mi.meld {Amelia} | R Documentation |
Combine sets of estimates (and their standard errors) generated from different multiply imputed datasets into one set of results.
mi.meld(q, se, byrow = TRUE)
q |
A matrix or data frame of (k) quantities of interest (eg.
coefficients, parameters, means) from (m) multiply imputed datasets.
Default is to assume the matrix is m-by-k (see |
se |
A matrix or data frame of standard errors that correspond to each of the
elements of the quantities of interest in |
byrow |
logical. If |
Uses Rubin's rules for combining a set of results from multiply imputed datasets to reflect the average result, with standard errors that both average uncertainty across models and account for disagreement in the estimated values across the models.
q.mi |
Average value of each quantity of interest across the m models |
se.mi |
Standard errors of each quantity of interest |
Rubin, D. (1987). Multiple Imputation for Nonresponse in Surveys. New York: Wiley.
Honaker, J., King, G., Honaker, J. Joseph, A. Scheve K. (2001). Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation American Political Science Review, 95(1), 49–69. (p53)