Fuzzy statistics and random variables represent a progressive fusion of traditional probability theory with the principles of fuzzy logic, enabling the treatment of imprecision and vagueness ...

Dichotomizing a continuous outcome variable casts that variable in traditional epidemiologic terms (that is, disease, no disease). One consequence is overall reduced statistical power. A more ...

David B. Dunson, Bayesian Latent Variable Models for Clustered Mixed Outcomes, Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 62, No. 2 (2000), pp. 355-366 ...

You don't need a crystal ball to tell you what is going to happen next in the economy. You need a statistical model. A new method can help researchers determine which economic variables they ...

Statistical Process Control (SPC) charting has long been recognized as a method for monitoring processes of all types. This webinar will discuss the application of basic SPC to variable data, and ...

This refers to any bias in a predictive model which is the result of the omission of variables that are relevant to the outcome. The omission of a relevant variable can, among other things, lead ...

suppresses the display of default statistics considers missing values as valid level values for only one class variable orders observations in the output data set by the ascending frequency for a ...