Reducing And Analyzing Observational Data

In contrast with both self-report or questionnaire methods, and more similar with automatic collection of physiological data, observational methods often result in voluminous data. Thus data reduction is often a necessary prelude to analysis. A useful strategy is to collect slightly more detailed data than one intends to examine, thus initial data reduction may consist of combining some codes. Other data reduction may involve computation of conceptually targeted indices (e.g., an index of the extent to which mothers are responsive to their infants' gaze), which then serve as scores for multiple regression or other kinds of statistical analyses. Several examples of this useful and productive strategy for observational data are given in Bakeman and Gottman (1997); Bakeman (2000); and Bakeman, Deckner, and Quera (2004), and a specific example is presented in the following paragraphs.

Earlier we noted that sequences of events might be coded without recording their onset or offset time. Such event sequences are amenable to Sackett's (1979) lag-sequential analysis. However, when events are coded along with their onset and offset times—and current technology makes timing information ever easier to record—such timed sequences afford analytic options not available with event sequences (Bakeman & Quera, 1995). Timed sequences can consist of any number of mutually exclusive or co-occurring behaviors, and the time unit, not the event, can be used as the tallying unit when constructing contingency tables. This can be very useful. Often we want to know whether one behavior occurred within a specified time relative to another, and we are not particularly concerned with its lag position (i.e., with whether or not other behaviors intervened).

For example, Deckner, Adamson, and Bakeman (2003) wanted to know whether mothers and their toddlers matched each other's rhythmic vocalizations and so coded onset and offset times for mothers' and toddlers' rhythmic vocalizations. Their time unit was a second, and Figure 10.5 shows results for one dyad. For the rows, each second of the observed interaction was classified as within (or not within) a 5-second time window; the window began the second the mother began a rhythmic vocalization and extended for the next 4 seconds. For the columns, seconds were classified as a second the toddler began a rhythmic vocalization, or not. A useful way to summarize this 2x2 table is to note that the odds the toddler began a rhythmic vocalization within 5 seconds of her mother beginning one were 0.0582 to 1 (i.e., 11 * 189), whereas the corresponding odds otherwise were 0.0299 to 1 (i.e., 29 + 971). Thus the odds ratio—a statistic probably more used in epidemiology than in other social science fields—is 1.95 (i.e., 0.0582 - 0.0299).

Within 5s of




mother's onset



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