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