Simulation Theory Applied to Direct Systematic Observation - PubMed (original) (raw)
Simulation Theory Applied to Direct Systematic Observation
Rumen Manolov et al. Front Psychol. 2017.
Abstract
Observational studies entail making several decisions before data collection, such as the observational design to use, the sampling of sessions within the observational period, the need for time sampling within the observation sessions, as well as the observation recording procedures to use. The focus of the present article is on observational recording procedures different from continuous recording (i.e., momentary time sampling, partial and whole interval recording). The main aim is to develop an online software application, constructed using R and the Shiny package, on the basis of simulations using the alternating renewal process (a model implemented in the ARPobservation package). The application offers graphical representations that can be useful to both university students constructing knowledge on Observational Methodology and to applied researchers planning to use discontinuous recording in their studies, because it helps identifying the conditions (e.g., interval length, average duration of the behavior of interest) in which the prevalence of the target behavior is expected to be estimated with less bias or no bias and with more efficiency. The estimation of frequency is another topic covered.
Keywords: alternating renewal process; direct observation; interval recording; prevalence; time sampling.
Figures
FIGURE 1
Representation of intersessional and intrasessional time sampling.
FIGURE 2
Graphical representation of within-session sampling of participants to be the focus of observation: alternating multifocal sweep.
FIGURE 3
Screenshot of the web application created using Shiny. The average interim time and the average incidence per minute can be seen for each value of prevalence, considering the average duration of the event.
FIGURE 4
Screenshot of the web application created using Shiny. Prevalence of a behavior with average duration per occurrence of 8 s as estimated in a single observation session of 20 min, using continuous recording (green dots) and momentary time sampling [MTS] (empty triangles) based on a 5-s interval. The numerical values represent the relative bias of the estimation using MTS.
FIGURE 5
Screenshot of the web application created using Shiny. Average prevalence of a behavior with average duration per occurrence of 8 s as estimated in 1000 observation sessions of 20 min, using continuous recording (green dots) and MTS (empty triangles) based on a 6-s interval. The dashed lines represent one and two standard deviations above and below the average estimate by MTS. The numerical values represent the relative bias of the estimation using MTS.
FIGURE 6
Screenshot of the web application created using Shiny. Average prevalence of a behavior with average duration per occurrence of 12 s as estimated in 100 observation sessions of 60 min, using continuous recording (green dots) and partial interval recording (PIR) (empty triangles without the correction; red crosses with the correction) based on a 6-s interval. The dashed lines represent one and two standard deviations above and below the average of the corrected estimates by PIR. The numerical values represent the relative bias of the estimation using PIR: black values refer to using the modified frequency in the numerator, whereas red values refer to using modified frequency minus pseudofrequency in the numerator.
FIGURE 7
Screenshot of the web application created using Shiny. Frequency estimates of a behavior with average duration per occurrence of 6 s as estimated in 100 observation sessions of 20 min, using PIR) based on a 15-s interval (i.e., the rate of interval length to duration per occurrence is 2.5).
FIGURE 8
Screenshot of the web application created using Shiny. Average prevalence of a behavior with average duration per occurrence of 35 s as estimated in 100 observation sessions of 60 min, using continuous recording (green dots) and PIR (empty triangles without the correction; red crosses with the correction) based on a 4-s interval. The dashed lines represent one and two standard deviations above and below the average of the corrected estimates by PIR. The numerical values represent the relative bias of the estimation using PIR: black values refer to using the modified frequency in the numerator, whereas red values refer to using modified frequency minus pseudofrequency in the numerator.
FIGURE 9
Screenshot of the web application created using Shiny. Average prevalence of a behavior with average duration per occurrence of 120 s as estimated in 100 observation sessions of 60 min, using continuous recording (green dots) and PIR (empty triangles without the correction; red crosses with the correction) based on a 15-s interval. The dashed lines represent one and two standard deviations above and below the average of the corrected estimates by PIR. The numerical values represent the relative bias of the estimation using PIR: black values refer to using the modified frequency in the numerator, whereas red values refer to using modified frequency minus pseudofrequency in the numerator.
References
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