Sentence examples for binary data can be from inspiring English sources

For example, visualizing the surface of binary data can be written as (see Fig. 4 for the resulting visualization).

The analysis of binary data can be greatly enhanced by Yule's transformation of odds ratios into estimated correlation matrix that can be further analysed by SEM.

As only binary data can be analysed with the Crossing-SIBTEST, categories on the rating scale were combined as follows: no difficulty vs. the rest.

It is defined as [ 18, 19] D i j = b + c a + b + c Similarly, one can use the Jaccard similarity coefficient which is defined as (1-D i, j) and is given by S i j = a a + b + c Binary data can be nominal or ordinal where in the latter case presence ("1") more in some sense than absence ("0").

Sex was deleted in this analysis due to its two-category response format since binary data can be difficult to analyze with SEM [ 32], requiring either very large sample sizes for asymptotic least squares or integration of the multivariate normal distribution over as many dimensions as there are relatives in the pedigree [ 33].

Using equations (1) and (2), the family of asymmetric transformations for univariate binary response data can be written as log{[ 1- π)- λ -1]/ λ} = X'β     (3) Using simple calculations, one can show that for λ = 1 equation (3) reduces to the ordinary logistic model, while for λ→0 the complementary log-log model is obtained.

Unreported confidence intervals for large sample paired binary and numeric data can be computed fairly accurately using simple methods provided the p-value is given.

When the outcome in each independent study is a binary variable, the data can be viewed as a two-by-two contingency table, with each cell corresponding to counts of events (e.g. the number of people with and without disease) in separate groups, for example, participants assigned to treatment and control arms of an intervention study.

The same holds true for the censored data, as the threshold values are set to correspond the thresholds of the binary phenotype: the 20%and80%0% censored data can be compared with the binary data with 80% success rate, as the proportions of the observations belonging to the classes is 20 80, and similarly the 50% censored data are equivalent to the 50% or 50 50 binary data.

DNA copy number amplification data can be presented as binary vectors x ∈ {0,1} d in which x i = 1 denotes an amplified chromosome band and x i = 0 stands for a non-amplified band and d is the number of bands.

Raw data can be downloaded either as binary (Affymetrix) or text (spotted) files.