paramtest (version 0.1.0)

lm_error_var: Calculate error variance given model coefficients.

Description

lm_error_var will calculate the required error variance for a linear model, given specified model coefficients, to create variance for your dependent variable of approximately 'var'.

Usage

lm_error_var(var = 1, ...)

Arguments

var

The variance you wish your dependent variable to be.

...

Pass along all model coefficients, excluding the intercept. These can be named or unnamed.

Value

Returns the required error variance so that the variance of your dependent variable is approximately 'var'.

Details

Note: This function assumes that all predictors are independent (i.e., uncorrelated).

Examples

# NOT RUN {
lm_error_var(var=1, .15, .3)  # returns error variance of 0.8875
# }