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20c_hhClassif_an_mv_an_wInteractions_67alone_HR_covidHosp.do
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20c_hhClassif_an_mv_an_wInteractions_67alone_HR_covidHosp.do
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*************************************************************************
*Do file: 08_hhClassif_an_mv_analysis_perEth5Group_HR_table.do
*
*Purpose: Create content that is ready to paste into a pre-formatted Word
* shell table containing minimally and fully-adjusted HRs for risk factors
* of interest, across 2 outcomes
*
*Requires: final analysis dataset (analysis_dataset.dta)
*
*Coding: K Wing, base on file from HFORBES, based on file from Krishnan Bhaskaran
*
*Date drafted: 17th June 2021
*************************************************************************
local dataset `1'
/*for reference
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 i.imd##i.eth5 i.ageCatfor67Plus##i.eth5 i.obese4cat##i.eth5 i.rural_urbanFive i.smoke i.male i.coMorbCat, strata(utla_group) vce(cluster hh_id)
*/
*global demogadjlistWInts i.imd##i.eth5 i.smoke##i.eth5 i.obese4cat##i.eth5 i.rural_urbanFive##i.eth5 i.ageCatfor67Plus##i.eth5 i.male##i.eth5 i.coMorbCat##i.eth5
global demogadjlistWInts i.imd##i.eth5 i.ageCatfor67Plus##i.eth5 i.obese4cat##i.eth5 i.rural_urbanFive i.smoke i.male i.coMorbCat
prog drop _all
prog define outputHRsforvar
syntax, variable(string) catLabel(string) min(real) max(real) ethnicity(real) outcome(string)
*calculation of rates
*get total count of people by for each ethnicity
count if eth5==`ethnicity'
local total = r(N)
forvalues i=`min'/`max' {
display
*get overall number for each category
cou if `variable' == `i' & eth5==`ethnicity'
*get number of events
cou if `variable' == `i' & _d == 1 & eth5==`ethnicity'
local event = r(N)
*get person time and rate and counts
bysort `variable': egen total_follow_up = total(_t) if eth5==`ethnicity'
su total_follow_up if eth5==`ethnicity'
local n_people_All = r(N)
su total_follow_up if `variable' == `i' & eth5==`ethnicity'
local n_people = r(N)
local person_days = r(mean)
local person_years=`person_days'/365.25
local rate = 100000*(`event'/`person_years')
local percent=100*(`n_people'/`n_people_All')
*get HRs for each regression analysis
*crude
estimates restore crude
*cap lincom `i'.`variable', eform
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
local hr_crude = r(estimate)
local lb_crude = r(lb)
local ub_crude = r(ub)
*age adjusted
estimates restore ageAdj
*cap lincom `i'.`variable', eform
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
local hr_ageAdj = r(estimate)
local lb_ageAdj = r(lb)
local ub_ageAdj = r(ub)
*mv adjusted
estimates restore mvAdj
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
local hr_mvAdj = r(estimate)
local lb_mvAdj = r(lb)
local ub_mvAdj = r(ub)
*mv adjusted with hh size
capture noisily estimates restore mvAdjWHHSize
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
capture noisily local hr_mvAdjWHHSize = r(estimate)
capture noisily local lb_mvAdjWHHSize = r(lb)
capture noisily local ub_mvAdjWHHSize = r(ub)
*mv adjusted with hh size CONTINOUS
/*
capture noisily estimates restore mvAdjWHHSizeCONT
cap noisily lincom `i'.`variable', eform
capture noisily local hr_mvAdjWHHSizeCONT = r(estimate)
capture noisily local lb_mvAdjWHHSizeCONT = r(lb)
capture noisily local ub_mvAdjWHHSizeCONT = r(ub)
*/
*get variable name
local lab: variable label `variable'
*file write tablecontents _tab (`i') _n
*get category name
local category: label `catLabel' `i'
display "Category label: `category'"
*write each row hg
if `i'==1 {
*write the total
file write tablecontents "(Ethnicity="(`ethnicity') ")" _n
