Sentence examples for binary and clustered outcomes from inspiring English sources

The analysis is extended to models with categorical treatments and binary and clustered outcomes.

We systematically outline sample size formulae (including required number of randomisation units, detectable difference and power) for CRCTs with a fixed number of clusters, to provide a concise summary for both binary and continuous outcomes.

A two-level hierarchical model with binary clustering outcome was estimated with the high SEP quartile serving as the referent.

Cheng et al. used sensitivity analyses to compare different methods (six models for clustered binary outcomes and three models for clustered nominal outcomes) of analysing correlated data in discrete choice surveys [ 49].

Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor.

Binary and continuous outcomes were analyzed separately.

Statistical analysis: Unadjusted ORs and mean differences were calculated for binary and continuous outcomes, respectively.

We used logistic and normal regression models for binary and continuous outcomes, respectively.

Binary and multinomial outcomes were described using the number and percentage endorsing.

The statistical models (for both binary and continuous outcomes) were built as follows.

A mixed model for continuous outcome variables with random intercepts corresponding to "birth clusters" and ordinary logistic regression for binary (and ordinal) outcome variables was planned per protocol.