## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 5.5, fig.height = 4.5, fig.align = "center", dpi = 150 ) ## ----load--------------------------------------------------------------------- # load the package library(iv.sensemakr) # load the dataset data("card") ## ----ols---------------------------------------------------------------------- # OLS regression of log wages on education and covariates card.ols <- lm(lwage ~ educ + exper + expersq + black + south + smsa + reg661 + reg662 + reg663 + reg664 + reg665 + reg666 + reg667 + reg668 + smsa66, data = card) coef(card.ols)["educ"] confint(card.ols)["educ", ] ## ----fit---------------------------------------------------------------------- # prepare data y <- card$lwage # outcome: log wage d <- card$educ # treatment: years of education z <- card$nearc4 # instrument: proximity to college x <- model.matrix(~ exper + expersq + black + south + smsa + reg661 + reg662 + reg663 + reg664 + reg665 + reg666 + reg667 + reg668 + smsa66, data = card) # fit the IV model card.fit <- iv_fit(y, d, z, x) card.fit ## ----sensemakr-full----------------------------------------------------------- # with all parameters shown explicitly card.sens <- sensemakr(model = card.fit, benchmark_covariates = c("black", "smsa"), kz = 1, # benchmark multiplier for Z ky = 1, # benchmark multiplier for Y q = 1, # reduce estimate to zero alpha = 0.05) # significance level ## ----sensemakr-simple--------------------------------------------------------- card.sens <- sensemakr(card.fit, benchmark_covariates = c("black", "smsa")) ## ----------------------------------------------------------------------------- card.sens ## ----plot-ci, fig.width = 10, fig.height = 5---------------------------------- plot(card.sens, lim = 0.09)