twoCatCI: Confidence intervals and standard errors of multiple...

In RTIInternational/SynthTools: Tools and Tests for Experiments with Partially Synthetic Data Sets

Description

This function will calculate confidence intervals and standard errors from the proportional tabular responses of multiple imputed datasets for two categorical variables, and also give a YES/NO indicator for whether or not the observed value is within the confidence interval. The confidence intervals and standard errors are calculated from formulas that are adapted for partially synthetic data sets. See reference for more information.

Usage

twoCatCI(obs_data, imp_data_list, type, vars, sig = 4, alpha = 0.05)

Arguments

obs_data	The original dataset to which the next will be compared, of the type "data.frame".
imp_data_list	A list composed of m synthetic data sets.
type	Specifies which type of datasets are in imp_data_list. Options are "synthetic" and "imputed".
vars	A vector of the two categorical variable being checked. Should be of type "factor".
sig	The number of significant digits in the output dataframes. Defaults to 4.
alpha	Test size, defaults to 0.05.

Details

This function was developed with the intention of making the job of researching partially synthetic data utility a bit easier by providing another way of measuring utility.

Value

This function returns a list of five data frames:

Observed	A cross-tabular proportion of observed values
Lower	Lower limit of the confidence interval
Upper	Upper limit of the confidence interval
SEs	Standard Errors
CI_Indicator	"YES"/"NO" indicating whether or not the observed value is within the confidence interval

References

\insertRef

adaptSynthTools

Examples

#PPA is the observed data set.  PPAm5 is a list of 5 partially synthetic data sets derived from PPA.
#"sex" and "race" are categorical variables present in the synthesized data sets.
#3 significant digits are desired in the output dataframes.

twoCatCI(PPA, PPAm5, "synthetic", c("sex", "race"), sig=3)

RTIInternational/SynthTools documentation built on Oct. 30, 2019, 10:50 p.m.