Multivariate analyses such as principal component analysis were among the first statistical methods employed to extract information from genetic markers. From their early applications to current ...

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 177, No. 2 (FEBRUARY 2014), pp. 553-564 (12 pages) The paper extends existing models for multilevel multivariate data ...

Nonparametric methodology for longitudinal data analysis is becoming increasingly popular. The analysis of multivariate longitudinal data, where data on several time courses are recorded for each ...

Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Before we learn how to perform multivariate regression in Excel, it is important to have a refresher on regression as a whole and multivariate regression in particular. One of the hallmarks of human ...

Four poor prognostic factors were identified and a simple prognostic index was devised. Information from this analysis can be used to aid clinical decision-making, help individual patient risk ...

Our research group develops modern and efficient multivariate statistical methods tailored for different types of multivariate data, such as time series, spatial data, spatio-temporal data, or ...

Explainable predictive AI in Qlik Cloud lets teams model real-world drivers and update plans in-app with WriteTable for faster outcomes PHILADELPHIA--(BUSINESS WIRE)--October 30, 2025-- Qlik(R) , a ...