DAVGMMI {DLMRMV} | R Documentation |
Impute Missing Values in Response Variable Y Using Distributed AVGMMI Method (With Grouping)
Description
This function implements the Distributed Averaged Generalized Method of Moments Imputation (DAVGMMI) to fill in missing values in the response variable Y based on observed covariates X. Assumes a single group structure and does not require group size input ('n').
Usage
DAVGMMI(data, R, M)
Arguments
data |
A data frame or matrix where the first column is the response variable Y (may contain NA), and remaining columns are covariates X. |
R |
Number of simulations for stable Beta estimation. |
M |
Number of multiple imputations. |
Value
A list containing:
Yhat |
The vector of Y with missing values imputed. |
betahat |
Final averaged regression coefficient estimates used for imputation. |
Examples
set.seed(123)
data <- data.frame(
y = c(rnorm(50), rep(NA, 10)),
x1 = rnorm(60),
x2 = rnorm(60)
)
result <- DAVGMMI(data, R = 50, M = 10)
head(result$Yhat)
[Package DLMRMV version 0.2.0 Index]