The generalized linear model (GLM) is a hot topic in statistics. Numerous research articles on GLM\u27s appear in each edition of all major journals in statistics. GLM\u27s are the subject of substantial numbers of presentations at most statistics conferences. Despite the high level of interest and research activity within the statistics community, GLM\u27s are not widely used, with some exceptions, by biological scientists in the statistical analysis of their research data. Why? Reasons include 1) many statisticians are not comfortable with GLM\u27s, 2) the biological research community is not familiar with GLM\u27s, and 3) there is little in introductory statistics courses as currently taught to change (1) or (2). Whether or not this is...
CTA has undertaken a study on ways of strengthening the use of biometry and statisitics in agricultu...
This book is concerned with the use of generalized linear models for univariate and multivariate reg...
One method of judging the effectiveness of the teaching of statistical methods is to rate the qualit...
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
Generalized linear models provide a methodology for doing regression and ANOV A-type analysis with d...
Generalized linear mixed models (GLMMs), regardless of the software used to implement them (R, SAS, ...
An understanding of estimable functions is essential when using an overparameterized linear model. T...
The purpose of this paper is to present a specific application of the generalized linear mixed model...
An area of increasing interest to agricultural and ecological researchers is the analysis of spatial...
Advances in computers and modeling over the past couple of decades have greatly expanded options for...
Statistical modelling plays a very important role in comprehending underlying relationships among cr...
Abstract: We compared the goodness of fit and efficiency of models for germination. Generalized Line...
In explanatory research, as opposed to exploratory research, data analysis is meant to shed light on...
Biometry is nor just the mechanical application of mathematical procedures, but is a coherent concep...
Recap: Generalized linear models for univariate responses Recall that generalized linear models (GLM...
CTA has undertaken a study on ways of strengthening the use of biometry and statisitics in agricultu...
This book is concerned with the use of generalized linear models for univariate and multivariate reg...
One method of judging the effectiveness of the teaching of statistical methods is to rate the qualit...
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
Generalized linear models provide a methodology for doing regression and ANOV A-type analysis with d...
Generalized linear mixed models (GLMMs), regardless of the software used to implement them (R, SAS, ...
An understanding of estimable functions is essential when using an overparameterized linear model. T...
The purpose of this paper is to present a specific application of the generalized linear mixed model...
An area of increasing interest to agricultural and ecological researchers is the analysis of spatial...
Advances in computers and modeling over the past couple of decades have greatly expanded options for...
Statistical modelling plays a very important role in comprehending underlying relationships among cr...
Abstract: We compared the goodness of fit and efficiency of models for germination. Generalized Line...
In explanatory research, as opposed to exploratory research, data analysis is meant to shed light on...
Biometry is nor just the mechanical application of mathematical procedures, but is a coherent concep...
Recap: Generalized linear models for univariate responses Recall that generalized linear models (GLM...
CTA has undertaken a study on ways of strengthening the use of biometry and statisitics in agricultu...
This book is concerned with the use of generalized linear models for univariate and multivariate reg...
One method of judging the effectiveness of the teaching of statistical methods is to rate the qualit...