Title: | Regression Table for Publication |
---|---|
Description: | Create regression tables for publication. Currently supports 'lm', 'glm', 'survreg', and 'ivreg' outputs. |
Authors: | Kota Mori [aut, cre] |
Maintainer: | Kota Mori <[email protected]> |
License: | MIT + file LICENSE |
Version: | 0.2.2 |
Built: | 2025-01-02 02:55:43 UTC |
Source: | https://github.com/kota7/outreg |
Return display name for stats
get_display_names(stats)
get_display_names(stats)
stats |
character vector of stats |
character vector of display names
Generate a regression table in data.frame
format from a set of model fit objects.
Currently supports lm
, glm
, survreg
, and ivreg
model outcomes.
outreg(fitlist, digits = 3L, alpha = c(0.1, 0.05, 0.01), bracket = c("se"), starred = c("coef"), robust = FALSE, small = TRUE, constlast = FALSE, norepeat = TRUE, displayed = list(), ...)
outreg(fitlist, digits = 3L, alpha = c(0.1, 0.05, 0.01), bracket = c("se"), starred = c("coef"), robust = FALSE, small = TRUE, constlast = FALSE, norepeat = TRUE, displayed = list(), ...)
fitlist |
list of regression outcomes |
digits |
number of dicimal places for real numbers |
alpha |
vector of significance levels to star |
bracket |
stats to be in brackets |
starred |
stats to put stars on |
robust |
if TRUE, robust standard error is used |
small |
if TRUE, small sample parameter distribution is used |
constlast |
if TRUE, intercept is moved to the end of coefficient list |
norepeat |
if TRUE, repeated variable names are replaced by a empty string |
displayed |
a list of named logicals to customize the stats to display |
... |
alternative way to specify which stats to display |
Use outreg_stat_list
to see the available stats
names. The stats names are to be used for specifying
bracket
, starred
, and displayed
options.
Statistics to include can be chosen by displayed
option or
by `...`
.
For example, outreg(fitlist, displayed = list(pv = TRUE))
is
identical with outreg(fitlist pv = TRUE)
, and
p values of coefficients are displayed.
regression table in data.frame
format
fitlist <- list(lm(mpg ~ cyl, data = mtcars), lm(mpg ~ cyl + wt + hp, data = mtcars), lm(mpg ~ cyl + wt + hp + drat, data = mtcars)) outreg(fitlist) # with custom regression names outreg(setNames(fitlist, c('small', 'medium', 'large'))) # star on standard errors, instead of estimate outreg(fitlist, starred = 'se') # include other stats outreg(fitlist, pv = TRUE, tv = TRUE, se = FALSE) # poisson regression counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9) treatment <- gl(3,3) fitlist2 <- list(glm(counts ~ outcome, family = poisson()), glm(counts ~ outcome + treatment, family = poisson())) outreg(fitlist2) # logistic regression fitlist3 <- list(glm(cbind(ncases, ncontrols) ~ agegp, data = esoph, family = binomial()), glm(cbind(ncases, ncontrols) ~ agegp + tobgp + alcgp, data = esoph, family = binomial()), glm(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp, data = esoph, family = binomial())) outreg(fitlist3) # survival regression library(survival) fitlist4 <- list(survreg(Surv(time, status) ~ ph.ecog + age, data = lung), survreg(Surv(time, status) ~ ph.ecog + age + strata(sex), data = lung)) outreg(fitlist4) # tobit regression fitlist5 <- list(survreg(Surv(durable, durable>0, type='left') ~ 1, data=tobin, dist='gaussian'), survreg(Surv(durable, durable>0, type='left') ~ age + quant, data=tobin, dist='gaussian')) outreg(fitlist5) # instrumental variable regression library(AER) data("CigarettesSW", package = "AER") CigarettesSW$rprice <- with(CigarettesSW, price/cpi) CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi) CigarettesSW$tdiff <- with(CigarettesSW, (taxs - tax)/cpi) fitlist6 <- list(OLS = lm(log(packs) ~ log(rprice) + log(rincome), data = CigarettesSW, subset = year == "1995"), IV1 = ivreg(log(packs) ~ log(rprice) + log(rincome) | log(rincome) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995"), IV2 = ivreg(log(packs) ~ log(rprice) + log(rincome) | log(population) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995")) outreg(fitlist6)
fitlist <- list(lm(mpg ~ cyl, data = mtcars), lm(mpg ~ cyl + wt + hp, data = mtcars), lm(mpg ~ cyl + wt + hp + drat, data = mtcars)) outreg(fitlist) # with custom regression names outreg(setNames(fitlist, c('small', 'medium', 'large'))) # star on standard errors, instead of estimate outreg(fitlist, starred = 'se') # include other stats outreg(fitlist, pv = TRUE, tv = TRUE, se = FALSE) # poisson regression counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9) treatment <- gl(3,3) fitlist2 <- list(glm(counts ~ outcome, family = poisson()), glm(counts ~ outcome + treatment, family = poisson())) outreg(fitlist2) # logistic regression fitlist3 <- list(glm(cbind(ncases, ncontrols) ~ agegp, data = esoph, family = binomial()), glm(cbind(ncases, ncontrols) ~ agegp + tobgp + alcgp, data = esoph, family = binomial()), glm(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp, data = esoph, family = binomial())) outreg(fitlist3) # survival regression library(survival) fitlist4 <- list(survreg(Surv(time, status) ~ ph.ecog + age, data = lung), survreg(Surv(time, status) ~ ph.ecog + age + strata(sex), data = lung)) outreg(fitlist4) # tobit regression fitlist5 <- list(survreg(Surv(durable, durable>0, type='left') ~ 1, data=tobin, dist='gaussian'), survreg(Surv(durable, durable>0, type='left') ~ age + quant, data=tobin, dist='gaussian')) outreg(fitlist5) # instrumental variable regression library(AER) data("CigarettesSW", package = "AER") CigarettesSW$rprice <- with(CigarettesSW, price/cpi) CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi) CigarettesSW$tdiff <- with(CigarettesSW, (taxs - tax)/cpi) fitlist6 <- list(OLS = lm(log(packs) ~ log(rprice) + log(rincome), data = CigarettesSW, subset = year == "1995"), IV1 = ivreg(log(packs) ~ log(rprice) + log(rincome) | log(rincome) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995"), IV2 = ivreg(log(packs) ~ log(rprice) + log(rincome) | log(population) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995")) outreg(fitlist6)
Returns all available statistics on outreg
.
Statistics names can be used for customizing the outputs, e.g.,
to choose stats to display or to choose stats to put starts.
outreg_stat_list()
outreg_stat_list()
a data.frame that matches stat name and display name
outreg_stat_list()
outreg_stat_list()