Pool together the results from M
complete-data analyses according to Rubin's rules. See details.
Value
A list containing:
est_point
: the pooled point estimate according to Little-Rubin (2002).var_t
: total variance according to Little-Rubin (2002).df
: degrees of freedom according to Barnard-Rubin (1999).
Details
rubin_rules
applies Rubin's rules (Rubin, 1987) for pooling together
the results from a multiple imputation procedure. The pooled point estimate est_point
is
is the average across the point estimates from the complete-data analyses (given by the input argument ests
).
The total variance var_t
is the sum of two terms representing the within-variance
and the between-variance (see Little-Rubin (2002)). The function
also returns df
, the estimated pooled degrees of freedom according to Barnard-Rubin (1999)
that can be used for inference based on the t-distribution.
References
Barnard, J. and Rubin, D.B. (1999). Small sample degrees of freedom with multiple imputation. Biometrika, 86, 948-955
Roderick J. A. Little and Donald B. Rubin. Statistical Analysis with Missing Data, Second Edition. John Wiley & Sons, Hoboken, New Jersey, 2002. [Section 5.4]
See also
rubin_df()
for the degrees of freedom estimation.