ArticleBiometrical journal. Biometrische Zeitschrift2021
Sample size and power considerations for cluster randomized trials with count outcomes subject to right truncation.
Article in Biometrical journal. Biometrische Zeitschrift, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Informative cluster size in cluster-randomised trials: A case study from the TRIGGER trial.Clinical trials (London, England) · 2023Trial
- Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations.Statistics in medicine · 2024Article
- Leveraging baseline covariates to analyze small cluster-randomized trials with a rare binary outcome.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials.Biometrical journal. Biometrische Zeitschrift · 2023Article
- Estimands in cluster-randomized trials: choosing analyses that answer the right question.International journal of epidemiology · 2023Article
- Design and analysis of cluster randomized trials with time-to-event outcomes under the additive hazards mixed model.Statistics in medicine · 2022Article
- Accounting for unequal cluster sizes in designing cluster randomized trials to detect treatment effect heterogeneity.Statistics in medicine · 2022Article
- Power considerations for generalized estimating equations analyses of four-level cluster randomized trials.Biometrical journal. Biometrische Zeitschrift · 2022Article
- Impact of unequal cluster sizes for GEE analyses of stepped wedge cluster randomized trials with binary outcomes.Biometrical journal. Biometrische Zeitschrift · 2022Article
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2 authors.
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Abstract
Cluster randomized trials (CRTs) are widely used in epidemiological and public health studies assessing population-level effect of group-based interventions. One important application of CRTs is the control of vector-borne disease, such as malaria. However, a particular challenge for designing these trials is that the primary outcome involves counts of episodes that are subject to right truncation. While sample size formulas have been developed for CRTs with clustered counts, they are not directly applicable when the counts are right truncated. To address this limitation, we discuss two marginal modeling approaches for the analysis of CRTs with truncated counts and develop two corresponding closed-form sample size formulas to facilitate the design of such trials. The proposed sample size formulas allow investigators to explore the power under a large number of scenarios without computationally intensive simulations. The proposed formulas are validated in extensive simulations. We further explore the implication of right truncation on power and apply the proposed formulas to illustrate the power calculation for a malaria control CRT where the primary outcome is subject to right truncation.
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