fixest (version 0.8.4)

stepwise: Stepwise estimation tools

Description

Functions to perform stepwise estimations.

Usage

stepwise(...)
sw(...)
cstepwise(...)
csw(...)
stepwise0(...)
sw0(...)
cstepwise0(...)
csw0(...)

Arguments

...

Represents formula variables to be added in a stepwise fashion to an estimation.

Details

To include multiple independent variables, you need to use the stepwise functions. There are 4 stepwise functions associated to 4 short aliases. These are a) stepwise, stepwise0, cstepwise, cstepwise0, and b) sw, sw0, csw, csw0. Let's explain that.

Assume you have the following formula: fml = y ~ x1 + sw(x2, x3). The stepwise function sw will estimate the following two models: y ~ x1 + x2 and y ~ x1 + x3. That is, each element in sw() is sequentially, and separately, added to the formula. Would have you used sw0 in lieu of sw, then the model y ~ x1 would also have been estimated. The 0 in the name means that the model wihtout any stepwise element also needs to be estimated.

Finally, the prefix c means cumulative: each stepwise element is added to the next. That is, fml = y ~ x1 + csw(x2, x3) would lead to the following models y ~ x1 + x2 and y ~ x1 + x2 + x3. The 0 has the same meaning and would also lead to the model without the stepwise elements to be estimated: in other words, fml = y ~ x1 + csw0(x2, x3) leads to the following three models: y ~ x1, y ~ x1 + x2 and y ~ x1 + x2 + x3.

Examples

# NOT RUN {
base = iris
names(base) = c("y", "x1", "x2", "x3", "species")

# Regular stepwise
feols(y ~ sw(x1, x2, x3), base)

# Cumulative stepwise
feols(y ~ csw(x1, x2, x3), base)

# Using the 0
feols(y ~ x1 + x2 + sw0(x3), base)

# }