Titlebook: Regression-Based Normative Data for Psychological Assessment; A Hands-On Approach Wim Van der Elst Book 2024 The Editor(s) (if applicable)

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Normative Data Accounting for a Binary Independent Variable,wo possible outcome levels, such as Gender) has to be accounted for in the norms. Some important concepts of regression analysis that are relevant in a normative data context are discussed, such as the sampling distribution of an estimated parameter and inferential procedures for the mean structure

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Normative Data Accounting for a Non-binary Qualitative Independent Variable,l of Education, with outcome values low, average, and high). It is explained that the inferential procedure that is based on . test statistics (see Chap. .) is suboptimal in this setting, because the evaluation of the effect of a non-binary qualitative independent variable requires the testing of mu

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Normative Data Accounting for Multiple Qualitative and/or Quantitative Independent Variables,it often occurs that several independent variables have to be considered in a normative analysis (e.g., Age, Gender, and/or Level of Education). This chapter focuses on such settings. The general multiple linear regression model is introduced, and the important distinction between additive and inter

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Quantifying Uncertainty in Regression-Based Norms,evel) relative position of a test score. Indeed, there is always uncertainty in the estimated percentile ranks because the population distribution of the raw test scores is unknown. This chapter introduces a bootstrap procedure that allows for quantifying the uncertainty in the percentile ranks (in

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Dynamic and Steady-State Analysis of Switching Power Converters Made Easy: Complementarity Formalismrnal if forced by directly manipulable control variables, and internal if determined by state dependent conditions. The presence of internal switchings makes it difficult to know a priori the sequence of modes and also open loop steady-state behaviours are difficult to obtain. In this chapter, it is