se.slope {vcmeta} | R Documentation |
Computes a slope and standard error
Description
This function computes a slope and its standard error for a simple linear regression model (random-x model) using the estimated Pearson correlation and the estimated standard deviations of the response variable and predictor variable. This function is useful in a meta-analysis of slopes of a simple linear regression model where some studies report the Pearson correlation but not the slope.
Usage
se.slope(cor, sdy, sdx, n)
Arguments
cor |
estimated Pearson correlation |
sdy |
estimated standard deviation of the response variable |
sdx |
estimated standard deviation of the predictor variable |
n |
sample size |
Value
Returns a one-row matrix:
Estimate - estimated slope
SE - standard error
References
Snedecor GW, Cochran WG (1980). Statistical methods, 7th edition. ISU University Pres, Ames, Iowa.
Examples
se.slope(.392, 4.54, 2.89, 60)
# Should return:
# Estimate SE
# Slope: 0.6158062 0.1897647
[Package vcmeta version 1.4.0 Index]