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Hans-Peter Blossfetd, Alfred Hamerle, and Karl Ulrich Mayer. Event History Analysis. Statistical Theory and Applications in the Social Sciences. Hillsdale, N J: Lawrence Erlbaum Associates, 1989, 297 pp.

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Hans-Peter Blossfetd, Alfred Hamerle, and Karl Ulrich Mayer. Event History Analysis. Statistical Theory and Applications in the Social Sciences. Hillsdale, N J: Lawrence Erlbaum Associates, 1989, 297 pp.

Published online by Cambridge University Press:  01 January 2025

Trond Petersen
Trond Petersen*
Affiliation:
University of California, Berkeley
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Type
Book-Review
Information
Psychometrika , Volume 57 , Issue 1 , March 1992 , pp. 158 - 159
Copyright
Copyright © 1992 The Psychometric Society

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References

Allison, P. D. (1984). Event History Analysis. Regression for Longitudinal Event Data, Beverly Hills: Sage.Google Scholar
Cox, D. R., Oakes, D. (1984). Survival analysis, London: Chapman and Hall.Google Scholar
Hamerle, A. (1991). On the treatment of interrupted spells and initial conditions in event history analysis. Sociological methods and research, 19, 388–414.CrossRefGoogle Scholar
Hoem, J. M. (1985). Weighting, misclassification, and other issues in the analysis of survey samples of life histories. In Heckman, J. J., Singer, B. (Eds.), Longitudinal analysis of labor market data (pp. 249–283). New York: Cambridge University Press.CrossRefGoogle Scholar
Kalbfleisch, J. D., Prentice, R. L. (1980). The statistical analysis of failure time data, New York: Wiley.Google Scholar
Lancaster, T. (1990). The econometric analysis of transition data, New York: Cambridge University Press.CrossRefGoogle Scholar
Petersen, T. (1988). Analyzing change over time in a continuous dependent variable: Specification and estimation of continuous state space hazard rate models. In Clogg, C. C. (Eds.), Sociological Methodology 1988 (pp. 137–164). Washington, DC: American Sociological Association.Google Scholar
Petersen, T. (1990). Analyzing event histories. In von Eye, A. (Eds.), New statistical methods in longitudinal research (pp. 258–288). Orlando, FL: Academic Press.Google Scholar
Petersen, T. (1990). Analyzing continuous state space failure time processes: Two further results. Journal of Mathematical Sociology, 10, 247–256.CrossRefGoogle Scholar
Petersen, T. (1991). The statistical analysis of event histories. Sociological Methods and Research, 19, 270–323.CrossRefGoogle Scholar
Petersen, T. (1991). Time-aggregation bias in continuous-time hazard-rate models. In Marsden, P. V. (Eds.), Sociological methodology 1991 (pp. 263–290). Cambridge, MA: Basil Blackwell.Google Scholar
Tuma, N. B., Hannan, M. T. (1984). Social dynamics. Models and methods, Orlando, FL: Academic Press.Google Scholar
Yamaguchi, K. (1991). Event history analysis, Newbury Park, CA: Sage.Google Scholar