Screen LibraryApplied longitudinal data analysis : modeling change and event occurrence /
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| Main Authors: | |
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| Corporate Authors: | |
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| Published: |
Oxford University Press,
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| Publisher Address: | Oxford ; New York : |
| Publication Dates: | 2009. |
| Literature type: | eBook |
| Language: | English |
| Subjects: | |
| Online Access: |
http://www.iresearchbook.cn/f/ebook/detail?id=0bf24dfa807b49c1a1b2d45d637f433f |
| Carrier Form: | 1 online resource (xx, 644 pages) : ill |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9780199760725 9780195152968 |
| Index Number: | H62 |
| CLC: | C32 |
| Contents: |
A Framework for Investigating Change over Time -- When Might You Study Change over Time? -- Distinguishing Between Two Types of Questions about Change -- Three Important Features of a Study of Change -- Exploring Longitudinal Data on Change -- Creating a Longitudinal Data Set -- Descriptive Analysis of Individual Change over Time -- Exploring Differences in Change across People -- Improving the Precision and Reliability of OLS-Estimated Rates of Change: Lessons for Research Design -- Introducing the Multilevel Model for Change -- What Is the Purpose of the Multilevel Model for Change? -- The Level-1 Submodel for Individual Change -- The Level-2 Submodel for Systematic Interindividual Differences in Change -- Fitting the Multilevel Model for Change to Data -- Examining Estimated Fixed Effects -- Examining Estimated Variance Components -- Doing Data Analysis with the Multilevel Model for Change -- Example: Changes in Adolescent Alcohol Use -- The Composite Specification of the Multilevel Model for Change -- Methods of Estimation, Revisited -- First Steps: Fitting Two Unconditional Multilevel Models for Change -- Practical Data Analytic Strategies for Model Building -- Comparing Models Using Deviance Statistics -- Using Wald Statistics to Test Composite Hypotheses About Fixed Effects -- Evaluating the Tenability of a Model's Assumptions -- Model-Based (Empirical Bayes) Estimates of the Individual Growth Parameters -- Treating TIME More Flexibly -- Variably Spaced Measurement Occasions -- Varying Numbers of Measurement Occasions. |