Abstract
Systematic reviews involve a sequence of decisions and assumptions ranging from the definition of a particular variable and use of statistical methods to the type of model chosen for meta-analysis. If incorrect, these decisions and assumptions can influence the conclusions of the systematic review. Sensitivity and subgroup analyses play an important role in addressing these issues in meta-analysis. Sensitivity analysis helps in checking the sensitivity of the overall conclusions to various limitations of the data, assumptions, and approach to analysis. Consistency between the results of primary analysis and sensitivity analysis strengthens the conclusions and credibility of the findings. Effects of an intervention may not be homogeneous across all participants in a clinical trial. They may vary based on participant characteristics such as age, gender, and severity of illness. Subgroup analyses help in identifying subgroups of participants with most benefits (or adverse effects) of the intervention compared with others. This chapter covers the principles, practice, and pitfalls, of sensitivity and subgroup analyses in systematic reviews and meta-analysis.
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Deshmukh, M. (2021). Sensitivity and Subgroup Analyses. In: Patole, S. (eds) Principles and Practice of Systematic Reviews and Meta-Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-71921-0_9
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DOI: https://doi.org/10.1007/978-3-030-71921-0_9
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