Analyzing Repeated Surveys (Quantitative Applications in the - download pdf or read online

By Glenn Firebaugh

ISBN-10: 0585216738

ISBN-13: 9780585216737

ISBN-10: 0803973985

ISBN-13: 9780803973985

Repeated surveys -- a method for asking an analogous inquiries to various samples of individuals -- permits researchers the chance to investigate alterations in society as a complete. This e-book starts with a dialogue of the vintage factor of ways to split cohort, interval, and age results. It then covers equipment for modeling mixture tendencies; equipment for estimating cohort replacement's contribution to combination traits, a decomposition version for clarifying how microchange contributes to combination switch, and easy types which are worthy for the review of adjusting individual-level results.

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Extra resources for Analyzing Repeated Surveys (Quantitative Applications in the Social Sciences)

Example text

The CPS and the Survey on Income and Program Participation (SIPP) are examples of rotating panel surveys. A second hybrid, the "split panel survey" (Duncan & Kalton, 1987), solves the problem of estimating gross change in repeated surveys by adding a panel component to repeated surveys. The British Social Attitudes Survey is an example of a split panel survey. The NES is partially a split panel survey, because it includes panel components for selected surveys (Kiecolt & Nathan, 1985). Kish (1983, 1986) recommends the use of split panel designs, and split designs and other hybrids likely will become more common in the future.

3 demonstrates, the period coefficient is the sum of the period effect and the age effect, bp + bA, whereas the cohort coefficient is the difference between the cohort effect and the age effect, bCbA. 3 yield unbiased estimates of period and cohort effects only if the age effect is in fact zero; otherwise, the coefficient for period reflects age as well as period effects, and the coefficient for cohort reflects age as well as cohort effects. Other identifying assumptions could be made. For example, Mason, Mason, Winsborough, and Poole (1973) show that estimates of age, period, and cohort effects in categorical data analysis can be obtained by constrain- Page 10 ing selected adjacent cohorts (or ages, or periods) to be the same.

I rely on that template in this book, especially in the discussion of aggregate change (Chapters 3 and 4). Because those chapters borrow heavily from fundamental concepts of cohort analysis, in this chapter I briefly review those concepts. I begin by defining cohort effects and distinguishing them from age effects and period effects. Then I describe different approaches to the thorny problem of how to separate cohort, period, and age effects empirically. Readers already familiar with cohort analysis can go directly to the discussion of how to disentangle age, period, and cohort effects.

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Analyzing Repeated Surveys (Quantitative Applications in the Social Sciences) by Glenn Firebaugh


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