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COhtlhuous-ilme Modeis for the An~lyglgof Sequential Categorical Data

William GardnerUniversity of Virginia

Sequential categorical data are frequentlycollected tn observational research on socialinteraction. Social interactions occur incontinuous-time and contemporary observationaltechnology allows researchers to time thedurations of events to precisions in smallfractions of a second. However, the statisti­cal methodology employed to analyze sequentialcategorical data has usually represented timeonly as a sequence of discrete events, eitherby ignoring duration information or attemptingto capture it implicitly via interval coding .Consequently, many researchers employing adiscrete-time methodology are not using all theinformation available in their data sets. Thispaper presents methods for the analysis ofparallel streams of sequential categorical datain continuous-time, e.g., the interactivebehavior of two or more individuals in whichboth the sequence of events and their onset andoffset times are recorded.