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"This paper will investigate the issue of weighting for panel attrition in event-history models by comparing alternative treatments of sampling weights in a divorce model for members of the 1986 [U.S.] Survey of Income and Program Participation (SIPP). Three distinct weighting procedures are compared. These are based on (1) the initial selection probability weights; (2) the 1986 SIPP panel weights; and (3) the monthly attrition-adjusted weights. The paper also compares these weighted estimates with the estimates of a structural model in which attrition is treated as an error-correlated competing alternative to divorce." The results indicate that in many instances divorces in the SIPP end up being recorded as attrition., (excerpt)

This paper examines methods for integrating latent class models with association and conditional association models, including those in multiple groups. These methods are shown to be generalizable to a wide range of association models in which one or more variables is latent and shown to be especially well suited to modeling temporal changes (tends) in latent structures. Like the usual association model, association models with latent variables utilize the information inherent in the ordering of the categories. Consequently, these models require the estimation of fewer parameters and are preferred to loglinear models that may require the estimation of substantial numbers of parameters even for models with a moderate number of observed variables. Following a discussion of the formal model, an example is considered. This example focuses on the American public's approval (disapproval) of legalized abortion from 1972 to 1988.

"This paper aims at providing a practical guidance for coping with social science event-history data that are left-truncated, especially when the length of exposure prior to observation is known. Only the case of single events is treated, although much of the discussion should be applicable to the case of repeated events, in which only the first spell is likely to be left-truncated. Marital dissolution data from the Panel Study of Income Dynamics (PSID) are used as an example....", (excerpt)

"The present paper develops a generalization of the standard discrete-time competing hazards model that allows for the types of stochastic dependencies resulting from shared unmeasured risk factors. An empirical example is provided using the process by which young women form their first conjugal residential union, with married and unmarried cohabitation representing the competing alternatives. The results suggest considerable and significant similarity of the alternatives in terms of the unmeasurables. It is also shown that, as a result, the independence assumption leads to substantially biased estimates of the net marriage and net cohabitation survival functions." The data concern a cohort of white children born in Detroit, Michigan, in 1961 and their mothers, followed up to 1985., (excerpt)

"This paper details the authors' selection, design, and use of a life history calendar (LHC) to collect retrospective life course data. A sample of nine hundred [U.S.] 23-year-olds, originally interviewed in 1980, were asked about the incidence and timing of various life events in the nine years since their 15th birthday.... The following aspects of the LHC are described: (a) the concept, uses, and advantages of the LHC, (b) the time units and domains used, (c) the mode of recording the responses and the decisions and problems involved, (d) interviewer training, and (e) coding. The following results attest to the accuracy of the LHC retrospective data: (a) only four of the calendars had missing data in any month; (b) the data obtained in 1980 about current work, school attendance, marriage, and children showed a remarkable correspondence to the retrospective 1985 LHC reports of these events; (c) the interviewers were positive about the LHC's ability to increase respondent recall.", (excerpt)