Longitudinal data are used commonly in sociology, and over the years sociologists have imported a wide variety of statistical procedures from other disciplines to analyze such data. Examples include survival analysis (Cox and Oakes 1984), dynamic modeling (Harvey 1990), and techniques for pooled cross-sectional and time series data (Hsiao 1986). Typically, these procedures are used to represent the causal mechanisms by which one or more outcomes are produced; a stochastic model is provided that is presumed to extract the essential means by which changes in some variables bring about changes in others (Berk 1988).

The techniques called time series analysis have somewhat different intellectual roots. Rather than try to represent explicit causal mechanisms, the goal in classical time series analysis is "simply" to describe some longitudinal stochastic processes in summary form. That description may be used to inform existing theory or inductively extract new theoretical notions, but classical...