Bibliographic Details
| Title: |
A systematic review of the quality of reporting of simulation studies about methods for the analysis of complex longitudinal patient-reported outcomes data. |
| Authors: |
Hinds, Aynslie M., Sajobi, Tolulope T., Sebille, Véronique, Sawatzky, Richard, Lix, Lisa M. |
| Source: |
Quality of Life Research. Oct2018, Vol. 27 Issue 10, p2507-2516. 10p. 1 Diagram, 3 Charts, 1 Graph. |
| Subjects: |
Health outcome assessment, Evaluation of medical care, Best practices, Computer simulation, Statistics |
| Abstract: |
Purpose: This study describes the characteristics and quality of reporting for published computer simulation studies about statistical methods to analyze complex longitudinal (i.e., repeated measures) patient-reported outcomes (PROs); we included methods for longitudinal latent variable measurement and growth models and response shift.Methods: Scopus, PsycINFO, PubMed, EMBASE, and Social Science Citation Index were searched for English-language studies published between 1999 and 2016 using selected keywords. Extracted information included characteristics of the study purpose/objectives, simulation design, software, execution, performance, and results. The quality of reporting was evaluated using published best-practice guidelines.Synthesis: A total of 1470 articles were reviewed and 42 articles met the inclusion criteria. The majority of the included studies (73.8%) investigated an existing statistical method, primarily a latent variable model (95.2%). Most studies specified the population model, including variable distributions, mean parameters, and correlation/covariances. The number of time points and sample size(s) were reported by all studies, but justification for the selected values was rarely provided. The majority of the studies (52.4%) did not report on model non-convergence. Bias, accuracy, and model fit were commonly reported performance metrics. All studies reported results descriptively, and 26.2% also used an inferential method.Conclusions: While methodological research on statistical analyses of complex longitudinal PRO data is informed by computer simulation studies, current reporting practices of these studies have not been consistent with best-practice guidelines. Comprehensive reporting of simulation methods and results ensures that the strengths and limitations of the investigated statistical methods are thoroughly explored. [ABSTRACT FROM AUTHOR] |
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| Database: |
Psychology and Behavioral Sciences Collection |
