Work

Prediction intervals for random-effects meta-analysis: A confidence distribution approach

Year: 2018

Type: article

Abstract: Prediction intervals are commonly used in meta-analysis with random-effects models. One widely used method, the Higgins-Thompson-Spiegelhalter prediction interval, replaces the heterogeneity parameter with its point estimate, but its validity strongly depends on a large sample approximation. This is a weakness in meta-analyses with few studies. We propose an alternative based on bootstrap and show by simulations that its coverage is close to the nominal level, unlike the Higgins-Thompson-Spiegelhalter method and its extensions. The proposed method was applied in three meta-analyses.

Source: Statistical Methods in Medical Research

DOI: 10.1177/0962280218773520

Authors: Kengo Nagashima, Hisashi Noma, Toshi A Furukawa

Institutions: The Institute of Statistical Mathematics, Kyoto University

Language: English

Topic: Meta-analysis and systematic reviews

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

Funder: Japan Science and Technology Agency

Award: G426841107