scholarly journals Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial

2020 ◽  
Vol 49 (3) ◽  
pp. 954-962 ◽  
Author(s):  
Lazaro M Mwandigha ◽  
Keith J Fraser ◽  
Amy Racine-Poon ◽  
Mohamad-Samer Mouksassi ◽  
Azra C Ghani

Abstract Background Cluster randomized trials (CRTs) are increasingly used to study the efficacy of interventions targeted at the population level. Formulae exist to calculate sample sizes for CRTs, but they assume that the domain of the outcomes being considered covers the full range of values of the considered distribution. This assumption is frequently incorrect in epidemiological trials in which counts of infection episodes are right-truncated due to practical constraints on the number of times a person can be tested. Methods Motivated by a malaria vector control trial with right-truncated Poisson-distributed outcomes, we investigated the effect of right-truncation on power using Monte Carlo simulations. Results The results demonstrate that the adverse impact of right-truncation is directly proportional to the magnitude of the event rate, λ, with calculations of power being overestimated in instances where right-truncation was not accounted for. The severity of the adverse impact of right-truncation on power was more pronounced when the number of clusters was ≤30 but decreased the further the right-truncation point was from zero. Conclusions Potential right-truncation should always be accounted for in the calculation of sample size requirements at the study design stage.

2020 ◽  
Vol 376 (1818) ◽  
pp. 20190807 ◽  
Author(s):  
Robert T. Jones ◽  
Elizabeth Pretorius ◽  
Thomas H. Ant ◽  
John Bradley ◽  
Anna Last ◽  
...  

Vector-borne diseases threaten the health of populations around the world. While key interventions continue to provide protection from vectors, there remains a need to develop and test new vector control tools. Cluster-randomized trials, in which the intervention or control is randomly allocated to clusters, are commonly selected for such evaluations, but their design must carefully consider cluster size and cluster separation, as well as the movement of people and vectors, to ensure sufficient statistical power and avoid contamination of results. Island settings present an opportunity to conduct these studies. Here, we explore the benefits and challenges of conducting intervention studies on islands and introduce the Bijagós archipelago of Guinea-Bissau as a potential study site for interventions intended to control vector-borne diseases. This article is part of the theme issue ‘Novel control strategies for mosquito-borne diseases'.


Author(s):  
Eva Lorenz ◽  
Sabine Gabrysch

In cluster-randomized trials, groups or clusters of individuals, rather than individuals themselves, are randomly allocated to intervention or control. In this article, we describe a new command, ccrand, that implements a covariate-constrained randomization procedure for cluster-randomized trials. It can ensure balance of one or more baseline covariates between trial arms by restriction to allocations that meet specified balance criteria. We provide a brief overview of the theoretical background, describe ccrand and its options, and illustrate it using an example.


2010 ◽  
Vol 8 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Zhiying You ◽  
O Dale Williams ◽  
Inmaculada Aban ◽  
Edmond Kato Kabagambe ◽  
Hemant K Tiwari ◽  
...  

2021 ◽  
Author(s):  
L Miriam Dickinson ◽  
Patrick Hosokawa ◽  
Jeanette A Waxmonsky ◽  
Bethany M Kwan

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