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- W1706060364 abstract "This chapter discusses the inference based on conditionally specified univariate analysis of variance (ANOVA) models incorporating preliminary testing. The specification of a particular mathematical model may be either (1) unconditionally specified or (2) conditionally specified. For both model specifications, inferences made regarding the unknown parameters actually select a particular subclass of the particular reasonable model specification. In the case of unconditionally specified models, such a selection is made in one step; while for conditionally specified models, the final selection is made after one or more steps in accordance with the number of preliminary tests. It is well known that ANOVA models can be interpreted as special cases of the general linear model. Multiple regressions and polynomial regression are two other types of statistical methods, which also may make the use of the general linear model and inferences based on conditionally specified ANOVA models incorporating preliminary testing. In particular, such a model and inference procedures would be appropriate when an investigator is uncertain whether or not to include a suspected subset of regressors in multipleregression, or in the case of polynomial regression, uncertain as to the degree of polynomial to fit to available data. The model specification and particular inference theory used by an investigator should be determined by circumstances peculiar to each research investigation." @default.
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- W1706060364 date "1980-01-01" @default.
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- W1706060364 title "13 Inference based on conditionally specified ANOVA models incorporating preliminary testing" @default.
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