mi_wald_phat: Calculates the MI-Wald interval if given a vector of observed...
In MIWilson: Implementing the MI-Wilson Confidence Interval
Description
Usage
Arguments
Value
Related Functions
Examples
Description
Calculates the MI-Wald interval if given a vector of observed
binomial proportions (one for each imputed data frame)
Usage
1
mi_wald_phat(phats, n, ci_level = 0.95, summaries = TRUE)
Arguments
phats
vector of binomial proportions (one for each imputation)
n
the common number of observations over the imputed dataframes
ci_level
desired confidence interval level (default 95%)
summaries
boolean: should summary helper values be printed (default TRUE)
Value
Two-length vector of Wilson lower CI and upper CI
Related Functions
-
mi_wald
-
mi_wilson_phat
Examples
1
2
phats = c(0.2, 0.23, 0.25)
mi_wald_phat(phats, 100, 0.99, TRUE)
MIWilson documentation built on Aug. 24, 2021, 1:06 a.m.
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Description Usage Arguments Value Related Functions Examples
Description
Calculates the MI-Wald interval if given a vector of observed binomial proportions (one for each imputed data frame)
Usage
1 | mi_wald_phat(phats, n, ci_level = 0.95, summaries = TRUE)
|
Arguments
phats |
vector of binomial proportions (one for each imputation) |
n |
the common number of observations over the imputed dataframes |
ci_level |
desired confidence interval level (default 95%) |
summaries |
boolean: should summary helper values be printed (default TRUE) |
Value
Two-length vector of Wilson lower CI and upper CI
Related Functions
-
mi_wald -
mi_wilson_phat
Examples
1 2 | phats = c(0.2, 0.23, 0.25)
mi_wald_phat(phats, 100, 0.99, TRUE)
|
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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