Eliciting and using expert opinions about dropout bias in randomized controlled trials.
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Topical treatments for athlete's footOn-line randomized controlled trial of an internet based psychologically enhanced intervention for people with hazardous alcohol consumptionImpact of interventions to improve the quality of peer review of biomedical journals: a systematic review and meta-analysisAddressing Missing Data Mechanism Uncertainty using Multiple-Model Multiple Imputation: Application to a Longitudinal Clinical Trial.Sensitivity analysis of incomplete longitudinal data departing from the missing at random assumption: Methodology and application in a clinical trial with drop-outs.Nondetection sampling bias in marked presence-only dataBinary variable multiple-model multiple imputation to address missing data mechanism uncertainty: application to a smoking cessation trial.Allowing for uncertainty due to missing continuous outcome data in pairwise and network meta-analysis.A Bayesian framework to account for uncertainty due to missing binary outcome data in pairwise meta-analysis.What impact do assumptions about missing data have on conclusions? A practical sensitivity analysis for a cancer survival registry.The DYD-RCT protocol: an on-line randomised controlled trial of an interactive computer-based intervention compared with a standard information website to reduce alcohol consumption among hazardous drinkers.Sensitivity analysis using elicited expert information for inference with coarsened data: illustration of censored discrete event times in the AIDS Link to Intravenous Experience (ALIVE) Study.Sensitivity analysis of informatively coarsened data using pattern mixture models.Pattern-mixture models for analyzing normal outcome data with proxy respondentsHow much can we learn about missing data?: an exploration of a clinical trial in psychiatry.Strategy for intention to treat analysis in randomised trials with missing outcome data.Subjective prior distributions for modeling longitudinal continuous outcomes with non-ignorable dropout.Allowing for missing outcome data and incomplete uptake of randomised interventions, with application to an Internet-based alcohol trialPractical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data.Effectiveness of dual-task functional power training for preventing falls in older people: study protocol for a cluster randomised controlled trial.Evaluation of a weighting approach for performing sensitivity analysis after multiple imputation.Including all individuals is not enough: lessons for intention-to-treat analysis.Outcome-sensitive multiple imputation: a simulation study.Sensitivity analysis after multiple imputation under missing at random: a weighting approach.Concurrent transcranial direct current stimulation and progressive resistance training in Parkinson's disease: study protocol for a randomised controlled trial.Using expert opinion to quantify unmeasured confounding bias parametersAppropriate inclusion of interactions was needed to avoid bias in multiple imputation.A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial.Analysis of longitudinal trials with protocol deviation: a framework for relevant, accessible assumptions, and inference via multiple imputation.Pattern mixture models for the analysis of repeated attempt designsDirect likelihood inference and sensitivity analysis for competing risks regression with missing causes of failure.Estimating causal effects using prior information on nontrial treatments.Missing data in clinical research: an integrated approach.Reference-based sensitivity analysis via multiple imputation for longitudinal trials with protocol deviation.Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial.A mean score method for sensitivity analysis to departures from the missing at random assumption in randomised trials
P2860
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P2860
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@ast
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@en
type
label
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@ast
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@en
prefLabel
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@ast
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@en
P2860
P356
P1433
P1476
Eliciting and using expert opinions about dropout bias in randomized controlled trials.
@en
P2093
Ian R White
Stephen Evans
P2860
P304
P356
10.1177/1740774507077849
P577
2007-01-01T00:00:00Z