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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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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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Multifactor Experiments,ognostic factors. If these variables are continuous, their influence on the response is taken into account by so-called factor levels. These are ranges ( e.g., low, medium, high) that classify the continuous variables as ordinal variables. In Sections 1.7 and 1.8, we have already cited examples for
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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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Modelling Support for Design of Safety-Critical Automotive Embedded Systemsy Case development in close connection to the system model; (3) Analysis of mal-functional behaviour that may cause hazards, by modelling of errors and error propagation in a (complex and hierarchical) system model.
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