The general linear model (glm) provides a general framework for a large set of models whose common goal is to explain or predict a quantitative dependent variable by a set of independent variables which can be categorical of quantitative. The glm encompasses techniques such as Student’s t test, simple and multiple linear regression, analysis of variance, and covariance analysis. The glm is adeq...

We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

menorrhagia is one of the most common gynecological problem and leading causes of poor quality of life and iron deficiency anemia in women of reproductive age. research in gynecological field relies heavily on repeated measure designs. repeated measure studies are helpful in understanding how factors of interest change over time. our goal is to apply statistical methods which are appropriate fo...

In this article, a new class of functional models in which smoothing splines are used to model fixed effects as well as random effects is introduced. The linear mixed effects models are extended to nonparametric mixed effects models by introducing functional random effects, which are modeled as realizations of zero-mean stochastic processes. The fixed functional effects and the random functiona...

Like many other projects, this software library started with a data set and a problem. From this came statistical ideas for a solution, followed by some initial programming — which more than anything else helped to define the real computational and statistical issues — and then a more ambitious programming solution. The problem turned out to be harder than I thought; the first release-worthy co...

Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of inte...

We propose the semiparametric small area estimator under the partially linear model. Unlike the linear mixed models widely used in the small area estimation, which assume that the area effect is the random effect, we model the area effect as the unknown function of an area-indicative variable. We represent the nonparametric part for area effect using penalized splines, by which the estimation a...