Skip to main content
Top
Gepubliceerd in: Quality of Life Research 10/2018

20-04-2018 | Review

A systematic review of the quality of reporting of simulation studies about methods for the analysis of complex longitudinal patient-reported outcomes data

Auteurs: Aynslie M. Hinds, Tolulope T. Sajobi, Véronique Sebille, Richard Sawatzky, Lisa M. Lix

Gepubliceerd in: Quality of Life Research | Uitgave 10/2018

Log in om toegang te krijgen
share
DELEN

Deel dit onderdeel of sectie (kopieer de link)

  • Optie A:
    Klik op de rechtermuisknop op de link en selecteer de optie “linkadres kopiëren”
  • Optie B:
    Deel de link per e-mail

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.
Bijlagen
Alleen toegankelijk voor geautoriseerde gebruikers
Literatuur
2.
go back to reference Fayers, P. M., & Machin, D. (2016). Quality of life: The assessment, analysis, and reporting of patient-reported outcomes (3rd ed.). Chichester: Wiley. Fayers, P. M., & Machin, D. (2016). Quality of life: The assessment, analysis, and reporting of patient-reported outcomes (3rd ed.). Chichester: Wiley.
3.
5.
go back to reference Schwartz, C. E., & Sprangers, M. A. (1999). Methodological approaches for assessing response shift in longitudinal health-related quality-of-life research. Social Science & Medicine, 48, 1531–1548.CrossRef Schwartz, C. E., & Sprangers, M. A. (1999). Methodological approaches for assessing response shift in longitudinal health-related quality-of-life research. Social Science & Medicine, 48, 1531–1548.CrossRef
7.
go back to reference Millsap, R. E. (2010). Testing measurement invariance using item response theory in longitudinal data: An introduction. Child Development Perspectives, 4(1), 5–9.CrossRef Millsap, R. E. (2010). Testing measurement invariance using item response theory in longitudinal data: An introduction. Child Development Perspectives, 4(1), 5–9.CrossRef
8.
go back to reference Sawatzky, R., Sajobi, T. T., Brahmbhatt, R., Chan, E. K. H., Lix, L. M., & Zumbo, B. D. (2017). Longitudinal change in response processes: A response shift perspective. In B. D. Zumbo & A. M. Hubley (Eds.), Understanding and investigating response processes in validation research (1st ed., pp. 251–276). Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-56129-5_14.CrossRef Sawatzky, R., Sajobi, T. T., Brahmbhatt, R., Chan, E. K. H., Lix, L. M., & Zumbo, B. D. (2017). Longitudinal change in response processes: A response shift perspective. In B. D. Zumbo & A. M. Hubley (Eds.), Understanding and investigating response processes in validation research (1st ed., pp. 251–276). Switzerland: Springer International Publishing. https://​doi.​org/​10.​1007/​978-3-319-56129-5_​14.CrossRef
10.
go back to reference Guilleux, A., Blanchin, M., Vanier, A., Guillemin, F., Falissard, B., Schwartz, C. E., … Sébille, V. (2015). RespOnse Shift ALgorithm in item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies. Quality of Life Research, 24(3), 553–564. https://doi.org/10.1007/s11136-014-0876-4.CrossRefPubMed Guilleux, A., Blanchin, M., Vanier, A., Guillemin, F., Falissard, B., Schwartz, C. E., … Sébille, V. (2015). RespOnse Shift ALgorithm in item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies. Quality of Life Research, 24(3), 553–564. https://​doi.​org/​10.​1007/​s11136-014-0876-4.CrossRefPubMed
14.
19.
go back to reference de Bock, E., Hardouin, J., Blanchin, M., Le Neel, T., Kubis, G., Bonnaud-Antignac, A., … Sebille, V. (2013). Rasch-family models are more valuable than score-based approaches for analysing longitudinal patient-reported outcomes with missing data. Statistical Methods in Medical Research, 16, 1–21. https://doi.org/10.1177/0962280213515570.CrossRef de Bock, E., Hardouin, J., Blanchin, M., Le Neel, T., Kubis, G., Bonnaud-Antignac, A., … Sebille, V. (2013). Rasch-family models are more valuable than score-based approaches for analysing longitudinal patient-reported outcomes with missing data. Statistical Methods in Medical Research, 16, 1–21. https://​doi.​org/​10.​1177/​0962280213515570​.CrossRef
20.
go back to reference de Bock, E., Hardouin, J. B., Blanchin, M., Le Neel, T., Kubis, G., & Sebille, V. (2015). Assessment of score- and Rasch-based methods for group comparison of longitudinal patient-reported outcomes with intermittent missing data (informative and non-informative). Quality of Life Research, 24(1), 19–29. https://doi.org/10.1007/s11136-014-0648-1.CrossRefPubMed de Bock, E., Hardouin, J. B., Blanchin, M., Le Neel, T., Kubis, G., & Sebille, V. (2015). Assessment of score- and Rasch-based methods for group comparison of longitudinal patient-reported outcomes with intermittent missing data (informative and non-informative). Quality of Life Research, 24(1), 19–29. https://​doi.​org/​10.​1007/​s11136-014-0648-1.CrossRefPubMed
