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
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References in periodicals archive ?
Dichotomous data. Dichotomous data use binary "success" or "failure" categories (1 or 0, respectively) to describe the status of subjects (e.g., animals tested in a toxicity study) treated at various dose levels with or without an effect (e.g., cancer).
(a) Subgroup analysis of dichotomous data for mRS defined by time widow of intervention.
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.
Dichotomous data are presented as counts or frequencies and continuous variables summarized as means (SD).
They worked with multidimensional dichotomous data, different sample sizes and percentages of DIF bigger than we defined in this study.
Additionally, how the regression dilution factor applies to dichotomous data is not clear, although it is applicable to survival and logistic regression as well as to bivariate quantitative data (5).
Data were compared across the three groups using analysis of variance for interval data, Kruskal-Wallis test for ordinal data and the Chi-squared test for dichotomous data, with post hoc Bonferroni's correction.
The forced-choice response set of the HMI yields dichotomous data that were coded with the hypermasculine option as a one, and its opposite as a zero.
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).
The data were analyzed using a 2 ([e.sub.A]) x 3 ([r.sub.R]) x 6 ([r.sub.A]) repeated-measures analysis of variance (see Myers, DiCecco, White, & Borden, 1982, for discussion of use of the F test to analyze dichotomous data).