Effect of present state bias on minimal important change estimates: a simulation study.

ABSTRACT:

Purpose

The minimal important change (MIC) in a patient-reported outcome measure is often estimated using patient-reported transition ratings as anchor. However, transition ratings are often more heavily weighted by the follow-up state than by the baseline state, a phenomenon known as "present state bias" (PSB). It is unknown if and how PSB affects the estimation of MICs using various methods.

Methods

We simulated 3240 samples in which the true MIC was simulated as the mean of individual MICs, and PSB was created by basing transition ratings on a "weighted change", differentially weighting baseline and follow-up states. In each sample we estimated MICs based on the following methods: mean change (MC), receiver operating characteristic (ROC) analysis, predictive modeling (PM)

SUBMITTER: Terluin B 

PROVIDER: S-EPMC11541299 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature