论文信息 - Meta-analysis with Missing Data

Meta-analysis with Missing Data

A new command, metamiss, performs meta-analysis with binary outcomes when some or all studies have missing data. Missing values can be imputed as successes, as failures, according to observed event rates, or by a combination of these according to reported reasons for the data being missing. Alternatively, the user can specify the value of, or a prior distribution for, the informative missingness odds ratio.

I. White | J. Higgins

[1] Ian R White,et al. Imputation methods for missing outcome data in meta-analysis of clinical trials , 2008, Clinical trials.

[2] Ian R White,et al. Allowing for uncertainty due to missing data in meta‐analysis—Part 1: Two‐stage methods , 2008, Statistics in medicine.

[3] Carrol Gamble,et al. Uncertainty method improved on best-worst case analysis in a binary meta-analysis. , 2005, Journal of clinical epidemiology.

[4] Nicole A. Lazar,et al. Statistical Analysis With Missing Data , 2003, Technometrics.

[5] Roderick J. A. Little,et al. Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data , 2002 .

[6] S. Lawrie,et al. Haloperidol versus placebo for schizophrenia. , 2001, The Cochrane database of systematic reviews.

[7] Jonathan J. Forster,et al. Model‐based inference for categorical survey data subject to non‐ignorable non‐response , 1998 .

[8] D. Rubin. Formalizing Subjective Notions about the Effect of Nonrespondents in Sample Surveys , 1977 .