lm_error_var: Calculate error variance given model coefficients.

In paramtest: Run a Function Iteratively While Varying Parameters

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.

Details

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

Value

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

Examples

lm_error_var(var=1, .15, .3)  # returns error variance of 0.8875

paramtest documentation built on May 2, 2019, 9:40 a.m.