Abstract
Obtaining individual participant data (IPD) can reduce many of the potential biases facing conventional meta-analyses of published aggregate data. This chapter describes how researchers can examine the potential impact of biases on IPD meta-analysis results by using sensitivity analyses, funnel plots, and a combination of IPD and aggregate data. Publication bias is a well-known threat to the validity of traditional meta-analyses based on aggregate data. IPD meta-analysis projects have strong potential to reduce publication bias in meta-analysis by obtaining data for unpublished trials. The factors that cause between-trial heterogeneity in treatment effect may also cause small-study effects and thus asymmetry in a funnel plot. Availability bias can occur in an IPD meta-analysis project if IPD are unavailable for some trials and this unavailability is related to the trial results. Unavailability of IPD may be related to trial quality. Selective outcome reporting occurs where trial outcomes are entirely excluded upon publication.
| Original language | English |
|---|---|
| Title of host publication | Individual Participant Data Meta-Analysis |
| Subtitle of host publication | a Handbook for Healthcare Research |
| Publisher | Wiley-Blackwell Publishing Ltd |
| Chapter | 9 |
| Pages | 237-251 |
| Number of pages | 15 |
| ISBN (Electronic) | 9781119333784 |
| ISBN (Print) | 9781119333722 |
| DOIs | |
| Publication status | Published - 22 Apr 2021 |
Bibliographical note
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