Titlebook: Experimental Design and Model Choice; The Planning and Ana Helge Toutenburg Book 1995 Springer-Verlag Berlin Heidelberg 1995 Experimental D

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https://doi.org/10.1007/978-3-663-08043-5eral statistical procedures for testing and analysing data. These procedures require a large amount of computation, especially in case of complicated classifications. For this reason, these procedures are available as software.

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Single-Factor Experiments with Fixed and Random Effects,eral statistical procedures for testing and analysing data. These procedures require a large amount of computation, especially in case of complicated classifications. For this reason, these procedures are available as software.

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Statistical Analysis of Incomplete Data,garded as the pioneer of modern theory of .. Little and Rubin (1987) and Rubin (1987) have discussed fundamental concepts for handling missing data based on decision theory and models for the mechanism of nonresponse.

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978-3-642-52500-1Springer-Verlag Berlin Heidelberg 1995

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https://doi.org/10.1007/978-3-658-44220-0 observation or may be the outcomes of a controlled experiment. In the latter case, randomization plays a crucial role in gaining information about possible differences in the samples which may be due to a specific factor. Randomization means, for example, that in a controlled clinical trial there i

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https://doi.org/10.1007/978-3-8349-6670-4observed (clinical population: stratified according to patient’s age, degree of disease, etc.). If we have such prior information then a gain in efficiency compared to the completely randomized experiment is possible by grouping into blocks. The experimental units are grouped together in homogeneous

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