Analysis of crop lodging using a latent variable model

A method for quantifying treatment comparisons for a situation in which there are too many zeros in the dataset for a conventional analysis of variance to be valid is presented. The method assumes the existence of a latent variable such that zero observations correspond to values below a threshold,...

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Bibliographic Details
Published in:The Journal of agricultural science 2003-06, Vol.140 (4), p.383-393
Main Authors: ALLCROFT, D. J., GLASBEY, C. A.
Format: Article
Language:English
Subjects:
Agronomy. Soil science and plant productions
Biological and medical sciences
Biometrics, statistics, experimental designs, modeling, agricultural computer applications
crops
CROPS AND SOILS
Datasets
Econometrics
equations
Fundamental and applied biological sciences. Psychology
Generalities. Biometrics, experimentation. Remote sensing
Lodging
mathematical models
Normal distribution
Seasons
statistical analysis
Variance analysis
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Summary:A method for quantifying treatment comparisons for a situation in which there are too many zeros in the dataset for a conventional analysis of variance to be valid is presented. The method assumes the existence of a latent variable such that zero observations correspond to values below a threshold, and non-zero observations are transformed to fit the part of the distribution above the threshold. The method is known as Tobit analysis in econometrics. Parameters are estimated by maximum likelihood and standard errors obtained, all using standard numerical routines. Use of the method is demonstrated by analysis of a dataset of crop lodging, and it is anticipated to be widely applicable to other types of data for which high numbers of zeros prevent conventional analysis.
ISSN:0021-8596
1469-5146
DOI:10.1017/S0021859603003332