Table 1.
Summary of Illustrative Designs and Analyses
| Illustrative design and analysis |
Treatment of time | Example content/research question |
|---|---|---|
| Between-subjects differences | Time is not represented in the analysis, though observations may be selected by time | Whether more dependent smokers experience more intense craving |
| Contrasting events (case–control) | Contrasts observations collected at different “times”—that is, in different situations—but without respect to their temporal ordering | Whether the probability of drinking differs between when the person is smoking versus not smoking |
| Event rates: Events/unit time | Uses time to calculate a rate of events (e.g., smoking) per unit of time | Whether smoking rate increases when smokers are feeling restless |
| Sequence of events | Uses time to establish a temporal ordering of events | Whether negative affect is higher at the time of a lapse than during a prior, randomly selected, occasion |
| Clock and calendar time | Time is represented conventionally, as a time of day or day of week | Whether smoking rate varies by time of day |
| Time defined by event | Time is defined by a contrast of before versus after an event | Whether self-efficacy drops after a lapse, compared to its level before the lapse |
| Time following an anchoring event | Data are analyzed for trends over time, running forward from a key event | How craving intensity changes after a smoker establishes abstinence |
| Time preceding an anchoring event | Data are analyzed for trends over time, preceding and leading up to a key event | Whether negative affect is on the rise in the time leading up to a lapse |
| Time-to-event analyses: Time as risk | The analysis focuses on the time elapsed until a certain event occurs (if it occurs at all), with shorter times indicating a greater risk per unit time | Whether smokers who are more demoralized after a lapse progress more quickly to a second lapse |
| Events recurring over time | Analyzes time-to-events, as above, but allows for multiple cycles of event recurrence | How the time between one lapse to the next changes across a sequence of lapses |
| Change in effects over time | Analyzes whether the relationship between two variables changes over time | How the relationship between self-efficacy and craving changes over time |