Inhalt
This book advocates an exploratory approach to survey data analysis, rather than confirmatory approaches, which many other textbooks explicitly or implicitly recommend.
Most survey data, especially attitudinal data, might not be suitable for causal analysis. Descriptive analyses of survey data will, however, expand our understanding of the social mechanisms in which people's attitudes and beliefs mediate institutional settings and their actions. Thus, we should pursue an exploratory approach when studying social processes in terms of survey data analysis. In this approach, hypothesis tests, significance tests, or statistical modeling should be used in a way that serves to continually expand on and refine our theoretical hypotheses on social mechanisms.
This book presents essential tools for this approach. It summarizes key statistical methods including multidimensional scaling, latent class analysis, loglinear analysis, and multilevel analysis. It also highlights representative analyses concerning sociological and social psychological topics, such as the relationship between life satisfaction and social status, configuration of attitudes toward child-rearing, moral judgment in developmental processes, gender role attitudes through different life stages, and subjective social position in the era of globalization.
Bibliografische Angaben
März 2025, ca. 300 Seiten, Behaviormetrics: Quantitative Approaches to Human Behavior, Englisch
Springer Nature EN
978-981-1307-30-0