Graduate Thesis Or Dissertation
 

Analysis of enumerative data in randomized block designs

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/x633f427j

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  • Randomized block designs are often modeled by fixed treatment effects, an additive random effect that is shared by all observations in the same block, and a second random effect accounting for the residual variation. With enumerative data, the residual variation may be related to the treatment and block effects in a complex way. A two-stage model is presented, in which the parameter of a binomial or Poisson count is some one-to-one function of the outcome of the usual randomized block linear model. The implications of this model for analyses of variance are discussed, and some extensions of binomial and Poisson weighted least squares methods to overdispersed counts are adapted to the randomized block situation. Variations of the ANOVA and weighted least squares approaches are discussed and compared on a binomial and a Poisson example, and both approaches are compared to a direct maximum likelihood method on several simulated data sets.
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