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The weighted mean difference (WMD) was used for continuous data, while the risk ratio (RR) was used for binary data.
For statistical analysis, Fisher's exact test has been used for binary data and the Mann–Whitney U-test for continuous data (R v2.15.1).
Canonical link functions that are commonly used for binary data are the probit and logit link functions [ 23], which assume that the probability of the trait to be equal to one, i.e. to have become infected in our case, follows a cumulative normal or a logistic distribution, respectively [ 23].
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The same type of models can be used for binary endpoints, but data are typically logit-transformed in order to apply nonlinear logistic regression, with an underlying model such as the Emax model, similar to models of continuous data.
We test our approach on Keirn and Aunon's data, used for binary classification of electroencephalogram signals, achieving promising results.
8 Efficacy analyses were performed in the intent-to-treat (ITT) population (randomised patients who received ≥1 administration of study medication) with non-responder imputation of missing data used for binary response variables (eg, DAS28-ESR remission and ACR response).
Because the test is based on observed and expected numbers of "positive" results, it can be used for binary, continuous or time-to-event outcome data.
A commonly used statistical model for binary data is the logistic regression model.
The Jaccard similarity matrix is the most commonly used distance matrix for binary data.
Here we will present the two commonly used distance/similarity measures for binary data: Jaccard and simple matching similarity measures.
For the main analyses concentrating on primary and secondary outcomes, linear growth curve models for normally distributed outcome measurements will be used, logistic regression for binary data, and Poisson regression models for ordinal data.
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