logistic regression models; that is, models using parametric, semi-parametric, and nonparametric specifications of the distribution of the random effects. Whereas earlier studies focussed on models with a single random effect, here we look at models with multidimensional random effects (intercepts and slopes). Moreove...

In this paper we address the problem of clustering sets of curve or trajectory data generated by groups of objects or individuals. The focus is to model curve data directly using a set of model-based curve clustering algorithms referred to as mixtures of regressions or regression mixtures. The proposed methodology is based on extension to regression mixtures that we call random effects regressi...

This paper shows how the probability, for a random confounding factor to reverse the estimate of ordinary regression, decreases exponentially with the sample size.

Background Between 1990 and 2015, under-5 mortality rate (U5MR) declined by 53%, from an estimated rate of 91 deaths per 1000 live births to 43, globally. The aim of this study was to determine the share of health research systems in this decrease alongside other influential factors.   Methods We used random effect regression models including the ‘random intercept’ and ‘random intercept and ran...

the aim of the present study was to estimate the genetic parameters and genetic trends of somatic cell score (scs) in the first 3 lactations of iranian holstein cows by random regression (rr) animal model by using restricted maximum likelihood (reml) method. the data set used in this analysis included observations of 340318 test-day records of 41526 cows in 288 herds; 89969 test-day of 11750 co...