Chapter FOUR. Variance Matrices and Linear Transformations
Published Online: 11 AUG 2003
DOI: 10.1002/0471467979.ch4
Copyright © 2003 John Wiley & Sons, Inc.
Book Title
Quantitative Methods in Population Health: Extensions of Ordinary Regression
Additional Information
How to Cite
Palta, M. (2003) Variance Matrices and Linear Transformations, in Quantitative Methods in Population Health: Extensions of Ordinary Regression, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471467979.ch4
Publication History
- Published Online: 11 AUG 2003
- Published Print: 15 AUG 2003
Book Series:
Book Series Editors:
- Walter A. Shewhart,
- Samuel S. Wilks
ISBN Information
Print ISBN: 9780471455059
Online ISBN: 9780471467977
- Summary
- Chapter
Keywords:
- variance matrix;
- correlation matrix;
- linear transformation;
- variance of difference;
- variance of mean;
- paired t-test;
- matching;
- interaction effect;
- standard error;
- PROC TTEST
Summary
We define the variance matrix including covariance elements. Correlation matrix. Definition of linear transformation. Variance matrix of a linear transformation. Application of variance formula to obtain the variance of means and difference of correlated observations. Implications for study design Example of comparing the variance used for paired and unpaired t-test. Obtaining the standard error of the regression coefficient of a main effect in the presence of interaction two ways, applied to the regression of systolic blood pressure on age, BMI and their interaction. PROC REG with the COVB feature to obtain the variance matrix of the regression coefficients. Paired and unpaired t-tests by PROC TTEST illustrated by comparison of glycosylated hemoglobin between first two years of type 1 diabetes.