mi.combine {Amelia} | R Documentation |
Combine results from analyses on imputed data sets
Description
Combine results from statistical models run on multiply imputed data sets using the so-called Rubin rules.
Usage
mi.combine(x, conf.int = FALSE, conf.level = 0.95)
Arguments
x |
List of output from statistical models estimated on
different imputed data sets, as outputted by |
conf.int |
Logical indicating if confidence intervals should
be computed for each quantity of interest (default is |
conf.level |
The confidence level to use for the confidence
interval if |
Value
Returns a tibble
that contains:
- term
Name of the coefficient or parameter.
- estimate
Estimate of the parameter, averagine across imputations.
- std.error
Standard error of the estimate, accounting for imputation uncertainty.
- statistic
Value of the t-statistic for the estimated parameter.
- p.value
p-value associated with the test of a null hypothesis that the true coefficient is zero. Uses the t-distribution with an imputation-adjusted degrees of freedom.
- df
Imputation-adjusted degrees of freedom for each parameter.
- r
Relative increase in variance due to nonresponse.
- miss.info
Estimated fraction of missing information.
- conf.low
Lower bound of the estimated confidence interval. Only present if
conf.int = TRUE
.- conf.high
Upper bound of the estimated confidence interval. Only present if
conf.int = TRUE
.
Author(s)
Matt Blackwell
Examples
data(africa)
a.out <- amelia(x = africa, cs = "country", ts = "year", logs =
"gdp_pc")
imp.mods <- with(a.out, lm(gdp_pc ~ infl + trade))
mi.combine(imp.mods, conf.int = TRUE)