05637nam 2200733 a 450 991102004990332120200520144314.09786611841003978128184100112818410059780470770771047077077597804707707880470770783(CKB)1000000000549390(EBL)366774(OCoLC)476201818(SSID)ssj0000206842(PQKBManifestationID)11180050(PQKBTitleCode)TC0000206842(PQKBWorkID)10246504(PQKB)10229985(MiAaPQ)EBC366774(PPN)263348644(Perlego)2772175(EXLCZ)99100000000054939020080124d2008 uy 0engur|n|---|||||txtccrMultivariable model-building a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables /Patrick Royston, Willi SauerbreiChichester, England ;Hoboken, NJ John Wileyc20081 online resource (323 p.)Wiley series in probability and statisticsDescription based upon print version of record.9780470028421 0470028424 Includes bibliographical references (p. 271-283) and index.Multivariable Model-Building; Contents; Preface; 1 Introduction; 1.1 Real-Life Problems as Motivation for Model Building; 1.1.1 Many Candidate Models; 1.1.2 Functional Form for Continuous Predictors; 1.1.3 Example 1: Continuous Response; 1.1.4 Example 2: Multivariable Model for Survival Data; 1.2 Issues in Modelling Continuous Predictors; 1.2.1 Effects of Assumptions; 1.2.2 Global versus Local Influence Models; 1.2.3 Disadvantages of Fractional Polynomial Modelling; 1.2.4 Controlling Model Complexity; 1.3 Types of Regression Model Considered; 1.3.1 Normal-Errors Regression1.3.2 Logistic Regression1.3.3 Cox Regression; 1.3.4 Generalized Linear Models; 1.3.5 Linear and Additive Predictors; 1.4 Role of Residuals; 1.4.1 Uses of Residuals; 1.4.2 Graphical Analysis of Residuals; 1.5 Role of Subject-Matter Knowledge in Model Development; 1.6 Scope of Model Building in our Book; 1.7 Modelling Preferences; 1.7.1 General Issues; 1.7.2 Criteria for a Good Model; 1.7.3 Personal Preferences; 1.8 General Notation; 2 Selection of Variables; 2.1 Introduction; 2.2 Background; 2.3 Preliminaries for a Multivariable Analysis; 2.4 Aims of Multivariable Models2.5 Prediction: Summary Statistics and Comparisons2.6 Procedures for Selecting Variables; 2.6.1 Strength of Predictors; 2.6.2 Stepwise Procedures; 2.6.3 All-Subsets Model Selection Using Information Criteria; 2.6.4 Further Considerations; 2.7 Comparison of Selection Strategies in Examples; 2.7.1 Myeloma Study; 2.7.2 Educational Body-Fat Data; 2.7.3 Glioma Study; 2.8 Selection and Shrinkage; 2.8.1 Selection Bias; 2.8.2 Simulation Study; 2.8.3 Shrinkage to Correct for Selection Bias; 2.8.4 Post-estimation Shrinkage; 2.8.5 Reducing Selection Bias; 2.8.6 Example; 2.9 Discussion2.9.1 Model Building in Small Datasets2.9.2 Full, Pre-specified or Selected Model?; 2.9.3 Comparison of Selection Procedures; 2.9.4 Complexity, Stability and Interpretability; 2.9.5 Conclusions and Outlook; 3 Handling Categorical and Continuous Predictors; 3.1 Introduction; 3.2 Types of Predictor; 3.2.1 Binary; 3.2.2 Nominal; 3.2.3 Ordinal, Counting, Continuous; 3.2.4 Derived; 3.3 Handling Ordinal Predictors; 3.3.1 Coding Schemes; 3.3.2 Effect of Coding Schemes on Variable Selection; 3.4 Handling Counting and Continuous Predictors: Categorization3.4.1 'Optimal' Cutpoints: A Dangerous Analysis3.4.2 Other Ways of Choosing a Cutpoint; 3.5 Example: Issues in Model Building with Categorized Variables; 3.5.1 One Ordinal Variable; 3.5.2 Several Ordinal Variables; 3.6 Handling Counting and Continuous Predictors: Functional Form; 3.6.1 Beyond Linearity; 3.6.2 Does Nonlinearity Matter?; 3.6.3 Simple versus Complex Functions; 3.6.4 Interpretability and Transportability; 3.7 Empirical Curve Fitting; 3.7.1 General Approaches to Smoothing; 3.7.2 Critique of Local and Global Influence Models; 3.8 Discussion; 3.8.1 Sparse Categories3.8.2 Choice of Coding SchemeMultivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed. This book proposes a systematic approach to building such models based on standard principles of statistical modeling. The main emphasis is on the fractional polynomial method for modeling the influence of continuous variables in a multivariable context, a topic for which there is no standard approach. Existing options range from very simple step functions to highly complex adaptive methods such as multivariate splines with many knots and penalisation. This new approaWiley series in probability and statistics.Regression analysisPolynomialsVariables (Mathematics)Regression analysis.Polynomials.Variables (Mathematics)519.5/36Royston Patrick1341128Sauerbrei Willi1839202MiAaPQMiAaPQMiAaPQBOOK9911020049903321Multivariable model-building4418364UNINA03712nam 22006255 450 991072628860332120260327143358.09783658407094365840709310.1007/978-3-658-40709-4(MiAaPQ)EBC30549265(Au-PeEL)EBL30549265(OCoLC)1380463377(DE-He213)978-3-658-40709-4(BIP)087520165(CKB)26742400600041(EXLCZ)992674240060004120230522d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierRacism in Schools History, Explanations, Impact, and Intervention Approaches /edited by Matthias Böhmer, Georges Steffgen1st ed. 2023.Wiesbaden :Springer Fachmedien Wiesbaden :Imprint: Springer,2023.1 online resource (203 pages)Print version: Böhmer, Matthias Racism in Schools Wiesbaden : Springer Fachmedien Wiesbaden GmbH,c2023 9783658407087 How to explain racist behaviors -- Effects of racist discrimination -- Recognizing, preventing, intervening: (self-)reflexive prevention and intervention approaches for a practice critical of racism in schools.Racism, i.e. discrimination against people on the basis of their perceived ethnic origin, is pervasive in schools. Apart from students, pre-service teachers and teachers, all actors in the school context are affected by this topic. Why is this so? How can racist discrimination be explained? What effects does this behavior have on those affected? And how can schools counteract it? These are all questions that arise and which this book aims to answer with the intention of enabling all those acting in the school context to critically examine their own knowledge bases relevant to racism. This book contributes to the development of school as a racism-sensitive space in which all actors behave in a racism-sensitive manner. Therefore, in addition to an overview of the history of racism, approaches to explaining racist behaviors and effects of racial discrimination, prevention and intervention approaches for a practice critical of racism in schools are presented. The editors Dr. Matthias Böhmer, graduate psychologist, is a psychological psychotherapist. He is an academic at several universities (since 2008 at the University of Luxembourg) and conducts research in the field of empirical educational research and on REBT. Dr. Georges Steffgen, graduate psychologist, is Professor of Social and Work Psychology at the University of Luxembourg and conducts research on aggression, emotion regulation and health promotion. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.School psychologyEducational psychologySchool PsychologyEducational PsychologyRacismethubIntervenció psicològicathubEscolesthubLlibres electrònicsthubSchool psychology.Educational psychology.School Psychology.Educational Psychology.RacismeIntervenció psicològicaEscoles370.89Böhmer Matthiasedt0Steffgen GeorgesedtMiAaPQMiAaPQMiAaPQBOOK9910726288603321Racism in Schools3373809UNINA