insider.si.edu

Applied multivariate statistical analysis / Richard A. Johnson, Dean W. Wichern

1. Aspects of multivariate analysis -- 2. Matrix algebra and random vectors -- 3. Sample geometry and random sampling -- 4. The multivariate normal distribution -- 5. Inferences about a mean vector -- ...
Semiconductor Engineering

Multivariate Analysis For Full Process Visibility

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...
ascopubs.org

Multivariate analysis of PFS from the AETHERA trial: A phase III study of brentuximab vedotin consolidation after autologous stem cell transplant for HL.

Combination of everolimus with R-CHOP (ever R-CHOP) as an initial therapy for diffuse large B-cell lymphoma (DLBCL): A phase I and feasibility study (NCCTG N1085 [Alliance]). Multivariate analyses of ...
JSTOR Daily

Forecasting Single Disease Cost of Cataract Based on Multivariable Regression Analysis and Backpropagation Neural Network

Department of Health and Aging Australia. The Review of the AR-DRG Classification System Development Process: Brisbane, QLD, Australia: PricewaterhouseCoopers; 2009. 2. Klein-Hitpass U, ...
ascopubs.org

Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses

A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative ...
JSTOR Daily

Multivariate Fay–Herriot Bayesian estimation of small area means under functional measurement error

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 180, No. 4 (OCTOBER 2017), pp. 1191-1209 (19 pages) Area level models, such as the Fay–Herriot model, aim to improve ...
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Linear vs. multiple regression explained

Linear regression analyzes the relationship between two variables. Multiple regression examines several variables' effects on a single outcome. Both techniques predict an outcome based on historical ...