IV2SLS binary estimator: two-stage predictor substitution with logistic / LPM

Two-stage predictor substitution (2SPS): the first stage regresses X on the instrument G (plus W and covariates) via OLS, producing fitted \(\hat X\); the second stage regresses the binary outcome on \(\hat X\) (plus W and covariates) via logistic regression (log-OR) or a linear probability model (risk difference).

Usage

fit_iv2sls_bin(
  y,
  X,
  g,
  w,
  covars = NULL,
  min_f = 10,
  effect_scale = c("logor", "riskdiff")
)

Arguments

y

Numeric 0/1 outcome vector (length n).

X

Numeric exposure vector (length n).

g

Numeric instrument vector (length n).

w

Numeric NC vector (length n) or matrix (n x q).

covars

Optional data frame of covariates (n rows).

min_f

Minimum partial F for the excluded instrument. Default 10.

effect_scale

Character: "logor" or "riskdiff".

Value

Named list: beta, se, pvalue.

Details

A weak-instrument check (partial F for the excluded instrument G, Stock & Yogo 2005) is applied to the OLS first stage. If the partial F is below min_f, the function returns NA.

Examples

set.seed(1)
dat <- generate_toy_data(n = 200, outcome_type = "binary", seed = 1)
fit_iv2sls_bin(dat$y_bin, dat$X, dat$G[, 1], dat$W[, 1])
#> $beta
#> [1] -0.01277931
#> 
#> $se
#> [1] 0.2630275
#> 
#> $pvalue
#> [1] 0.9612497
#>