Covariate adjustment in randomized controlled trials with dichotomous outcomes increases statistical power and reduces sample size requirements.
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Summary
It is concluded that adjustment for a predictive baseline characteristic may lead to a potentially important increase in power of analyses of treatment effect and should be considered more often for RCTs with dichotomous outcomes.
- Type
- article
- Published
- 2004-05-01
- Cited by
- 249
- References
- 34
- OpenAlex
- https://openalex.org/W15196615
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1894025
Keywords
Sialography, Parotid gland, Sjögren syndrome, Medicine, Salivary gland
References
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- Sample size in clinical trials with dichotomous endpoints: use of covariables.
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- Some surprising results about covariate adjustment in logistic regression models
- A consequence of omitted covariates when estimating odds ratios.
- Aspirin and coumadin after acute coronary syndromes (the ASPECT-2 study): a randomised controlled trial.
- Clinical trials in acute myocardial infarction: when should we adjust for baseline characteristics?
- How to select covariates to include in the analysis of a clinical trial.
- Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates
- Randomised controlled trials in cardiovascular medicine: past achievements, future challenges
- Stratified randomization for clinical trials.
- Choosing covariates in the analysis of clinical trials.
- Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practiceand problems
- On model prespecification in confirmatory randomized studies.
- Covariate adjustment of treatment effects in clinical trials.
- Stepwise selection in small data sets: a simulation study of bias in logistic regression analysis.
- Can overall results of clinical trials be applied to all patients?
Cited by
- Effect Modification of Interventions. Bridging the Gap Between Clinical Studies and the Individual Patient
- PINCER trial: a cluster randomised trial comparing the effectiveness and cost-effectiveness of a pharmacist-led IT-based intervention with simple feedback in reducing rates of clinically important errors in medicines management in general practices
- Should Stroke Trials Adjust Functional Outcome for Baseline Prognostic Factors?
- A Menu-Driven Facility for Sample-Size Calculations in Cluster Randomized Controlled Trials
- Towards successful Web-based smoking relapse prevention : the efficacy of a computer tailored program incorporating post-motivational components & an attentional bias modification program
- Efficient analysis of ordinal data from clinical trials in head injury
- Economic evaluation of factorial randomised controlled trials
- HETEROGENEITY IN COST-EFFECTIVENESS ANALYSIS:
- Preventing falls in older people
- Readings in Targeted Maximum Likelihood Estimation
- Interval Estimation of Treatment Effects In Randomized Trials: When do Confidence Intervals Have Nominal Coverage?
- Promoting Health by Addressing Basic Needs: Effect of Problem Resolution on Contacting Health Referrals
- Meta-analysis of clinical prediction models
- The Emergency Department Action in Smoking Cessation (EDASC) Trial: Impact on Delivery of Smoking Cessation Counseling
- New approaches to increase statistical power in TBI trials: insights from the IMPACT study.
- Small bites versus large bites for closure of abdominal midline incisions (STITCH): a double-blind, multicentre, randomised controlled trial.
- Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury
- Clinical Trial Design in the Neurocritical Care Unit
- To adjust or not to adjust for baseline when analyzing repeated binary responses? The case of complete data when treatment comparison at study end is of interest
- Statistical Power for School-Based RCTs With Binary Outcomes
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