Table of Contents

Volume 5 No.2,  2016

* This issue includes papers published with

Survival Analysis of Duration of Breastfeeding and Associated Factors of Early Cessation of Breastfeeding in Ethiopia - Pages 71-79
Melkamu Molla and Leakemariam Berhe
http://dx.doi.org/10.6000/1929-6029.2016.05.02.1

The Usefulness of Maximum Daily Temperatures Versus Defined Heatwave Periods in Assessing the Impact of Extreme Heat on ED Admissions for Chronic Conditions - Pages 80-89
Richard J. Woodman and Lidia Mayner
http://dx.doi.org/10.6000/1929-6029.2016.05.02.2

Intention-to-Treat Analysis but for Treatment Intention: How should Consumer Product Randomized Controlled Trials be Analyzed? - Pages 90-98
Rolf Weitkunat, Gizelle Baker and Frank Lüdicke
http://dx.doi.org/10.6000/1929-6029.2016.05.02.3

Confidence Intervals for the Population Correlation Coefficient ρ - Pages 99-111
Shipra Banik and B.M. Golam Kibria
http://dx.doi.org/10.6000/1929-6029.2016.05.02.4

A Declaratory Model of Generalized Regression Neural Network (GRNN) for Estimating Sleep Apnea Index in the Elderly Suffering from Sleep Disturbance - Pages 112-119
Bingh Tang
http://dx.doi.org/10.6000/1929-6029.2016.05.02.5

Study on Temporal Effects of Urban Malaria Incidences - Pages 120-132
Krishnendra S. Ganguly, Soumita Modak, Krishna S. Ganguly and Asis K. Chattopadhyay
http://dx.doi.org/10.6000/1929-6029.2016.05.02.6

The Method of Randomization for Cluster-Randomized Trials: Challenges of Including Patients with Multiple Chronic Conditions
Pages 2-7
Denise Esserman, Heather G. Allore and Thomas G. Travison
DOI: http://dx.doi.org/10.6000/1929-6029.2016.05.01.1
Published: 08 January 2016

Abstract: Cluster-randomized clinical trials (CRT) are trials in which the unit of randomization is not a participant but a group (e.g. healthcare systems or community centers). They are suitable when the intervention applies naturally to the cluster (e.g. healthcare policy); when lack of independence among participants may occur (e.g. nursing home hygiene); or when it is most ethical to apply an intervention to all within a group (e.g. school-level immunization). Because participants in the same cluster receive the same intervention, CRT may approximate clinical practice, and may produce generalizable findings. However, when not properly designed or interpreted, CRT may induce biased results.

CRT designs have features that add complexity to statistical estimation and inference. Chief among these is the cluster-level correlation in response measurements induced by the randomization. A critical consideration is the experimental unit of inference; often it is desirable to consider intervention effects at the level of the individual rather than the cluster. Finally, given that the number of clusters available may be limited, simple forms of randomization may not achieve balance between intervention and control arms at either the cluster- or participant-level.

In non-clustered clinical trials, balance of key factors may be easier to achieve because the sample can be homogenous by exclusion of participants with multiple chronic conditions (MCC). CRTs, which are often pragmatic, may eschew such restrictions. Failure to account for imbalance may induce bias and reducing validity. This article focuses on the complexities of randomization in the design of CRTs, such as the inclusion of patients with MCC, and imbalances in covariate factors across clusters.