Statistical Guides: Mixed Models and Multilevel Data Structures in Agriculture
Langues disponibles :
Langues disponibles :
Daté : mars 2001
Auteurs : Eleanor Allan , John Rowlands , Statistical Services Centre
A booklet aiming to help the reader understand what heirarchical data structures are and how they may be analysed. It presents several examples to help demonstrate these concepts.
From the introduction:
"Hierarchical or multilevel data structures can occur in many areas of agricultural research – for instance in on-farm trials, where there can be information at the village, farm and plot or animal level. Experiments in animal breeding are often concerned with attributing variation in traits of offspring, such as their growth, to the sires and dams from which they were bred. Researchers in this discipline are therefore familiar with the idea that livestock data often have some hierarchical structure with different levels of variation.
Analysis of variance – except in balanced or nested designs – has been difficult to apply to data with a multilevel structure. Mixed modelling is becoming a standard approach for analysing these types of data, particularly since it can deal with complicated or "messy" structures. The mixed model facilities are now available in some of the more powerful statistical packages such as Genstat and SAS.
There seems to be some "mystique" surrounding these methods, and our claim is that there should not be. The purpose of this guide is to review the general concepts of mixed models. We illustrate by example how to recognise the structure in the data and how to fit and interpret a mixed model analysis. The reader is expected to be familiar with simple analysis of variance methods."
Part of a series of statistical guides by The University of Reading Statistical Services Centre, which were originally written as part of a contract with DFID to give guidance to research and support staff working on DFID Natural Resources projects. They provide guidelines for staff involved in the development and presentation of research projects. The guidelines are intended to help researchers to identify their biometric or statistical needs.
This guide was produced in collaboration with the International Livestock Research Institute (ILRI)
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Mixed_Models_And_Multilevel_Data_Structures.pdf
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