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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Avoiding excessive enrollment of a single cohort in a clinical trial is prudent in order to avoid imbalances and to prevent one cohort from having a disproportionate influence on the results of a trial and perhaps even negating positive findings of the clinical trial. Numerical criteria are provided here to evaluate the expected influence of a large cohort as a function of both its size and the relative effect of interventions, in comparison to those of other groups. Measures of expected influence are obtained as a function of the parameters of the distribution of statistics measuring influence. Calculated numerical criteria for the binomial, continuous and time-to-event contexts are presented. Details of the application of this method and sensitivity analyses conducted during the planning stages of a multiple myeloma clinical trial are provided. Numerical criteria are derived under asymptotic conditions and thus results hold for large cohorts. The numerical criteria are easy to compute and are useful tools to assess possible detrimental effects of large cohorts during the design of a study or during enrollment prior to any un-blinding. The numerical criteria allow for a-priori sensitivity analyses of the likely influence of large cohorts under varying conditions.

journal of statistical science and application

Measures of Expected Influence Provide Useful Constraints to Enrollment in Randomized Multi-Center Clinical Trials for Binomial, Continuous and Time-to-Event Endpoints