oneCatCI: 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 responses of multiple imputed datasets for a specified categorical variable, and also gives 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 variance formulas that are specific to whether the multiple imputed datasets are synthetic or imputed. See reference for more information.

Usage

oneCatCI(obs_data, imp_data_list, type, var, sig = 6, 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 of datasets that are either synthetic or contain imputed values.
type	Specifies which type of datasets are in imp_data_list. Options are "synthetic" and "imputed".
var	The categorical variable being checked. Should be of type "factor".
sig	The number of significant digits in the output dataframe. Defaults to 6.
alpha	Test size, defaults to 0.05.

Details

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

Value

This function returns a dataframe with the variable's responses, observed values, lower and upper limits of the confidence interval, standard error, and "YES"/"NO" indicating whether or not the observed value is within the confidence interval.

References

\insertRef

adaptSynthTools

Examples

#PPA is observed data set, PPAm5 is a list of 5 partially synthetic data sets derived from PPA.
#sex is a categorical variable within these data sets. 3 significant digits are desired.

oneCatCI(obs_data=PPA, imp_data_list=PPAm5, type="synthetic", var="sex", sig=3)

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