cor2cov

Function to convert a correlation matrix to a covariance matrix.

 design 

Implements methods that are useful in designing research studies and analyzing data, with
particular emphasis on methods that are developed for or used within the behavioral,
educational, and social sciences (broadly defined). That being said, many of the methods
implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a
suite of functions for a variety of related topics, such as effect sizes, confidence intervals
for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size
planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and
minimum-risk point estimation perspectives), mediation analysis, various properties of
distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally
an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became
more general and now contains methods applicable and used in a wide variety of fields and is an
orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has
greatly benefited from others, see <https://www3.nd.edu/~kkelley/site/MBESS.html> for a detailed
list of those that have contributed and other details.

Ken Kelley

MBESS

The MBESS R Package

cor2cov function

<dl> <dt>cor.mat</dt>
<dd>the correlation matrix to be converted</dd> <dt>sd</dt>
<dd>a vector that contains the standard deviations of the variables in the correlation matrix</dd> <dt>discrepancy</dt>
<dd>a neighborhood of 1, such that numbers on the main diagonal of the correlation matrix
 will be considered as equal to 1 if they fall in this neighborhood</dd></dl>

Arguments

Ken Kelley (University of Notre Dame; <a href="/link/KKelley%40ND.Edu?package=MBESS&version=4.9.3" data-mini-rdoc="MBESS::KKelley@ND.Edu">KKelley@ND.Edu</a>), Keke Lai

Author

Correlation Matrix to Covariance Matrix Conversion — cor2cov

<dl>

 <dt>cor.mat</dt>
<dd>the correlation matrix to be converted</dd>

 <dt>sd</dt>
<dd>a vector that contains the standard deviations of the variables in the correlation matrix</dd>

 <dt>discrepancy</dt>
<dd>a neighborhood of 1, such that numbers on the main diagonal of the correlation matrix
 will be considered as equal to 1 if they fall in this neighborhood</dd>

</dl>

Ken Kelley (University of Notre Dame; <a href='mailto:KKelley@ND.Edu'>KKelley@ND.Edu</a>), Keke Lai

cor2cov: Correlation Matrix to Covariance Matrix Conversion

Description

Usage

Arguments

Author

Details