Simulating Study Data to Support Expected Value of Sample Information Calculations: A Tutorial
Nicky J. Welton and
Jeremy D. Goldhaber-Fiebert
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Anna Heath: Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada
Mark Strong: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
David Glynn: Centre for Health Economics, University of York, York, UK
Natalia Kunst: Harvard Medical School & Harvard Pilgrim Health Care Institute, Harvard University, Boston, MA
Nicky J. Welton: School of Social and Community Medicine, University of Bristol, Bristol, UK
Jeremy D. Goldhaber-Fiebert: Stanford Health Policy, Centers for Health Policy and Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA
Medical Decision Making, 2022, vol. 42, issue 2, 143-155
The expected value of sample information (EVSI) can be used to prioritize avenues for future research and design studies that support medical decision making and offer value for money spent. EVSI is calculated based on 3 key elements. Two of these, a probabilistic model-based economic evaluation and updating model uncertainty based on simulated data, have been frequently discussed in the literature. By contrast, the third element, simulating data from the proposed studies, has received little attention. This tutorial contributes to bridging this gap by providing a step-by-step guide to simulating study data for EVSI calculations. We discuss a general-purpose algorithm for simulating data and demonstrate its use to simulate 3 different outcome types. We then discuss how to induce correlations in the generated data, how to adjust for common issues in study implementation such as missingness and censoring, and how individual patient data from previous studies can be leveraged to undertake EVSI calculations. For all examples, we provide comprehensive code written in the R language and, where possible, Excel spreadsheets in the supplementary materials. This tutorial facilitates practical EVSI calculations and allows EVSI to be used to prioritize research and design studies.
Keywords: expected value of sample information; R tutorial; research design methods; simulation methods; value of information (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:42:y:2022:i:2:p:143-155
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