Abstract
Data arising from repeated measurements of experimental units occur in many occasions in forestry and related fields. Very often such data are analysed without considering their several peculiarities, like correlation between successive measurements and heterogeneity of variances, which may lead to erroneous conclusions. The present study was undertaken with the objective of identifying appropriate methods of analysis of data from long term trials characterised by repeated measurements on experimental units. In this study, three different methods of analysing repeated measures, viz., two way analysis of variance, univariate mixed model analysis of variance and multivariate analysis of variance methods were compared using data collected from a study on several soil properties observed from multiple core samples from 0-15, 15-50 and 50-100 cm layers under six different types of vegetation and another study on annual yield of latex from rubber trees in three years and the appropriate methods of analysis to be followed in respective cases were identified. The study revealed that multivariate analysis of variance is the most appropriate method of analysis for majority of the soil properties as well as for annual yield of latex from rubber trees.
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