INTRODUCTION Random regression (RR) models for longitudinal data often require a considerable number of parameters to describe the associated covariance functions. Estimation of these parameters has proven cumbersome and subject to sampling problems. Moreover, computational restraints have limited analyses of data sets sufficiently large to supply accurate estimates. This holds especially for c...

Fluoxetine and placebo were compared in 89 outpatients with major depression with (n = 45) or without (n = 44) a reduced or shortened rapid eye movement latency (SREML) (< or = 65 minutes) to determine whether rapid eye movement latency (REML) predicted placebo and/or antidepressant response. Men and women were stratified based on polysomnographic recordings and then randomly assigned to receiv...

In order to estimate genetic parameters for production traits and reproductive performance, 115 465 records of production traits and 90 942 records of reproductive performance from Iranian Holstein cows that were collected during 1980 to 2004 at Animal Breeding Center of Iran, were used. The estimations were performed using Restricted Maximum Likelihood method (REML) under an animal model by DF...

Finite mixtures of simpler component models such as mixtures of normals and mixtures of generalized linear models (GLM) have proven useful for modelling data arising from a heterogeneous population, typically under an independence assumption. Mixed-effects models are often used to handle correlation as arises in longitudinal or other clustered data. In Chapter 3 of this dissertation, we present...

BACKGROUND The random-effects (RE) model is the standard choice for meta-analysis in the presence of heterogeneity, and the standard RE method is the DerSimonian and Laird (DSL) approach, where the degree of heterogeneity is estimated using a moment-estimator. The DSL approach does not take into account the variability of the estimated heterogeneity variance in the estimation of Cochran's Q. Bi...

Generalized additive models (GAMs) have been widely used. While the procedure for fitting a generalized additive model to independent data has been well established, not as much work has been done when the data are correlated. The currently available methods are not completely satisfactory in practice. A new approach is proposed to fit generalized additive models with spatio-temporal data via t...

The main aim of considerations in the problem of estimation of variance components σ 1 and σ 2 2 by using the ML-method and REML-method in normal mixed linear model N{Y, E(Y ) = Xβ, Cov(Y ) = σ 1V + σ 2In} was concerned in the examination of theirs efficiency. It is particularly important when an explicit form of these estimators is unknown and we search for the solutions of the likelihood equa...