marginal_effects.Rd
Get all marginal effects of variables in the fit
marginal_effects(fit, variable = "all", data = NA, size = NA, trim = 0.05)
fit | model fitted by |
---|---|
variable | which variable to calculate marginal effects on |
data | optional data.frame that specifies level of data to calculate marginal effects |
size | What bin size to use when varying the variable of interest |
trim | What to trim the variable of interest at, 0 < trim < 0.5 |
This function defaults to using the average defaults to average for all coefficients except variable chosen. If you want to vary a covariate but keep everything else fixed at a certain level, you can specify the data argument. The size argument defaults to a bin size of 1/3 of the standard deviation of the variable, and the trim defaults to using the 95th percentile instead of the max because there may be large outliers. You can over-ride by setting trim to 0, which will use the min and max. By default, marginal effects will calculate marginal effects for all variables.