tidye: Tidy linear model summary

In DiogoFerrari/edar: Exploratory Data Analysis in R

Tidy linear model summary

Description

This function uses tidy to create a data.frame with model results from lm or glm functions

Usage

tidye(
  model,
  digits = 4,
  hc = FALSE,
  hc.type = c("hc3", "hc0", "hc1", "hc2", "hc4"),
  tibble = TRUE,
  keep.nohc = FALSE
)

Arguments

model	an output of lm, glm, or multinom functions. It can also be a list (named or not) with combinations of those objects
digits	integer, the number of significant digitis to use
hc	boolean, if TRUE robust standard errors (heteroskedasticity corrected) are returned
hc.type	a string with the method to compute the standard errors (see hccm)
tibble	boolean, if TRUE, it returns a tibble data.frame. Default TRUE
keep.nohc	boolean, if TRUE and hc=TRUE the std.errors originally estimated will be kept and returned alongside the robust estimates. The original estimates will have the suffix .nohc (no heteroskedasticity corrected)

Examples

set.seed(77)

data = tibble::data_frame(n = 300,
                          x1   = rnorm(n,3,1),
                          x2   = rexp(n),
                          cat1 = sample(c(0,1), n, replace=TRUE),
                          cat2 = sample(letters[1:4], n, replace=TRUE),
                          y    = -10*x1*cat1 + 10*x2*(3*(cat2=='a')
                                 -3*(cat2=='b') +1*(cat2=='c') -1*(cat2=='d')) + 
                              rnorm(n,0,10), 
                          y.bin = ifelse(y < mean(y), 0, 1),
                          y.mul = 1+ifelse( - x1 - x2 + rnorm(n,sd=10) < 0, 0,
                                    ifelse( - 2*x2 + rnorm(n,sd=10) < 0, 1, 2)),
                          )

model.g1 = lm(y ~ x1, data)
model.g2 = lm(y ~ x1 + x2, data)
model.g  = lm(y ~ x1*cat1 + x2*cat2, data)
model.bin = glm(y.bin ~ x1+x2*cat2, data=data, family='binomial')
model.mul <- nnet::multinom(y.mul ~ x1 + x2, data)

## digits and output format
tidye(model.g)
tidye(model.g, digits=12)
tidye(model.g, tibble=FALSE)
tidye(model.g, digits=12, tibble=FALSE)

## other model types
tidye(model.bin)
tidye(model.mul)

## with robust std.errors
tidye(model.g, hc=TRUE)
tidye(model.g, hc=TRUE, keep.nohc=TRUE) # keep no heterocedastic corrected std.errors
tidye(model.bin, hc=TRUE)

## list of models
tidye(list(model.g), hc=TRUE)
tidye(list(model.g, model.bin, model.mul))
tidye(list(Gaussian=model.g, Binomial=model.bin, Multinomial=model.mul))
tidye(list(model.g, model.g1, model.g2), hc=TRUE)
tidye(list('Only model'=model.g))

DiogoFerrari/edar documentation built on May 8, 2022, 8:26 a.m.