se.slope: Computes a slope and standard error

In dgbonett/vcmeta: Varying Coefficient Meta-Analysis

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

\insertRef

Snedecor1980vcmeta

Examples

se.slope(.392, 4.54, 2.89, 60)

# Should return: 
#          Estimate        SE
# Slope:  0.6158062 0.1897647

dgbonett/vcmeta documentation built on July 12, 2024, 3:12 p.m.