Abstract

Contents: Preface. Introduction. Bivariate Correlation and Regression. Multiple Regression/Correlation With Two or More Independent Variables. Data Visualization, Exploration, and Assumption Checking: Diagnosing and Solving Regression Problems I. Data-Analytic Strategies Using Multiple Regression/Correlation. Quantitative Scales, Curvilinear Relationships, and Transformations. Interactions Among Continuous Variables. Categorical or Nominal Independent Variables. Interactions With Categorical Variables. Outliers and Multicollinearity: Diagnosing and Solving Regression Problems II. Missing Data. Multiple Regression/Correlation and Causal Models. Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model. Random Coefficient Regression and Multilevel Models. Longitudinal Regression Methods. Multiple Dependent Variables: Set Correlation. Appendices: The Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements. Determination of the Inverse Matrix and Applications Thereof.

Keywords

CorrelationStatisticsRegression analysisPsychologyMathematics

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Year
2014
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book
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20846
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Closed

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Patricia Cohen, Patricia Cohen, Stephen G. West et al. (2014). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Psychology Press eBooks . https://doi.org/10.4324/9781410606266

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DOI
10.4324/9781410606266