Description Usage Arguments Value
Takes a data frame, and a model to fit to the data and each bootstrap replicate. Bootstrapping is by default resampling cases, but if you set boot_resid=TRUE then resampling residuals will be performed. If you pass a null model formula that includes a subset of the variables in the full model (i.e. it is a nested model) then the bootstrap statistics will come from the bootstrapped null data and can be used for a hypothesis test.
1 | slipper_lm_(df, formula, null_formula = NULL, B = 100, boot_resid = FALSE)
|
df |
A data frame |
formula |
A an expression for a formula to pass to the lm command |
null_formula |
(optional) If NULL, standard bootstrapping is performed. If a nested expression for a null formula is passed the bootstrapped statistics come from the null. |
B |
the number of bootstrap samples to draw |
boot_resid |
If TRUE then bootstrapping residuals is performed. |
out A data frame with the values, whether they come from the observed data or the bootstrapped data, and the coefficient name.
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