mi_wald: Calculates the specified Wald CI of a binomial proportion...
In MIWilson: Implementing the MI-Wilson Confidence Interval
Description
Usage
Arguments
Value
Examples
Description
Calculates the specified Wald CI of a binomial proportion
variable, given imputed data sets.
Usage
1
Arguments
mids_obj
mids object created by mice package
response
string name of response variable (must be 0-1 valued)
ci_level
desired confidence interval level (defaults to 95%)
summaries
boolean: should summary helper values be printed (default TRUE)
Value
two-length vector of Wald lower CI and upper CI
Examples
1
2
imp = mice::mice(mice::nhanes %>% dplyr::mutate(hyp = hyp-1))
mi_wald(imp, "hyp", 0.95)
MIWilson documentation built on Aug. 24, 2021, 1:06 a.m.
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Description Usage Arguments Value Examples
Description
Calculates the specified Wald CI of a binomial proportion variable, given imputed data sets.
Usage
1 |
Arguments
mids_obj |
mids object created by mice package |
response |
string name of response variable (must be 0-1 valued) |
ci_level |
desired confidence interval level (defaults to 95%) |
summaries |
boolean: should summary helper values be printed (default TRUE) |
Value
two-length vector of Wald lower CI and upper CI
Examples
1 2 | imp = mice::mice(mice::nhanes %>% dplyr::mutate(hyp = hyp-1))
mi_wald(imp, "hyp", 0.95)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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