r {healthequal} | R Documentation |
Ratio (R)
Description
The ratio (R) is a relative measure of inequality that shows the ratio of a health indicator between two population subgroups. For more information on this inequality measure see Schlotheuber, A., & Hosseinpoor, A. R. (2022) below.
Usage
r(
est,
se = NULL,
favourable_indicator,
ordered_dimension = NULL,
subgroup_order = NULL,
reference_subgroup = NULL,
conf.level = 0.95,
...
)
Arguments
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 MDBU cannot be calculated. |
favourable_indicator |
Records whether the indicator is favourable (1) or non-favourable (0). Favourable indicators measure desirable health events where the ultimate goal is to achieve a maximum level (such as skilled birth attendance). Non-favourable indicators measure undesirable health events where the ultimate goal is to achieve a minimum level (such as under-five mortality rate). |
ordered_dimension |
Records whether the dimension is ordered (1) or not (0). |
subgroup_order |
The order of subgroups in an increasing sequence. |
reference_subgroup |
Identifies a reference subgroup with the value of 1. |
conf.level |
confidence level of the interval. |
... |
Further arguments passed to or from other methods. |
Details
R is calculated as: R = y_1/y_2
where y_1
and y_2
indicate the
estimates for subgroups 1 and 2. The selection of the two subgroups depends
on the characteristics of the inequality dimension and the purpose of the
analysis. In addition, the direction of the calculation may depend on the
indicator type (favourable or adverse). Below are some examples of how
y_1 and y_2 may be identified.
Interpretation: The index R only assumes positive values. The further the value of R from one, the higher the level of inequality. R is one if there is no inequality.
Type of summary measure: Simple; relative; unweighted.
Applicability: Any
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 D 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,
r(est = estimate,
se = se,
favourable_indicator,
ordered_dimension = ordered_dimension,
reference_subgroup = reference_subgroup
)
)