file write tablecontents "(N="(`total') ")" _n
file write tablecontents _tab ("`category'") _tab (`n_people') (" (") %3.1f (`percent') (")") _tab (`event') _tab %3.0f (`person_years') _tab %3.0f (`rate') _tab "1" _tab "1" _tab "1" _n
}
else {
file write tablecontents _tab ("`category'") _tab (`n_people') (" (") %3.1f (`percent') (")") _tab (`event') _tab %3.0f (`person_years') _tab %3.0f (`rate') _tab %4.2f (`hr_crude') " (" %4.2f (`lb_crude') "-" %4.2f (`ub_crude') ")" _tab %4.2f (`hr_ageAdj') " (" %4.2f (`lb_ageAdj') "-" %4.2f (`ub_ageAdj') ")" _tab %4.2f (`hr_mvAdj') " (" %4.2f (`lb_mvAdj') "-" %4.2f (`ub_mvAdj') ")" _n
}
drop total_follow_up
}
*variable category
end
********Code that calls program and outputs tables*******
/*I think what I want here FOR EACH WAVE is
- A single page PER OUTCOME containing
- Results FOR EACH ETHNICITY for that outcome
*/
*Testing outcomes
*use ./output/hhClassif_analysis_dataset_STSET_covidDeath_ageband_3`dataset'.dta, clear
*foreach outcome in covidDeath covidHosp covidHospOrDeath nonCovidDeath {
foreach outcome in covidHosp {
* Open a log file
capture log close
log using "./logs/20c_hhClassif_an_mv_an_wInteractions_67alone_HR_`outcome'_`dataset'", text replace
*open dataset
use ./output/hhClassif_analysis_dataset_STSET_`outcome'_ageband_3`dataset'.dta, clear
*open table
file open tablecontents using ./output/20c_hhClassif_an_mv_an_wInteractions_67alone_HR_`outcome'_`dataset'.txt, t w replace
*write table title and column headers
file write tablecontents "Wave: `dataset', Outcome: `outcome'" _n
file write tablecontents _tab _tab ("N (%)") _tab ("Events") _tab ("Person years follow up") _tab ("Rate (per 100 000 person years)") _tab ("Crude") _tab ("Age adjusted") _tab ("MV adjusted") _n
**REGRESSIONS**
*only need to do the regressions once, so putting that code here and editing the outputHRsforvar program accordingly
strate hhRiskCatExp_5cats
**cox regressiona**
*need to account for different models for wave 1 (only interaction is with hhrisk) versus wave 2 (multiple interactions)
if "`dataset'"=="MAIN" {
*crude (only utla matched)
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store crude
*age-adjusted
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 i.ageCatfor67Plus##i.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store ageAdj
*MV adjusted (without household size)
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 i.ageCatfor67Plus##i.eth5 i.imd i.obese4cat i.rural_urbanFive i.smoke i.male i.coMorbCat, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store mvAdj
}
else if "`dataset'"=="W2" {
*crude (only utla matched)
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store crude
*age-adjusted
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 i.ageCatfor67Plus##i.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store ageAdj
*MV adjusted (without household size)
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 $demogadjlistWInts, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store mvAdj
*MV adjusted (with household size categorical)
*capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 $demogadjlistWInts i.hh_total_cat, strata(utla_group) vce(cluster hh_id)
*capture noisily estimates store mvAdjWHHSize
}
*MV adjusted (with household size continuous)
/*
capture noisily stcox i.`variable' $demogadjlist $comorbidadjlist i.imd i.hh_size, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store mvAdjWHHSizeCONT
*/
*helper variables
sum eth5
local maxEth5=r(max)
forvalues e=1/`maxEth5' {
display "*************Ethnicity: `e'************ "
display "`e'"
*next line: commented out while testing testparm etc
cap noisily outputHRsforvar, variable(hhRiskCatExp_5cats) catLabel(hhRiskCatExp_5cats) min(1) max(5) ethnicity(`e') outcome(`outcome')
