Generalized prediction intervals for treatment effects in random‐effects models. Issue 5 (30th July 2018)

• Record Type: Journal Article
• Authors: Al‐Sarraj, Razaw; von Brömssen, Claudia; Forkman, Johannes
• Is Part Of: Biometrical journal. Volume 61:Issue 5(2019:Sep.)
• Page Start: 1242
• Page End: 1257
• Publication Date: 2018-07-30
• Subjects: generalized prediction intervals -- random effects -- random models -- REML; Biometry -- Periodicals; Medical statistics -- Periodicals; 570.15195
• DOI: 10.1002/bimj.201700255
• Languages: English
• ISSNs: 0323-3847

Abstract

Abstract: This article derives generalized prediction intervals for random effects in linear random‐effects models. For balanced and unbalanced data in two‐way layouts, models are considered with and without interaction. Coverage of the proposed generalized prediction intervals was estimated in a simulation study based on an agricultural field experiment. Generalized prediction intervals were compared with prediction intervals based on the restricted maximum likelihood (REML) procedure and the approximate methods of Satterthwaite and Kenward and Roger. The simulation study showed that coverage of generalized prediction intervals was closer to the nominal level 0.95 than coverage of prediction intervals based on the REML procedure.