Wagstaff concentration Index for binary outcome

[Zahrah Rafique]

Hi,

I have read in existing literature that if we are dealing with a binary outcome (i.e th individual went for prenatal care/did not go for prenatal care), the Concentration Index is not valid as it is not normalised Could someone please explain how to normalise wagstaff concentration index and what this generally means.

Zahrah

[Nick Cox]

I hope someone knows what this means but if not then you need to spell out more details.

[Zahrah Rafique]

Dear Nick,
I am currently working on my Mphil thesis. It deals with the socioeconomic determinants that influence maternal health care behaviour. Therefore, the outcome variable is whether or not the respondent went for antenatal visits. This makes it a binary outcome. However, I read in various research papers that if the outcome variable is binary in nature, we have to normalize the concentration index as suggested by Wagstaff. This can easily be done through the coindex command. However, I am getting stuck at the decomposition analysis. I have no idea what commands to use get the elasticity, concentration index and marginal effect for each individual component. Please help me with the decomposition of the binary outcome.

Zahrah

[Zahrah Rafique]

I came across this

global X "wq3 wq2 Educ_women educ_husb age15to19 age20to34 age35to49 sindh punjab kpk islamabad first_child second_third_child child_4_5   decisionmaking1 media_exposure Resp_curr_working resp_cuurr_agegrp_35_49 resp_cuurr_agegrp_20_34 urban"
regr postnatal_check $X [aw=weight]
sum postnatal_check [aw=weight]
sca m_postnatal_check=r(mean)
sca m_postnatal_check=r(mean)
foreach  x of global X {
qui {
sca b_`x'=_b[`x']
corr rank `x' [aw=weight], c
sca cov_`x'=r(cov_12)
sum `x' [aw=weight]
sca elas_`x'=(b_`x'*r(mean))/m_postnatal_check
sca CI_`x'=2*cov_`x'/r(mean)
sca con_`x'=elas_`x'*CI_`x'
sca prcnt_`x'=(con_`x'/CI_`x')*100
}
di "`x' elasticity:", elas_`x'
di "`x' concentration index:", CI_`x'
di "`x' contribution:", con_`x'
di "`x' percentage contribution:", prcnt_`x'
matrix Aaa = nullmat(Aaa) \ (elas_`x', CI_`x', con_`x', prcnt_`x')
}
matrix rownames Aaa= $X
matrix colnames Aaa = "Elasticity""CI""Absolute""%"
matrix list Aaa, format(%8.4f)

But the above command applies to a standardised decomposition of the Wagstaff Concentration Index. I need commands for decomposing the normalized wagstaff/errygers index.

[Karan Babbar]

I came across this

global X "wq3 wq2 Educ_women educ_husb age15to19 age20to34 age35to49 sindh punjab kpk islamabad first_child second_third_child child_4_5 decisionmaking1 media_exposure Resp_curr_working resp_cuurr_agegrp_35_49 resp_cuurr_agegrp_20_34 urban"
regr postnatal_check $X [aw=weight]
sum postnatal_check [aw=weight]
sca m_postnatal_check=r(mean)
sca m_postnatal_check=r(mean)
foreach x of global X {
qui {
sca b_`x'=_b[`x']
corr rank `x' [aw=weight], c
sca cov_`x'=r(cov_12)
sum `x' [aw=weight]
sca elas_`x'=(b_`x'*r(mean))/m_postnatal_check
sca CI_`x'=2*cov_`x'/r(mean)
sca con_`x'=elas_`x'*CI_`x'
sca prcnt_`x'=(con_`x'/CI_`x')*100
}
di "`x' elasticity:", elas_`x'
di "`x' concentration index:", CI_`x'
di "`x' contribution:", con_`x'
di "`x' percentage contribution:", prcnt_`x'
matrix Aaa = nullmat(Aaa) \ (elas_`x', CI_`x', con_`x', prcnt_`x')
}
matrix rownames Aaa= $X
matrix colnames Aaa = "Elasticity""CI""Absolute""%"
matrix list Aaa, format(%8.4f)

But the above command applies to a standardised decomposition of the Wagstaff Concentration Index. I need commands for decomposing the normalized wagstaff/errygers index.

I am facing a similar issue. did you find a solution to this problem?

[Zahrah Rafique]

Hi, I have fixed the issue. If anyone has a problem they can reach out to me at [email protected]

[Romina Gisel Perez]

Hi, I have fixed the issue. If anyone has a problem they can reach out to me at [email protected]

Hi Zahrah. How are you? I wrote to you a few days ago at zahrah [email protected], but I'm not sure if that account is still in use. I hope it doesn't bother you.I will be on the lookout. Thanks.