Related Experiment Video
Updated: May 22, 2025

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
Published on: February 19, 2021
From Percentages to Precision: Using Response Rates to Advance Analyses of Procedural Fidelity
Claire C St Peter1, Olivia B Harvey1, Marisela Aguilar1
1West Virginia University, 53 Campus Drive, Morgantown, WV 26506 USA.
None:
In some domains of behavior analysis, summarizing data as a percentage is nearly ubiquitous. This is certainly the case when behavior analysts report data about procedural fidelity (the extent to which procedures are implemented as designed); fidelity data were reported solely as percentage in 423 of 425 recent studies published in the Journal of Applied Behavior Analysis. In this article, we critically examine the use of percentage, especially in the context of analyzing procedural-fidelity data. We demonstrate how exclusive reliance on percentage can obscure important nuances in fidelity data and how adding response rate as a metric offers a more precise understanding. To illustrate our points, we include reanalyzed data from a recent evaluation of procedural fidelity in public schools. We conclude with practical recommendations for adopting rate as a metric in the analysis of procedural-fidelity data, thereby building on contributions of notable behavior analysts like Henry Pennypacker, who prioritized continuous, dimensional approaches to measurement.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s40614-025-00433-9.
More Related Videos
14:05Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
Published on: January 23, 2017
08:06Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
Published on: June 18, 2018
Related Concept Videos
Surveys
Longitudinal Research
Sample Proportion and Population Proportion
Statistical Significance
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Friedman Two-way Analysis of Variance by Ranks