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Stratification, covariance and weight gain in experiments with repeated observations

Published online by Cambridge University Press:  27 March 2009

E. A. Roberts
E. A. Roberts
Affiliation:
Biometrical Branch, N.S.W. Department of Agriculture, McKell Building, Rawson Place, Sydney 2000, Australia
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Summary

The use of weight gain in long-term experiments can produce serious bias in treatment comparisons unless the initial weights of treatment groups are equal or nearly so. When observations are repeated on the same experimental unit, covariance analysis of the data for each occasion produces treatment comparisons adjusted by the regression on the covariate at that time; polynomial trends in these adjusted comparisons with time can be easily calculated even though the regression on the covariate varies with time.

Type
Research Article
Information
The Journal of Agricultural Science , Volume 95 , Issue 1 , August 1980 , pp. 141 - 145
Copyright
Copyright © Cambridge University Press 1980

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References

Björnsson, H. (1978). Analysis of a series of long-term grassland experiments with autocorrelated errors. Biometrics 34, 645–651.Google Scholar
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Roberts, E. A. (1975). Accounting for components of error. In Developments in Field Experiment Design and Analysis, (ed. Bofinger, V. J. and Wheeler, J. L.), pp. 59–71. Commonwealth Agricultural Bureau.Google Scholar
Rowell, J. G. & Walters, D. E. (1976). Analysing data with repeated observations on each experimental unit. Journal of Agricultural Science, Cambridge 87, 423–432.CrossRefGoogle Scholar