PRM68 - IMPUTATION METHODS FOR MISSING DATA IN COST-UTILITY ANALYSES ALONGSIDE RANDOMIZED CONTROLLED TRIALS: AGGREGATE OR NON-AGGREGATE?
نویسندگان
چکیده
منابع مشابه
Multiple imputation methods for handling missing data in cost-effectiveness analyses that use data from hierarchical studies: an application to cluster randomized trials.
PURPOSE Multiple imputation (MI) has been proposed for handling missing data in cost-effectiveness analyses (CEAs). In CEAs that use cluster randomized trials (CRTs), the imputation model, like the analysis model, should recognize the hierarchical structure of the data. This paper contrasts a multilevel MI approach that recognizes clustering, with single-level MI and complete case analysis (CCA...
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Multivariate time series data are found in a variety of fields such as bioinformatics, biology, genetics, astronomy, geography and finance. Many time series datasets contain missing data. Multivariate time series missing data imputation is a challenging topic and needs to be carefully considered before learning or predicting time series. Frequent researches have been done on the use of diffe...
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BACKGROUND Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate depen...
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genotyping. PNK and SM recruited some of the cases and PDM provided the Guthrie cards for the controls. LD did the statistical analysis. All authors contributed to writing revisions of the report and approved the final manuscript. PNK is guarantor. Funding: National Institute of Child Health and Human Development, National Institutes of Health (Contract No. NOIHD 23163) and the Health Research ...
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In combination with randomization, blinding or masking is an important factor in randomized controlled trials (RCTs), particularly in trials that assess therapeutic effects. Here an attempt is made to explain blindness and why it is important. In clinical trials, blinding is defined as the condition imposed on a study in which study participants, health care providers and assessors collecting o...
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ژورنال
عنوان ژورنال: Value in Health
سال: 2018
ISSN: 1098-3015
DOI: 10.1016/j.jval.2018.09.2189