Partial-Interval Recording and Estimates of Duration in Meta-analyses: Insights from Self-Monitoring Research

Abstract Time sampling, wherein an observer indicates whether a behavior occurred within a specified time interval, frequently appears in single-case designs. Partial-interval recording (PIR), the most common form of time sampling, is known to introduce error when used to estimate the duration of a behavior. Recent scholarship has suggested that PIR can be corrected statistically. However, few studies report the data needed to adjust for PIR in meta-analyses conducted to identify effective practices. This could present issues in identifying evidence-based practices in areas, such as research involving children with emotional and behavioral disorders (EBD), where PIR is commonly used. The present study examined the results of a previously published meta-analysis concerning the effect of self-monitoring on the challenging behavior of students with EBD (Bruhn et al. in J Positive Behav Interv 24(2):156–168, 2022). Analyses involved (a) calculating effects for each study based on three imputed average durations of their occurrence and (b) conducting meta-analyses to evaluate the impact of average duration on overall estimates of effect. Results suggest that correcting for PIR resulted in marginal changes when observation intervals were consistent with recommended lengths or when results were conclusive, but otherwise were indicative of a wide range of possible outcomes. A discussion of potential changes to reporting and analysis practices follows a description of results.