Binary Data

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Data in an ‘either-or’ format, i.e., in two mutually exclusive categories
Examples Alive/dead; sick/well; pregnant/not; high/sober; benign/malignant
References in periodicals archive ?
Dichotomous data use binary "success" or "failure" categories (1 or 0, respectively) to describe the status of subjects (e.
As a result, 4(50%) studies with3,5,7,8 225 subjects with dichotomous data were used to do meta-analysis.
Hence, these data can be converted to dichotomous data.
The aim of this article is to explain the procedures to conduct a mean structure analysis of dichotomous data from an IRT approach in the one-dimensional case.
Given the dichotomous data of the HMI, it is obviously impossible to impute values for missing data.
Typical metrics in clinical outcomes research include the effect size (the mean difference between treatment and control group) for continuous data and the risk ratio for dichotomous data.
To analyze repeated measures, with dichotomous data, we chose Generalized Estimating Equations (GEE).
Internal consistency for the Knowledge Scale employed the Kuder-Richardson formula, the K-R 20, a special case of Cronbach's alpha coefficient for dichotomous data.
The binomial test was used to assess the distribution of dichotomous data.
A 10% BMR was used for dichotomous data, and a "change in the mean equal to one control SD" BMR was used for continuous data.
Pair-wise comparisons were performed using t-tests for interval data, Mann-Whitney tests for ordinal data and Chi-squared tests for dichotomous data.