Applied Multiple Regression pot

[...]... 13.2.17 Regression Diagnostics in Logistic Regression 512 13.2.18 SparsenessofData 516 13.2.19 Classification of Cases 516 Extensions of Logistic Regression to Multiple Response Categories: Polytomous Logistic Regression and Ordinal Logistic Regression 519 13.3.1 Polytomous Logistic Regression 519 13.3.2 Nested Dichotomies 520 13.3.3 Ordinal Logistic Regression 522 Models for Count Data: Poisson Regression. .. and technologies 1.1.2 Testing Hypotheses Using Multiple Regression/ Correlation: Some Examples Multiple regression analysis is broadly applicable to hypotheses generated by researchers in the behavioral sciences, health sciences, education, and business These hypotheses may come from formal theory, previous research, or simply scientific hunches Consider the following hypotheses chosen from a variety... data analysis in the behavioral sciences: Statistical issues Hillsdale, NJ: Erlbaum Applied Multiple Regression/ Correlation Analysis for the Behavioral Sciences Third Edition This page intentionally left blank 1 Introduction 1.1 MULTIPLE REGRESSION/ CORRELATION AS A GENERAL DATA-ANALYTIC SYSTEM 1.1.1 Overview Multiple regression/ correlation analysis (MRC) is a highly general and therefore very flexible... of flexibility and ease of use that have made multiple regression analysis even more accessible However, this increased accessibility has also increased the risk that multiple regression may be used in a mindless manner by those unfamiliar with its basic concepts This development made the need for continued clear coverage of the basic concepts of multiple regression even more apparent Because Jack and... Logistic Regression 492 13.2.6 Multiple Logistic Regression 493 13.2.7 Numerical Example 494 13.2.8 Confidence Intervals on Regression Coefficients and Odds Ratios 497 13.2.9 Estimation of the Regression Model: Maximum Likelihood 498 13.2.10 Deviances: Indices of Overall Fit of the Logistic Regression Model 499 13.2 1 1 Multiple R2 Analogs in Logistic Regression 502 13.2.12 Testing Significance of Overall... Linear Regression Applied to Count Data 525 13.4.2 Poisson Probability Distribution 526 13.4.3 Poisson Regression Analysis 528 13.4.4 Overdispersion and Alternative Models 530 13.4.5 Independence of Observations 532 13.4.6 Sources on Poisson Regression 532 Full Circle: Parallels Between Logistic and Poisson Regression, and the Generalized Linear Model 532 13.5.1 Parallels Between Poisson and Logistic Regression. .. 13: Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model 13.1 13.2 Ordinary Least Squares Regression Revisited 479 13.1.1 Three Characteristics of Ordinary Least Squares Regression 480 13.1.2 The Generalized Linear Model 480 13.1.3 Relationship of Dichotomous and Count Dependent Variables Y to a Predictor 481 Dichotomous Outcomes and Logistic Regression 482 1... Linear Regression: The Linear Probability Model and Discriminant Analysis 483 13.2.2 The Nonlinear Transformation From Predictor to Predicted Scores: Probit and Logistic Transformation 485 13.2.3 The Logistic Regression Equation 486 13.2.4 Numerical Example: Three Forms of the Logistic Regression Equation 487 13.2.5 Understanding the Coefficients for the Predictor in Logistic Regression 492 13.2.6 Multiple. .. Quantitative Scales, Curvilinear Relationships, and Transformations Introduction 193 6.1.1 What Do We Mean by Linear Regression? 193 193 xii CONTENTS 6.1.2 6.2 6.3 6.4 Linearity in the Variables and Linear Multiple Regression 194 Four Approaches to Examining Nonlinear Relationships 6.1.3 in Multiple Regression 195 Power Polynomials 196 6.2.1 Method 196 An Example: Quadratic Fit 198 6.2.2 Centering Predictors... Summary 450 Chapter 12: Multiple Regression/ Correlation and Causal Models 12.1 12.2 12.3 12.4 12.5 12.6 XVii Introduction 452 12.1.1 Limits on the Current Discussion and the Relationship Between Causal Analysis and Analysis of Covariance 452 12 1 2 Theories and Multiple Regression/ Correlation Models That Estimate and Test Them 454 12.1.3 Kinds of Variables in Causal Models 457 1 2 1 4 Regression Models as . Applied Multiple Regression/ Correlation Analysis for the Behavioral Sciences Third Edition This page intentionally left blank Applied Multiple Regression/ Correlation Analysis . Data Applied multiple regression/ correlation analysis for the behavioral sciences 3rd ed./ Jacob Cohen [et al] p. cm. Rev. ed. of: Applied multiple