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| Kim, Lois G.; White, Ian R.. |
| Survival data are most frequently analyzed by the intention-to-treat principle. However, presenting a compliance-adjusted analysis alongside the primary analysis can provide an insight into the effect of the treatment for those individuals actually complying with their randomized intervention. There are a number of methods for this type of analysis. Loeys and Goetghebeur (2003) use proportional hazards techniques to provide an estimate of the treatment effect for compliers when compliance is measured on an all-or-nothing scale. This methodology is here made available through a new Stata command, stcomply. |
| Tipo: Journal Article |
Palavras-chave: Stcomply; Compliance; Proportional hazards; Research Methods/ Statistical Methods. |
| Ano: 2004 |
URL: http://purl.umn.edu/116246 |
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| White, Ian R.. |
| Multivariate meta-analysis combines estimates of several related parameters over several studies. These parameters can, for example, refer to multiple outcomes or comparisons between more than two groups. A new Stata command, mvmeta, performs maximum likelihood, restricted maximum likelihood, or method-of-moments estimation of random-effects multivariate meta-analysis models. A utility command, mvmeta_make, facilitates the preparation of summary datasets from more detailed data. The commands are illustrated with data from the Fibrinogen Studies Collaboration, a meta-analysis of observational studies; I estimate the shape of the association between a quantitative exposure and disease events by grouping the quantitative exposure into several categories. |
| Tipo: Article |
Palavras-chave: Mvmeta; Mvmeta_make; Mvmeta_l; Meta-analysis; Multivariate meta-analysis; Individual participant data; Observational studies; Research Methods/ Statistical Methods. |
| Ano: 2009 |
URL: http://purl.umn.edu/122697 |
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| White, Ian R.; Higgins, Julian P.T.. |
| 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. |
| Tipo: Article |
Palavras-chave: Metamiss; Meta-analysis; Missing data; Informative missingness odds ratio; Research Methods/ Statistical Methods. |
| Ano: 2009 |
URL: http://purl.umn.edu/122700 |
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