Stata for the Behavioral Sciences

Bibliographic Details
Title:	Stata for the Behavioral Sciences
Description:	Stata for the Behavioral Sciences, by Michael Mitchell, is the ideal reference for researchers using Stata to fit ANOVA models and other models commonly applied to behavioral science data. Drawing on his education in psychology and his experience in consulting, Mitchell uses terminology and examples familiar to the reader as he demonstrates how to fit a variety of models, how to interpret results, how to understand simple and interaction effects, and how to explore results graphically. Although this book is not designed as an introduction to Stata, it is appealing even to Stata novices. Throughout the text, Mitchell thoughtfully addresses any features of Stata that are important to understand for the analysis at hand. He also is careful to point out additional resources such as related videos from Stata's YouTube channel. The book is divided into five sections. The first section contains a chapter that introduces Stata commands for descriptive statistics and another that covers basic inferential statistics such as one- and two-sample t tests. The second section focuses on between-subjects ANOVA modeling. The discussion moves from one-way ANOVA models to ANCOVA models to two-way and three-way ANOVA models. In each case, special attention is given to the use of commands such as contrast and margins for testing specific hypotheses of interest. Mitchell also emphasizes the understanding of interactions through contrasts and graphs. Underscoring the importance of planning any experiment, he discusses power analysis for t tests, for one- and two-way ANOVA models, and for ANCOVA models. Section three of the book extends the discussion in the previous section to models for repeated-measures data and for longitudinal data. The fourth section of the book illustrates the use of the regress command for fitting multiple regression models. Mitchell then turns his attention to tools for formatting regression output, for testing assumptions, and for model building. This section ends with a discussion of power analysis for simple, multiple, and nested regression models. The final section has a tone that differs from the first four. Rather than focusing on a particular type of analysis, Mitchell describes elements of Stata. He first discusses estimation commands and similarities in syntax from command to command. Then, he details a set of postestimation commands that are available after most estimation commands. Another chapter provides an overview of data management commands. This section ends with a chapter that will be of particular interest to anyone who has used IBM® SPSS®; it lists commonly used SPSS® commands and provides equivalent Stata syntax. This book is an easy-to-follow guide to analyzing data using Stata for researchers in the behavioral sciences and a valuable addition to the bookshelf of anyone interested in applying ANOVA methods to a variety of experimental designs.
Authors:	Michael N. Mitchell
Resource Type:	eBook.
Subjects:	Psychology--Graphic methods--Computer programs, Statistics--Computer programs, Psychology--Statistical methods--Computer programs, Social sciences--Statistical methods--Computer programs, Social sciences--Graphic methods--Computer programs
Categories:	PSYCHOLOGY / Statistics
Database:	eBook Index

FullText	Text: Availability: 0
Header	DbId: edsebk DbLabel: eBook Index An: 2718821 RelevancyScore: 918 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 918.373718261719
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Items	– Name: Title Label: Title Group: Ti Data: Stata for the Behavioral Sciences – Name: Abstract Label: Description Group: Ab Data: Stata for the Behavioral Sciences, by Michael Mitchell, is the ideal reference for researchers using Stata to fit ANOVA models and other models commonly applied to behavioral science data. Drawing on his education in psychology and his experience in consulting, Mitchell uses terminology and examples familiar to the reader as he demonstrates how to fit a variety of models, how to interpret results, how to understand simple and interaction effects, and how to explore results graphically. Although this book is not designed as an introduction to Stata, it is appealing even to Stata novices. Throughout the text, Mitchell thoughtfully addresses any features of Stata that are important to understand for the analysis at hand. He also is careful to point out additional resources such as related videos from Stata's YouTube channel. The book is divided into five sections. The first section contains a chapter that introduces Stata commands for descriptive statistics and another that covers basic inferential statistics such as one- and two-sample t tests. The second section focuses on between-subjects ANOVA modeling. The discussion moves from one-way ANOVA models to ANCOVA models to two-way and three-way ANOVA models. In each case, special attention is given to the use of commands such as contrast and margins for testing specific hypotheses of interest. Mitchell also emphasizes the understanding of interactions through contrasts and graphs. Underscoring the importance of planning any experiment, he discusses power analysis for t tests, for one- and two-way ANOVA models, and for ANCOVA models. Section three of the book extends the discussion in the previous section to models for repeated-measures data and for longitudinal data. The fourth section of the book illustrates the use of the regress command for fitting multiple regression models. Mitchell then turns his attention to tools for formatting regression output, for testing assumptions, and for model building. This section ends with a discussion of power analysis for simple, multiple, and nested regression models. The final section has a tone that differs from the first four. Rather than focusing on a particular type of analysis, Mitchell describes elements of Stata. He first discusses estimation commands and similarities in syntax from command to command. Then, he details a set of postestimation commands that are available after most estimation commands. Another chapter provides an overview of data management commands. This section ends with a chapter that will be of particular interest to anyone who has used IBM® SPSS®; it lists commonly used SPSS® commands and provides equivalent Stata syntax. This book is an easy-to-follow guide to analyzing data using Stata for researchers in the behavioral sciences and a valuable addition to the bookshelf of anyone interested in applying ANOVA methods to a variety of experimental designs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Michael+N%2E+Mitchell%22">Michael N. Mitchell</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Psychology--Graphic+methods--Computer+programs%22">Psychology--Graphic methods--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics--Computer+programs%22">Statistics--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Psychology--Statistical+methods--Computer+programs%22">Psychology--Statistical methods--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Social+sciences--Statistical+methods--Computer+programs%22">Social sciences--Statistical methods--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Social+sciences--Graphic+methods--Computer+programs%22">Social sciences--Graphic methods--Computer programs</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22PSYCHOLOGY+%2F+Statistics%22">PSYCHOLOGY / Statistics</searchLink>
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RecordInfo	BibRecord: BibEntity: Classifications: – Code: 300.28555 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Psychology--Graphic methods--Computer programs Type: general – SubjectFull: Statistics--Computer programs Type: general – SubjectFull: Psychology--Statistical methods--Computer programs Type: general – SubjectFull: Social sciences--Statistical methods--Computer programs Type: general – SubjectFull: Social sciences--Graphic methods--Computer programs Type: general Titles: – TitleFull: Stata for the Behavioral Sciences Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Michael N. Mitchell – PersonEntity: Name: NameFull: Michael N. Mitchell IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2015 – D: 31 M: 08 Type: profile Y: 2021 Identifiers: – Type: isbn-print Value: 9781597181730 – Type: isbn-electronic Value: 9781597181983 Titles: – TitleFull: Stata for the Behavioral Sciences Type: main
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