pool.scalar {mice}R Documentation

Multiple Imputation Pooling: Univariate version

Description

Pools univariate estimates of m repeated complete data analysis

Usage

pool.scalar(Q,U)

Arguments

Q

A vector of univariate estimates of m repeated complete data analyses.

U

A vector containing the corresponding m variances of the univariate estimates.

Details

The function averages the univariate estimates of the complete data model, computes the total variance over the repeated analyses, and computes the relative increase in variance due to nonresponse and the fraction of missing information.

Value

Returns a list with components

m

The number of imputations

qhat

The m univariate estimates of repeated complete data analyses

u

The corresponding m variances of the univariate estimates

qbar

The pooled univariate estimate, formula (3.1.2) Rubin (1987).

ubar

The mean of the variances, formula (3.1.3) Rubin (1987).

b

The within imputation variance, formula (3.1.4) Rubin (1987).

t

Total variance of the pooled estimated, formula (3.1.5) Rubin (1987).

r

Relative increase in variance due to nonresponse, formula (3.1.7) Rubin (1987).

df

Degrees of freedom for t reference distribution, formula (3.1.6) Rubin (1987).

f

Fraction missing information due to nonresponse, formula (3.1.10) Rubin (1987).

Author(s)

Karin Groothuis-Oudshoorn and Stef van Buuren, 2009

References

Rubin, D.B. (1987). Multiple Imputation for Nonresponse in Surveys. New York: John Wiley and Sons.

See Also

pool

Examples


imp <- mice(nhanes)
m <- imp$m
Q <- rep(NA,m)
U <- rep(NA,m)
for (i in 1:m) {
    Q[i] <- mean(complete(imp,i)$bmi)
    U[i] <- var(complete(imp,i)$bmi)
}
pool.scalar(Q,U)

#pool.scalar(Q,U)
#$m
#[1] 5
#
#$qhat
#[1] 26.764 26.748 27.024 27.340 26.436
#
#$u
#[1] 17.85490 19.11677 20.61440 21.05750 15.16990
#
#$qbar
#[1] 26.8624
#
#$ubar
#[1] 18.76269
#
#$b
#[1] 0.1147008
#
#t
#[1] 18.90033
#
#$r
#[1] 0.007335885
#
#$df
#[1] 75422.96
#
#$f
#[1] 0.007308785
#

[Package mice version 2.11 Index]