file write tablecontents _n
}
cap file close tablecontents
cap log close
*output excel
*insheet using ./output/hhClassif_tablecontents_HRtable_`outcome'_`dataset'.txt, clear
*export excel using ./output/hhClassif_tablecontents_HRtable_`outcome'_`dataset'.xlsx, replace
}
/*
local dataset `1'
/*for reference
capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 i.imd##i.eth5 i.ageCatfor67Plus##i.eth5 i.obese4cat##i.eth5 i.rural_urbanFive i.smoke i.male i.coMorbCat, strata(utla_group) vce(cluster hh_id)
*/
*global demogadjlistWInts i.imd##i.eth5 i.smoke##i.eth5 i.obese4cat##i.eth5 i.rural_urbanFive##i.eth5 i.ageCatfor67Plus##i.eth5 i.male##i.eth5 i.coMorbCat##i.eth5
global demogadjlistWInts i.imd##i.eth5 i.ageCatfor67Plus##i.eth5 i.obese4cat##i.eth5 i.rural_urbanFive i.smoke i.male i.coMorbCat
prog drop _all
prog define outputHRsforvar
syntax, variable(string) catLabel(string) min(real) max(real) ethnicity(real) outcome(string)
display "CHECK 1"
*calculation of rates
strate `variable'
*get total count of people by for each ethnicity
count if eth5==`ethnicity'
local total = r(N)
display "CHECK 2"
forvalues i=`min'/`max' {
*display
*get overall number for each category
cou if `variable' == `i' & eth5==`ethnicity'
display "CHECK 2.1"
*get number of events
cou if `variable' == `i' & _d == 1 & eth5==`ethnicity'
local event = r(N)
display "CHECK 2.2"
*get person time and rate and counts
bysort `variable': egen total_follow_up = total(_t) if eth5==`ethnicity'
su total_follow_up if eth5==`ethnicity'
local n_people_All = r(N)
su total_follow_up if `variable' == `i' & eth5==`ethnicity'
local n_people = r(N)
local person_days = r(mean)
local person_years=`person_days'/365.25
local rate = 100000*(`event'/`person_years')
local percent=100*(`n_people'/`n_people_All')
display "CHECK 3"
*get HRs for each regression analysis
*crude
estimates restore crude_`ethnicity'
*cap lincom `i'.`variable', eform
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
*amazing new Krishnan way that has same ethnicity as baseline (see email Fri 4 March - couldnt' get this to work so doing it the other way suggested in same email)
*capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5#`i'.`variable', eform
local hr_crude = r(estimate)
local lb_crude = r(lb)
local ub_crude = r(ub)
display "CHECK 4"
*age adjusted
estimates restore ageAdj_`ethnicity'
*cap lincom `i'.`variable', eform
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
local hr_ageAdj = r(estimate)
local lb_ageAdj = r(lb)
local ub_ageAdj = r(ub)
display "CHECK 5"
*mv adjusted
estimates restore mvAdj_`ethnicity'
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
local hr_mvAdj = r(estimate)
local lb_mvAdj = r(lb)
local ub_mvAdj = r(ub)
display "CHECK 6"
*mv adjusted with hh size
/*
capture noisily estimates restore mvAdjWHHSize
capture noisily lincom `i'.`variable' + `i'.`variable'#`ethnicity'.eth5, eform
capture noisily local hr_mvAdjWHHSize = r(estimate)
capture noisily local lb_mvAdjWHHSize = r(lb)
capture noisily local ub_mvAdjWHHSize = r(ub)
*/
*mv adjusted with hh size CONTINOUS
/*
capture noisily estimates restore mvAdjWHHSizeCONT
cap noisily lincom `i'.`variable', eform
capture noisily local hr_mvAdjWHHSizeCONT = r(estimate)
capture noisily local lb_mvAdjWHHSizeCONT = r(lb)
capture noisily local ub_mvAdjWHHSizeCONT = r(ub)
*/
*get variable name
local lab: variable label `variable'
*file write tablecontents _tab (`i') _n
*get category name
local category: label `catLabel' `i'
display "Category label: `category'"
*write each row hg
if `i'==1 {
*write the total
file write tablecontents "(Ethnicity="(`ethnicity') ")" _n
file write tablecontents "(N="(`total') ")" _n
