When a regression is calculated with a simple linear model that returns intercept and slope for an equation like this $y=a + bx$ one can predict $y$, the response variable, based on that equation. Equally one could rearrange for $x$: $x=\frac{\left(y-a\right)}{b}$ and calculate the value of $x$. This isn't available in R's predict()
function but can easily be done. Can one do this calculation and still be statistically sound?
Why inverse of 'predict' function in r can not be used for dependent variable prediction in linear model
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