categorical data


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Related to categorical data: Numerical data

categorical data

A term used in the context of a clinical trial for data evaluated by sorting values—e.g., severe, moderate and mild—into various categories.

categorical data

data relating to category such as qualitative data, e.g. dog, cat, female. It may be nominal when a name is used, e.g. location, breed, or ordinal when a range of categories is used, e.g. calf, yearling, cow.
References in periodicals archive ?
In addition, the schemes discussed above including those for categorical data, introduce distortion in the contents by changing meaning of attribute values which is often not desirable.
But as long as government consumption and transfer payments follow the same long-run growth trend, this proxy should not result in any serious bias because our empirical analysis is based on categorical data.
Since order means nothing in non-ordinal categorical data, this transforms the variable in a manner appropriate for the assumptions of the model to be valid.
1999) is based on the clustering of categorical data.
7 Continuous data are expressed as Mean [+ or -] SD, categorical data are expressed as n (%) PM--pacemaker Table 2.
Categorical data are displayed as number of patients, ordinal data as median (IQR).
The categories allow for the investigation of associations between the degree of acceptance of evolutionary theory and categorical data such as gender, academic rank, and specific academic coursework.
The [chi square] Pearson Chi Square test was employed for categorical data with normal distribution and the [G.
The two groups were compared using descriptive statistics, namely frequency and percentages for categorical data, and medians and percentiles for continuous data.
Table 3, referred to in Olli Jaakkola's article on "Multi-scale Categorical Data Bases with Automatic Generalization Transformations Based on Map Algebra" in CaGIS vol.
For a broader introduction to categorical data analysis and an understanding of the relationship between contingency tables and generalized linear models, the book of Agresti (2) is suggested.
He has expertise in experimental design, power calculations, survival analyses, categorical data analyses, de-identification of data sources, big data sampling problems and Quality of Life analyses.