The analysis of proportions in agricultural experiments by a generalized linear mixed model
- 1 September 1993
- journal article
- Published by Wiley in Statistica Neerlandica
- Vol. 47 (3) , 161-174
- https://doi.org/10.1111/j.1467-9574.1993.tb01414.x
Abstract
This paper is concerned with the statistical analysis of proportions involving extra‐binomial variation. Extra‐binomial variation is inherent to experimental situations where experimental units are subject to some source of variation, e.g. biological or environmental variation. A generalized linear model for proportions does not account for random variation between experimental units. In this paper an extended version of the generalized linear model is discussed with special reference to experiments in agricultural research. In this model it is assumed that both treatment effects and random contributions of plots are part of the linear predictor. The methods are applied to results from two agricultural experiments.Keywords
This publication has 23 references indexed in Scilit:
- SOME MODELS FOR OVERDISPERSED BINOMIAL DATAAustralian Journal of Statistics, 1988
- Mixed Models for Binomial Data with an Application to Lamb MortalityJournal of the Royal Statistical Society Series C: Applied Statistics, 1988
- Maximum Likelihood Estimates for Binary Data with Random EffectsBiometrical Journal, 1988
- Random effects in generalized linear models and the em algorithamCommunications in Statistics - Theory and Methods, 1988
- The analysis of binomial data by a generalized linear mixed modelBiometrika, 1985
- On the Convergence Properties of the EM AlgorithmThe Annals of Statistics, 1983
- Beta-Binomial Anova for ProportionsJournal of the Royal Statistical Society Series C: Applied Statistics, 1978
- Symbolic Description of Factorial Models for Analysis of VarianceJournal of the Royal Statistical Society Series C: Applied Statistics, 1973
- Generalized Linear ModelsJournal of the Royal Statistical Society. Series A (General), 1972