bgv {healthequal}

Between-group variance (BGV)

Description

Between-Group Variance (BGV) is an absolute measure of inequality that considers all population subgroups. Subgroups are weighted according to their population share.

Usage

bgv(pop, est, se = NULL, conf.level = 0.95, ...)

Arguments

pop

The number of people within each subgroup. Population size must be available for all subgroups.

est

The subgroup estimate. Estimates must be available for all subgroups.

se

The standard error of the subgroup estimate. If this is missing, 95% confidence intervals of BGV cannot be calculated.

conf.level

confidence level of the interval.

...

Further arguments passed to or from other methods.

Details

BGV is calculated as the weighted average of squared differences between the subgroup estimates and the setting average. Squared differences are weighted by each subgroup’s population share. For more information on this inequality measure see Schlotheuber, A., & Hosseinpoor, A. R. (2022) below.

Interpretation: BGV has only positive values, with larger values indicating higher levels of inequality. BGV is zero if there is no inequality. BGV is more sensitive to outlier estimates as it gives more weight to the estimates that are further from the setting average. It is reported as the squared unit of the health indicator.

Type of summary measure: Complex; absolute; weighted

Applicability: Non-ordered; more than two subgroups

Warning: The confidence intervals are approximate and might be biased. See Ahn J. et al. (1978) below for further information on the standard error formula.

Value

The estimated BGV value, corresponding estimated standard error, and confidence interval as a data.frame.

References

Schlotheuber, A., & Hosseinpoor, A. R. (2022). Summary measures of health inequality: A review of existing measures and their application. International Journal of Environmental Research and Public Health, 19 (6), 3697.

Ahn J, Harper S, Yu M, Feuer EJ, Liu B, Luta G. Variance Estimation and Confidence Intervals for 11 Commonly Used Health Disparity Measures. JCO Clin Cancer Inform. 2018 Dec;2:1–19.

Examples

# example code
data(NonorderedSample)
head(NonorderedSample)
with(NonorderedSample,
     bgv(pop = population,
          est = estimate,
          se = se
         )
     )