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 ...

Cox model marginal survivor function and pairwise correlation models are specified for a multivariate failure time vector. The corresponding mean and covariance structure for the cumulative baseline ...

Multivariate longitudinal data are common in medical, industrial, and social science research. However, statistical analysis of such data in the current literature is restricted to linear or ...

Cell proliferation-related markers in colorectal liver metastases: correlation with patient prognosis. We analyzed 2,536 cases of surgically resected gastric adenocarcinoma of all pathologic stages.

The Unscrambler® is a complete Multivariate Analysis and Experimental Design (DoE) software solution that is equipped with powerful methods, including PCA, Multivariate Curve Resolution (MCR), PLS ...

In addition to point estimates (e.g., % approving of President Barack Obama’s job performance), public opinion polls are often used to determine what factors explain a given attitude or behavior. For ...

This course is available on the Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MSc in Applied Social Data Science, MSc in European and ...

MANOVA is a statistical test that extends the scope of the more commonly used ANOVA, that allows differences between three or more independent groups of explanatory (independent or predictor) ...

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 ...