50.
go back to reference Wilson, M., Zheng, X., & McGuire, L. (2012). Formulating latent growth using an explanatory item response model approach. Journal of Applied Measurement, 13(1), 1–22.PubMed Wilson, M., Zheng, X., & McGuire, L. (2012). Formulating latent growth using an explanatory item response model approach. Journal of Applied Measurement, 13(1), 1–22.PubMed
54.
go back to reference Feddag, M. L., Blanchin, M., Hardouin, J. B., & Sebille, V. (2014). Power analysis on the time effect for longitudinal Rasch model. Journal of Applied Measurement, 15(3), 292–301.PubMed Feddag, M. L., Blanchin, M., Hardouin, J. B., & Sebille, V. (2014). Power analysis on the time effect for longitudinal Rasch model. Journal of Applied Measurement, 15(3), 292–301.PubMed
55.
go back to reference Tavares, H. R., & Andrade, D. F. (2006). Item response theory for longitudinal data: Item and population ability parameters estimation. Sociedad de Estadistica e Investigacion Operativa, 15(1), 97–123. Tavares, H. R., & Andrade, D. F. (2006). Item response theory for longitudinal data: Item and population ability parameters estimation. Sociedad de Estadistica e Investigacion Operativa, 15(1), 97–123.
56.
go back to reference Blanchin, M., Hardouin, J.-B., Le Neel, T., Kubis, G., & Sebille, V. (2011). Analysis of longitudinal patient-reported outcomes with informative and non-informative dropout: Comparison of CTT and Rasch-based methods. International Journal of Applied Mathematics & Statistics, 24(SI-11A), 107–124. Blanchin, M., Hardouin, J.-B., Le Neel, T., Kubis, G., & Sebille, V. (2011). Analysis of longitudinal patient-reported outcomes with informative and non-informative dropout: Comparison of CTT and Rasch-based methods. International Journal of Applied Mathematics & Statistics, 24(SI-11A), 107–124.
58.
go back to reference Luo, S., Ma, J., & Kieburtz, K. D. (2013). Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions. Statistics in Medicine, 32(22), 3812–3828.CrossRef Luo, S., Ma, J., & Kieburtz, K. D. (2013). Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions. Statistics in Medicine, 32(22), 3812–3828.CrossRef
63.
go back to reference Bang, J. W., Schumacker, R. E., & Schlieve, P. L. (1998). Random-number generator validity in simulation studies: An investigation of normality. Educational and Psychological Measurement, 58(3), 430–450.CrossRef Bang, J. W., Schumacker, R. E., & Schlieve, P. L. (1998). Random-number generator validity in simulation studies: An investigation of normality. Educational and Psychological Measurement, 58(3), 430–450.CrossRef
64.
go back to reference Gadermann, A. M., Sawatzky, R., Palepu, A., Hubley, A. M., Zumbo, B. D., Aubry, T., … Hwang, S. W. (2017). Minimal impact of response shift for SF-12 mental and physical health status in homeless and vulnerably housed individuals: An item-level multi-group analysis. Quality of Life Research, 26(6), 1463–1472. https://doi.org/10.1007/s11136-016-1464-6.CrossRefPubMed Gadermann, A. M., Sawatzky, R., Palepu, A., Hubley, A. M., Zumbo, B. D., Aubry, T., … Hwang, S. W. (2017). Minimal impact of response shift for SF-12 mental and physical health status in homeless and vulnerably housed individuals: An item-level multi-group analysis. Quality of Life Research, 26(6), 1463–1472. https://​doi.​org/​10.​1007/​s11136-016-1464-6.CrossRefPubMed
65.
go back to reference Meijer, R. R., & Sijtsma, K. (2001). Methodology review: Evaluating person fit. Applied Psychological Measurement, 25(2), 107–135.CrossRef Meijer, R. R., & Sijtsma, K. (2001). Methodology review: Evaluating person fit. Applied Psychological Measurement, 25(2), 107–135.CrossRef
Metagegevens
Titel
A systematic review of the quality of reporting of simulation studies about methods for the analysis of complex longitudinal patient-reported outcomes data
Auteurs
Aynslie M. Hinds
Tolulope T. Sajobi
Véronique Sebille
Richard Sawatzky
Lisa M. Lix
Publicatiedatum
20-04-2018
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 10/2018
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-018-1861-0

Andere artikelen Uitgave 10/2018

Quality of Life Research 10/2018 Naar de uitgave