Multivariate statistics for categorical outcomes
Choice of multivariate statistical test depends upon the type of categorical outcome
Survival or time-to-event analysis falls under the guise of multivariate statistics with categorical outcomes. These types of statistics are used to understand the temporal differences among independent groups in terms of developing an outcome or disease state. When conducting survival statistics, researchers need a primary predictor variable denoting group membership, a dichotomous categorical outcome variable with one level defined as the "event," and some sort of time signature associated with developing the outcome. The time increment of the temporal differences can be in seconds, minutes, hours, days, weeks, months, or even years, depending upon the etiology and prognosis of the event or disease state of interest.
Choosing the correct multivariate statistical test for a categorical outcome or ordinal outcome depends upon the number of levels of the variable that are being measured.
What type of categorical outcome is being used for multivariate statistics?
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