A primer in longitudinal data analysis / Toon Taris.

Format:

Book

Author/Creator:

Taris, Toon.

Language:

English

Subjects (All):

Longitudinal method.

Physical Description:

ix, 163 pages : illustrations ; 24 cm

Place of Publication:

London ; Thousand Oaks, Calif. : SAGE, 2000.

Summary:

What is longitudinal data analysis and how do you do it? What are its strengths and weaknesses? This is the first accessible introduction to longitudinal data analysis. It is a survival kit, presenting the basics of how to conduct longitudinal research and covering the stages of the process. Written in a clear and engaging style, the book helps you to choose the right longitudinal design for your research. It shows you how to deal with topics such as (non-random) nonresponse and droput; the measurement invariance of factor structures; issues in discrete-time panel analysis (assessing causality, change scores, regression to the mean); repeated-measures analysis and profile analysis; survival analysis; and the analysis of sequences. While the book provides a broad overview of the field, the focus is always on the practical issues arising out of longitudinal research. Supplying everything you need to get started, it acts as a manual of opportunities and pitfalls. It is the ideal primer for this growing area of social research.

Contents:

1 Longitudinal Data and Longitudinal Designs 1

Covariation and causation 2

Designs for collecting longitudinal data 5

2 Nonresponse in Longitudinal Research 17

Nonresponse in cross-sectional and longitudinal designs 17

Better safe than sorry: minimizing nonresponse and attrition 22

Detecting selective nonresponse 27

Dealing with nonresponse 30

3 Measuring Concepts Across Time: Issues of Stability and Meaning 39

What do we talk about when we talk about stability and change? 39

Types of change and stability 40

Exploratory vs confirmatory factor analysis 45

Using the confirmatory factor-analytic model to assess structural invariance 46

Example: loneliness across young adulthood 48

4 Issues in Discrete-Time Panel Analysis 55

Measuring change in discrete time 55

Dependence on initial values: the sophomore slump 56

Change scores: what is the difference? 59

The regressor variable approach, and the return of the difference score 62

Example: income determination among men and women 65

Assessing causal direction across time: cross-lagged panel analysis 67

5 Analysis of Repeated Measures 75

Examining across-time growth 75

Analysis of variance: some basics 76

Analysis of variance for longitudinal survey data 84

Example: mental well-being of young workers across time 88

6 Analyzing Durations 93

Survival-, failure time-, and event history-analysis 93

Survival data 95

Continuous-time survival analysis: hazard function and survival function 98

Analysis of covariates: the stratification approach 102

Parametric and semi-parametric approaches to analyzing covariates 105

Example: continuity of women's employment after childbirth 112

Continuous-time survival analysis: evaluation and discussion 113

Discrete-time survival analysis 114

Example: the transition towards non-virginity 116

7 Analyzing Sequences 121

Event- vs career-centered modes of analysis 121

Measuring career change: characterizing development 122

Illustration: sensation seeking, job characteristics and mobility 124

Creating classifications of careers: distance-based methods 128

Same-order methods: sequencing careers 138.

Notes:

Includes bibliographical references and index.

ISBN:

0761960260

0761960279

OCLC:

43377952