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Data analysis : a model comparison approach to regression, ANOVA, and beyond / Charles M. Judd, University of Colorado, Gary H. McClelland, University of Colorado, Carey S. Ryan, University of Nebraska at Omaha.

By: Judd, Charles M., author.
Contributor(s): McClelland, Gary H.,, 1947- author. | Ryan, Carey S., author.
Call number: QA276 J83 2017 Material type: TextTextPublisher: New York : Routledge, Taylor & Francis Group, 2017Edition: Third Edition.Description: xii, 366 pages : illustrations ; 26 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781138819825 (hardback : alk. paper) ; 1138819824 (hardback : alk. paper) ; 9781138819832 (pbk. : alk. paper) ; 1138819832 (pbk. : alk. paper) ; 9781315744131 (ebook) (Invalid ISBN) Subject(s): Mathematical statisticsDDC classification: 519.5/36
Contents:
Preface -- Introduction to data analysis -- Simple models: definitions of error and parameter estimates -- Simple models: models of error and sampling distributions -- Simple models: statistical inferences about parameter values -- Simple regression: estimating models with a single continuous predictor -- Multiple regression: models with multiple continuous predictors -- Moderated and nonlinear regression models -- One-way anova: models with a single categorical predictor -- Factorial anova: models with multiple categorical predictors and product terms -- Ancova: models with continuous and categorical predictors -- Repeated measures anova: models with nonindependent errors -- Incorporating continuous predictors with nonindependent data: towards mixed models -- Outliers and ill-mannered error -- Logistic regression -- References -- Appendices -- Author index -- Subject index.
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ODI General Collection QA276 J83 2017 (Browse shelf) 1 1000522661 Available

Revised edition of Data analysis, 2007.

Includes bibliographical references (pages 254-255) and indexes.

Preface -- Introduction to data analysis -- Simple models: definitions of error and parameter estimates -- Simple models: models of error and sampling distributions -- Simple models: statistical inferences about parameter values -- Simple regression: estimating models with a single continuous predictor -- Multiple regression: models with multiple continuous predictors -- Moderated and nonlinear regression models -- One-way anova: models with a single categorical predictor -- Factorial anova: models with multiple categorical predictors and product terms -- Ancova: models with continuous and categorical predictors -- Repeated measures anova: models with nonindependent errors -- Incorporating continuous predictors with nonindependent data: towards mixed models -- Outliers and ill-mannered error -- Logistic regression -- References -- Appendices -- Author index -- Subject index.

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