help for rdecompose

Title

rdecompose implements the Gupta's rate decomposition method for aggregated data.

Description

The command reports the contribution of each specified variable to the aggregate value. The command keyword is rdecompose, and it should be immediately followed by the variable names of the factors contributing to the aggregate rates. The group indicator must also be included in the option group.

Syntax

rdecompose variables [if exp],
group(variable) [sum(variable)
detail reverse function(String) transform(variable) multi baseline(#) ]

Options

variables specifies the variables that contribute to the aggregated value.

group(variable) specify the two populations (groups) that will be compared. The variable can be both in numeric format and string format.

sum(variable) indicates that the population rate is an aggregated value summed over each distinct value of this variable or variables. (such as age or location)

function(string) allows users to specify the function form as they wish. For instance, “ln(factor1+factor2)*exp(factor3)” can be used as a function. Most Stata supported functions can be used here. An error message will be display if the function form is invalid

detail option will give a more detailed output when aggregation is required.

reverse this option reserves the order of the population.

transform This option converts the absolute numbers into proportions within the population.

multi this option indicates that there are more than 2 populations in the option “group”. Specifying this option will result in multiple comparisons against the baseline group.

baseline(#) this option specify the baseline group value.

Return Values

Scalar e(N) contains the number of observations used in the estimation

Scalar e(rate1) contains the rate calculated for the first group

Scalar e(rate2) contains the rate calculated for the second group

Scalar e(diff) shows the total differences between two groups

Macro e(basegroup_value) shows the baseline group value

Matrix e(b) contains the total contributions for each factor

Examples

rdecompose Marriage Contraception Abortion Lactation Fecundity , group(year)

rdecompose Size Rate , group( Parity ) transform( Size )

rdecompose age_structure CDM NCD Injuries , group(group) sum(age_group_i) func(age_structure*( CDM + NCD + Injuries ))

rdecompose prevalencerate population ageing exppercase healthpriceinflation, group(year) sum(disease_group agegroup)

Reference

Gupta, P. D. (1993). Standardization and decomposition of rates: A user's manual. US Department of Commerce, Economics and Statistics Administration, Bureau of the Census.

Li, J., & Kinfu, Y. (2015). rdecompose: Outcome decomposition for aggregate data. Paper presented at the Oceania Stata User Group Meeting, Canberra.

Contact

Jinjing Li, University of Canberra, Australia

mailto:jinjing.li@canberra.edu.au