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Updated: Jun 15, 2025
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The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
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Effect of present state bias on minimal important change estimates: a simulation study.
Berend Terluin1,2, Piper Fromy3, Andrew Trigg4
1Department of General Practice, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. b.terluin@amsterdamumc.nl.
Summary
Present state bias (PSB) can affect minimal important change (MIC) estimates. Unconstrained longitudinal item response theory (LIRT) and longitudinal confirmatory factor analysis (LCFA) methods accurately estimate MICs regardless of PSB.
Area of Science:
- Psychometrics
- Health Outcomes Research
- Statistical Modeling
Background:
- Patient-reported outcome measures (PROMs) are crucial for assessing treatment effects.
- Minimal important change (MIC) quantifies the smallest change in a PROM perceived as beneficial.
- Present state bias (PSB) in transition ratings can distort MIC estimation.
Purpose of the Study:
- To investigate the impact of present state bias (PSB) on various methods for estimating minimal important change (MIC).
- To identify robust methods for MIC estimation that are unaffected by PSB.
Main Methods:
- Simulated 3240 samples with varying degrees of true MIC and PSB.
- Estimated MICs using mean change (MC), receiver operating characteristic (ROC) analysis, predictive modeling (PM), adjusted predictive modeling (APM), longitudinal item response theory (LIRT), and longitudinal confirmatory factor analysis (LCFA).
- Assessed the performance of LIRT and LCFA with and without constraints on parameters.
Main Results:
- MC, ROC, and PM methods were susceptible to biases unrelated to PSB.
- PSB introduced imprecision in APM and constrained LIRT/LCFA estimates when PSB was substantial.
- Unconstrained LIRT and LCFA methods provided unbiased and precise MIC estimates, irrespective of PSB.
Conclusions:
- Unconstrained LIRT and LCFA are recommended for estimating anchor-based MICs due to their robustness against PSB.
- APM serves as a viable alternative when PSB is minimal.
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