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Estimates a linear IV model via 2SLS (rmorie native k-class engine).

Usage

morie_iv_tsls(
  data,
  outcome,
  endogenous,
  instruments,
  exogenous = NULL,
  cluster = NULL,
  robust = TRUE,
  alpha = 0.05
)

Arguments

data

Data frame.

outcome

Name of the outcome column.

endogenous

Character vector of endogenous regressor names.

instruments

Character vector of excluded-instrument names.

exogenous

Optional character vector of exogenous covariate names.

cluster

Optional name of a cluster ID column.

robust

Logical; if TRUE use HC1 robust standard errors.

alpha

Significance level for confidence intervals.

Value

A list with class morie_iv_result containing coefficients, standard errors, t-statistics, p-values, confidence interval bounds, variable names, sample size, method label, and a details list.

Examples

set.seed(2)
n <- 1000
z <- rbinom(n, 1, 0.5); u <- rnorm(n)
d <- rbinom(n, 1, plogis(0.8 * z + 0.3 * u))
y <- 0.5 * d + 0.4 * u + rnorm(n, sd = 0.5)
df <- data.frame(y, d, z)
res <- morie_iv_tsls(df, "y", "d", "z")
res$coefficients["d"]
#>         d 
#> 0.6149994