Combine Parameter Estimates Vector and Sampling Variance-Covariance Matrix Estimated from Multiple Imputations
Source:R/manMCMedMiss-mi-combine.R
MICombine.RdCombine Parameter Estimates Vector and Sampling Variance-Covariance Matrix Estimated from Multiple Imputations
Arguments
- param_vec
List of vectors of paramater estimates.
- var_mat
List of matrices of sampling variances and covariances.
Value
Returns a list with the following elements:
- m
Number of imputations \(M\).
- k
Number of parameters \(k\).
- estimates
Vector of pooled coefficients/parameter estimates \(\bar{\boldsymbol{\theta}}\).
- within
Covariance within imputations \(\mathbf{V}_{\mathrm{within}}\).
- between
Covariance between imputations \(\mathbf{V}_{\mathrm{between}}\).
- total
Total covariance matrix \(\mathbf{V}_{\mathrm{total}}\).
- total_adjusted
Adjusted total covariance matrix \(\tilde{\mathbf{V}}_{\mathrm{total}}\).
- ariv
Average relative increase in variance \(\mathrm{ARIV}\).
References
Li, K. H., Raghunathan, T. E., & Rubin, D. B. (1991). Large-sample significance levels from multiply imputed data using moment-based statistics and an F reference distribution. Journal of the American Statistical Association, 86 (416), 1065–1073. doi:10.1080/01621459.1991.10475152
Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. John Wiley & Sons, Inc. doi:10.1002/9780470316696