Blazing fast and highly versatile! The fixest package for fixed effects regressions in R

See the project page here: https://lrberge.github.io/fixest/ and install fixest using install.packages('fixest') NOTE: As of fixest 0.9.0 (released after this video), the syntax for i() with interactions has changed. You now want the factor first, THEN the continuous variable. The line should be m9 = feols(crmrte ~ polpc + density + taxpc + wcon + i(factor_avgsen, wcon, ref = 8) | county + year, data = crime4) Code from the video (adjusted to remove all greater-than or less-than signs for YouTube description rules): library(wooldridge) data(crime4) library(fixest) m1 = feols(crmrte ~ polpc + density + taxpc | county + year, data = crime4) etable(m1) m2 = feols(crmrte ~ polpc + density + taxpc | county + year, data = crime4, se = 'hetero') m3 = feols(crmrte ~ density + taxpc | county + year | polpc ~ prbarr, data = crime4) m4 = feglm( ~ polpc + density + taxpc | county + year, data = crime4) crime4$lowcrime = floor(crime4$crmrte*100) %in% 0:2 m5 = feglm(lowcrime ~ polpc + density + taxpc | county + year, data = crime4, cluster = c('county', 'year')) m6 = feols(lowcrime ~ density + d(taxpc) | county + year | polpc ~ prbarr, data = crime4, panel.id = c('county', 'year')) esttable(m6) m7 = feols(crmrte ~ density + taxpc | county + year | polpc ~ prbarr, data = crime4, fsplit = 'urban') esttable(m7) crime4$factor_avgsen = round(crime4$avgsen) m8 = feols(crmrte ~ polpc + density + taxpc + i(factor_avgsen, ref = 5) | county + year, data = crime4) m9 = feols(crmrte ~ polpc + density + taxpc + wcon + i(wcon, factor_avgsen, ref = 8) | county + year, data = crime4) esttable(m9)

Видео Blazing fast and highly versatile! The fixest package for fixed effects regressions in R автора JavaScript и Progressive Web Apps