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- Title
Simulation-based power calculations for planning a two-stage individual participant data meta-analysis.
- Authors
Ensor, Joie; Burke, Danielle L.; Snell, Kym I. E.; Riley, Richard D.; Hemming, Karla
- Abstract
<bold>Background: </bold>Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions.<bold>Methods: </bold>The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value.<bold>Results: </bold>In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has < 60% power to detect a reduction of 1 kg weight gain for a 10-unit increase in BMI. Additional IPD from ten other published trials (containing 1761 patients) would improve power to over 80%, but only if a fixed-effect meta-analysis was appropriate. Pre-specified adjustment for prognostic factors would increase power further. Incorrect dichotomisation of BMI would reduce power by over 20%, similar to immediately throwing away IPD from ten trials.<bold>Conclusions: </bold>Simulation-based power calculations could inform the planning and funding of IPD projects, and should be used routinely.
- Subjects
META-analysis; SIMULATION methods &; models; MEDICAL databases; WEIGHT gain; BODY mass index; PREGNANCY; RANDOMIZED controlled trials; STATISTICS
- Publication
BMC Medical Research Methodology, 2018, Vol 18, Issue 1, pN.PAG
- ISSN
1471-2288
- Publication type
journal article
- DOI
10.1186/s12874-018-0492-z