Consider a linear predictor having linear and square terms
associated with a variable \(x\). Assume this variable was centered
before being included in the linear predictor. This functions recovers the
regression coefficient associated to the linear term as if the variable
was not centered.
Usage
fix_linbeta(beta1, beta2, offset)
Arguments
- beta1
A numeric regression coefficient associated to the
linear term.
- beta2
A numeric regression coefficient associated to the
quadratic term.
- offset
a numeric representing the "center" of \(x\).
Value
a numeric representing the regression coefficient of the
linear term for the model where \(x\) is not centered.