file write tablecontents _tab ("`category'") _tab (`n_people') (" (") %3.1f (`percent') (")") _tab (`event') _tab %3.0f (`person_years') _tab %3.0f (`rate') _tab "1" _tab "1" _tab "1" _n
}
else {
file write tablecontents _tab ("`category'") _tab (`n_people') (" (") %3.1f (`percent') (")") _tab (`event') _tab %3.0f (`person_years') _tab %3.0f (`rate') _tab %4.2f (`hr_crude') " (" %4.2f (`lb_crude') "-" %4.2f (`ub_crude') ")" _tab %4.2f (`hr_ageAdj') " (" %4.2f (`lb_ageAdj') "-" %4.2f (`ub_ageAdj') ")" _tab %4.2f (`hr_mvAdj') " (" %4.2f (`lb_mvAdj') "-" %4.2f (`ub_mvAdj') ")" _n
}
drop total_follow_up
}
*variable category
end
********Code that calls program and outputs tables*******
/*I think what I want here FOR EACH WAVE is
- A single page PER OUTCOME containing
- Results FOR EACH ETHNICITY for that outcome
*/
*Testing outcomes
*use ./output/hhClassif_analysis_dataset_STSET_covidDeath_ageband_3`dataset'.dta, clear
*foreach outcome in covidDeath covidHosp covidHospOrDeath nonCovidDeath {
foreach outcome in covidHosp {
* Open a log file
capture log close
log using "./logs/20c_hhClassif_an_mv_an_wInteractions_67alone_HR_`outcome'_`dataset'", text replace
*open dataset
use ./output/hhClassif_analysis_dataset_STSET_`outcome'_ageband_3`dataset'.dta, clear
*open table
file open tablecontents using ./output/20c_hhClassif_an_mv_an_wInteractions_67alone_HR_`outcome'_`dataset'.txt, t w replace
*write table title and column headers
file write tablecontents "Wave: `dataset', Outcome: `outcome'" _n
file write tablecontents _tab _tab ("N (%)") _tab ("Events") _tab ("Person years follow up") _tab ("Rate (per 100 000 person years)") _tab ("Crude") _tab ("Age adjusted") _tab ("MV adjusted") _n
*helper variables
sum eth5
local maxEth5=r(max)
forvalues e=1/`maxEth5' {
display "*************Ethnicity: `e'************ "
display "`e'"
*run the regressions once per ethnicity, so that the baseline can be change each time (see Krishnan email Fri 4th March) - this is what the "ib.`e'" code is doing
if "`dataset'"=="MAIN" {
*crude (only utla matched)
capture noisily stcox i.hhRiskCatExp_5cats##ib`e'.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store crude_`e'
*age-adjusted
capture noisily stcox i.hhRiskCatExp_5cats##ib`e'.eth5 i.ageCatfor67Plus, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store ageAdj_`e'
*MV adjusted (without household size)
capture noisily stcox i.hhRiskCatExp_5cats##ib`e'.eth5 i.ageCatfor67Plus i.imd i.obese4cat i.rural_urbanFive i.smoke i.male i.coMorbCat, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store mvAdj_`e'
}
else if "`dataset'"=="W2" {
*crude (only utla matched)
capture noisily stcox i.hhRiskCatExp_5cats##ib`e'.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store crude_`e'
*age-adjusted
capture noisily stcox i.hhRiskCatExp_5cats##ib`e'.eth5 i.ageCatfor67Plus##i.eth5, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store ageAdj_`e'
*MV adjusted (without household size)
capture noisily stcox i.hhRiskCatExp_5cats##ib`e'.eth5 $demogadjlistWInts, strata(utla_group) vce(cluster hh_id)
capture noisily estimates store mvAdj_`e'
*MV adjusted (with household size categorical)
*capture noisily stcox i.hhRiskCatExp_5cats##i.eth5 $demogadjlistWInts i.hh_total_cat, strata(utla_group) vce(cluster hh_id)
*capture noisily estimates store mvAdjWHHSize
}
*next line: commented out while testing testparm etc
outputHRsforvar, variable(hhRiskCatExp_5cats) catLabel(hhRiskCatExp_5cats) min(1) max(5) ethnicity(`e') outcome(`outcome')
file write tablecontents _n
}
cap file close tablecontents
cap log close
*output excel
*insheet using ./output/hhClassif_tablecontents_HRtable_`outcome'_`dataset'.txt, clear
*export excel using ./output/hhClassif_tablecontents_HRtable_`outcome'_`dataset'.xlsx, replace
}