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Updated: Jun 11, 2026
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Published on: November 2, 2012
Comparing simulation and threshold approaches when analysing data with probabilities of categories
Fang Zhang1, J Frank Wharam, Dennis Ross-Degnan
1Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA 02215, USA. fang_zhang@hphc.org
Objective:
Constructing categories based on probabilities is not unusual in defining the outcome or the exposure. We compare the threshold approach and the simulation approach in making inferences.
Method:
We used a simple structured example as well as published data to illustrate the difference between the simulation and the threshold approaches.
Results:
We demonstrated that simulation results were different from the threshold approach in estimating the effect of a high-deductible health plan. For repeat visits, we estimated a statistically significant ratio of incident rate ratio (IRR) 0.78 (95% CI: 0.64, 0.93) for non-preventable emergency department visits using the simulation approach while the high-severity category showed no statistical significance with the ratio of IRR 0.98 (95% CI: 0.64, 1.49) using a threshold of 75%. We also demonstrated that none of the threshold values could achieve the results of the simulation approach.
Conclusions:
The simulation approach is preferred over the threshold one when analysing data with probability-based outcome, exposure and/or other covariates if the size of the data permits.
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