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Fortgeschrittene Verfahren der Längsschnittanalyse: Ereignisanalyse II Diskrete Modelle (Vorlesung) Introduction to History Analysis II – Discrete-Time Models
- Prof. Dr. Hans-Peter Blossfeld
2,00 SWS, Vorlesung mit zugehöriger Übung
Zeit und Ort: Di 14:00 - 16:00, FMA/00.07
vom 15.10.2018 bis zum 9.2.2019
- Over the last two decades, social scientists have been collecting and analyzing event history data with increasing frequency. Illustrative examples of this type of substantive process can be given for a wide variety of social research fields: in labor market studies, workers move between unemployment and employment, full-time and part-time work, or among various kinds of jobs; in social inequality studies, people become a home-owner over the life course; in demographic analyses, men and women enter into consensual unions, marriages, or into father/motherhood, or are getting a divorce; in sociological mobility studies, employees shift through different occupations, social classes, or industries; in studies of organizational ecology, firms, unions, or organizations are founded or closed down; in political science research, governments break down, voluntary organizations are founded, or countries go through a transition from one political regime to another; in migration studies, people move between different regions or countries; in marketing applications, consumers switch from one brand to another or purchase the same brand again; in criminological studies, prisoners are released and commit another criminal act after some time; in communication analysis, interaction processes such as inter- personal and small group processes are studied; in educational studies, students drop out of school before completing their degrees, enter into a specific educational track, or later in the life course, start a program of further education; in analyses of ethnic conflict, incidences of racial and ethnic confrontation, protest, riot, and attack are studied; etc.
Depending on theoretical considerations about the process time axis and the degree of measurement accuracy of event times, the literature often distinguishes between discrete-time and continuous-time event history models. Discrete-time event history methods (1) either theoretically presuppose a discrete process time axis, i.e. that the events can only occur at fixed time intervals; (2) or they assume a continuous process time axis, i.e. that events can happen at any point in time, but that the measurement of these event times could only be achieved in a sequence of quite crude time intervals. For example, in some national panel studies events such as job shifts are only recorded as happening in yearly intervals. Various publications on discrete-time models are available in the literature. In the seminar, we use Yamaguchi (1991), Singer and Willett (1993), Blossfeld and Blossfeld (2015a) as well as Blossfeld and Blossfeld (2015b).
The aim of the lecture (2 hours) with exercises (2 hours) in the WS 2018/19 is first to continue and finish the presentation of continuous-time event history models (e.g., parametric models of time-dependence such as the Gompertz, the Weibull, the Log-Logistic, the Log-Normal, and the semi-parametric models such as the Cox model). Then the students will be introduced into discrete-time event history analysis, including descriptions of data preparation and various discrete-time models. We will in detail discuss the analysis of aggregated data and the potential impact of aggregation on the estimated coefficients of time-constant and time-varying covariates. All discrete-time models are demonstrated on the basis of various concrete application examples in the social sciences.
It is certainly helpful but not necessary that students took part in the SS 2018 lecture/exercises on continuous-time event history analysis. However, researchers are expected to have a basic knowledge of Stata. Students also have the possibility to discuss analysis problems and present their own event history applications. Participants can get credits by submitting defined exercises that will be specified during the course. The Stata computer exercises will be given by Dr. Gwendolin J. Blossfeld. She will also assist students if they have Stata problems and help them in making their exercises. More details on the assignments will be given during the introductory meetings.
Depending on participants’ requests, the lectures/exercises will be given in German or English.
- Empfohlene Literatur
- Blossfeld, H-P., and Blossfeld, G.J. (2015a) Life Course and Event History Analysis. In: James D. Wright (ed.), International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Vol 14. Oxford: Elsevier. pp. 51–58.
Blossfeld, H-P., and Blossfeld, G.J. (2015b) Event History Analysis, in: Henning Best and Christof Wolf (eds.): the Sage Handbook of Regression Analysis and Causal Infernece, Los Angeles (CA) et al. 359-385.
Blossfeld, H.-P., K. Golsch, and G. Rohwer (2007): Event History Analysis with Stata, Mahwah (NJ) and London: Erlbaum, pp. 182-215 and 223-270.
Singer, Judith D., and John B. Willett (1993): “It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events.” Journal of Educational Statistics, 18: 155-195.
Yamaguchi, Kazuo. 1991. “Event History Analysis.” Newbury Park: Sage, pp. 1-28.
- Englischsprachige Informationen:
- Credits: 6
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 15
- Institution: Lehrstuhl für Soziologie I
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