Simulation study comparing analytical methods for single-item longitudinal patient-reported outcomes data.

ABSTRACT:

Purpose

Efficient analytical methods are necessary to make reproducible inferences on single-item longitudinal ordinal patient-reported outcome (PRO) data. A thorough simulation study was performed to compare the performance of the semiparametric probabilistic index models (PIM) with a longitudinal analysis using parametric cumulative logit mixed models (CLMM).

Methods

In the setting of a control and intervention arm, we compared the power of the PIM and CLMM to detect differences in PRO adverse event (AE) between these groups using several existing and novel summary scores of PROs. For each scenario, PRO data were simulated using copula multinomial models. Comparisons were also exemplified using clinical trial data.

Results

On average, CLMM provided substantially gre

SUBMITTER: Calsavara VF 

PROVIDER: S-EPMC9992042 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature