English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Many public health interventions are conducted in settings where individualsare connected to one another and the intervention assigned to randomly selectedindividuals may spill over to other individuals they are connected to. In thesespillover settings, the effects of such interventions can be quantified inseveral ways. The average individual effect measures the intervention effectamong those directly treated, while the spillover effect measures the effectamong those connected to those directly treated. In addition, the overalleffect measures the average intervention effect across the study population,over those directly treated along with those to whom the intervention spillsover but who are not directly treated. Here, we develop methods for studydesign with the aim of estimating individual, spillover, and overall effects.In particular, we consider an egocentric network-based randomized design inwhich a set of index participants is recruited from the population and randomlyassigned to treatment, while data are also collected from their untreatednetwork members. We use the potential outcomes framework to define twoclustered regression modeling approaches and clarify the underlying assumptionsrequired to identify and estimate causal effects. We then develop sample sizeformulas for detecting individual, spillover, and overall effects. Weinvestigate the roles of the intra-class correlation coefficient and theprobability of treatment allocation on the required number of egocentricnetworks with a fixed number of network members for each egocentric network andvice-versa.

Design of egocentric network-based studies to estimate causal effects under interference