CODEWITHSUNDEEP
rstata
chacepaulson
chacepaulson

Reputation: 31

Is there an equivalent to Stata's PSACALC in R?

In a class, we have been utilizing PSACALC in Stata for Oster's bounding for understanding the degree of omitted variable bias in regression. I'm wondering if there is an alternative anyone is aware of in R.

Upvotes: 3

Views: 609

Answers (2)

Saurabh Khanna
Saurabh Khanna

Reputation: 571

You can use the robomit package from Sergei Schaub.

Upvotes: 1

Jonathan
Jonathan

Reputation: 230

I adapted the code from PSACALC and made an R package about two years ago. I've never gotten around to putting it on CRAN (don't know how), but you can install it from my GitHub. Here's a short example reproducing Table 5 from Oster (2019)

#install.packages("devtools")
library(devtools)
#devtools::install_github("siverskog/oster")
library(oster)

data(nunn)

# FORMULA FOR INTERMEDIATE (TILDE) REGRESSION

f01c <- trust_relatives ~ ln_export_area + age + age2 + male + urban_dum +
  as.factor(education) + as.factor(occupation) + as.factor(religion) +
  as.factor(living_conditions) + district_ethnic_frac +
  frac_ethnicity_in_district + as.factor(isocode) + malaria_ecology +
  total_missions_area + explorer_contact + railway_contact + cities_1400_dum +
  as.factor(v30) + v33_alt + ln_init_pop_density

# FORMULA FOR SHORT (O) REGRESSION

f01u <- trust_relatives ~ ln_export_area + as.factor(isocode)

# FITS 

fit01c <- lm(f01c, data = nunn)

nunn$infit01c <- is.element(rownames(nunn), names(fit01c$residuals))
fit01u <- lm(f01u, data = nunn, subset = infit01c) # USE ONLY OBS. IN TILDE FIT

# CALCULATE BETA/DELTA/RMAX WITH oster() TO
# REPRODUCE ROW 1 OF TABLE 5 IN OSTER (2019)

z <- oster(fit01u, fit01c, "ln_export_area")
b13 <- oster(fit01u, fit01c, "ln_export_area", rm = 1.3)$beta

round(c(z$input$beta_o, z$input$beta_tilde, z$beta, b13, z$rmax), 3)

Upvotes: 2

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