waive: WAIVE: Weighted Adjusted Instrumental Variable Estimator

Description

WAIVE extends MAIVE by applying exponential-decay weights that downweight studies with spurious precision or extreme outlier behavior.

Usage

waive(dat, method, weight, instrument, studylevel, SE, AR, first_stage = 0L)

Value

List with the same structure as maive(). See ?maive for details.

Arguments

dat: Data frame with columns bs, sebs, Ns, study_id (optional).
method: 1 FAT-PET, 2 PEESE, 3 PET-PEESE, 4 EK.
weight: 0 no weights, 1 standard weights, 2 MAIVE adjusted weights, 3 study weights.
instrument: 1 yes, 0 no.
studylevel: Correlation at study level: 0 none, 1 fixed effects, 2 cluster.
SE: SE estimator: 0 CR0 (Huber-White), 1 CR1 (Standard empirical correction), 2 CR2 (Bias-reduced estimator), 3 wild bootstrap.
AR: Anderson Rubin corrected CI for weak instruments (available for unweighted and MAIVE-adjusted weight versions of PET, PEESE, PET-PEESE, not available for fixed effects): 0 no, 1 yes.
first_stage: First-stage specification for the variance model: 0 levels, 1 log.

Details

Computes robust downweighting based on first-stage residuals. Studies with negative residuals (spurious precision) or extreme residuals (outliers) receive reduced influence in the meta-analytic estimate.

Examples

Run this code

dat <- data.frame(
  bs = c(0.5, 0.45, 0.55, 0.6),
  sebs = c(0.25, 0.2, 0.22, 0.27),
  Ns = c(50, 80, 65, 90)
)

result <- waive(dat,
  method = 3, weight = 0, instrument = 1,
  studylevel = 0, SE = 0, AR = 0, first_stage = 0
)