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clear all
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set more off
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set matsize 5000
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version 13.1
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cap graph set window fontface Times-Roman
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global data_final= "$path/Data"
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global dofiles_fig = "$path/Do_Files/Figures"
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global dofiles_tab = "$path/Do_Files/Tables"
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global dofiles_admin = "$path/Do_Files/Stata admin files"
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global tables = "$path/Tables"
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global graphs = "$path/Figures"
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global prehead1 "\begin{tabular}{l*{"
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global prehead2 "}{c}} \hline\hline"
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global patientdata "LSS_analysis_datasets_20201108.dta"
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global censusdata "LSS_CSComCensus.dta"
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global doctorendline "LSS_DoctorEndlineInterview.dta"
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include "$dofiles_admin/LSS_config_stata.do"
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include "$dofiles_admin/LSS_TablePrograms.do"
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global date "DD1-DD35"
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global clinic "CL1-CL59"
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global patient "CC*"
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global cluvar "cscomnum"
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global clulevel "clinic"
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#delimit ;
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global footnote0 "\emph{Notes}: Robust standard errors clustered at the $clulevel level in parentheses.
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All regressions control for clinic visit date fixed effects. We use double selection
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lasso to choose additional controls. Eligible controls include clinic dummies, symptom dummies, duration of illness
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(topcoded at the 99th percentile) and its square, patient age and its square, a dummy for patients under 5, patient gender,
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a dummy to identify pregnant patients, a dummy to identify whether the patient (versus a caregiver) answered the survey, the gender of the survey
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respondent, an ethnicity (Bambara) dummy, a dummy for French speaking respondents, a dummy for literate
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respondents, a dummy for respondents with a primary education or less, a dummy to identify patients in the home-based
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follow up survey, and pairwise interactions between all previously-listed patient and respondent controls. Missing values are recoded to the sample
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mean and separately dummied out. These missing dummies are also used to construct pairwise interactions.";
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global footnoteb "\emph{Notes}: Robust standard errors clustered at the $clulevel level in parentheses.
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All regressions control for clinic visit date fixed effects. We use double selection
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lasso to choose additional controls. See notes to Table 3 for a list of potential controls.";
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global footnote0_nl "\emph{Notes}: Robust standard errors clustered at the $clulevel level in parentheses. All regressions control for clinic visit date fixed effects.";
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global footnote0_nl_new "\emph{Notes}: Robust standard errors clustered at the $clulevel level in parentheses.
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All regressions control for clinic visit date fixed effects. Controls include number of symptoms, symptom dummies,
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duration of illness (topcoded at the 99th percentile), patient age, a dummy for patients under 5, patient gender,
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dummy to identify pregnant patients, a dummy to identify whether the patient (versus a caregiver) answered the survey,
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the gender of the survey respondent, an ethnicity (Bambara) dummy, a dummy for French speaking respondents, a dummy for literate
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respondents, a dummy for respondents with a primary education or less. Missing values are recoded to the sample mean.";
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#delimit cr
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global footnote0_alt "\emph{Notes}: Robust standard errors clustered at the $clulevel level in parentheses. All regressions include clinic visit date fixed effects."
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global footnote1 "*, **, and *** denote statistical significance at the 10, 5, and 1 percent levels respectively."
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include "$dofiles_admin/LSS_make_bootstrap_repsets.do"
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/3_graph_outcomeXpredpos_control.do"
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/4_graph_tmtXpredpos.do"
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/5_graph_voucher_tmt.do"
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/B1_graph_misallocation.do"
|
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/B2_graph_dist_pred_pos.do"
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/B3_graph_outcomeXpredpos_control_home.do"
|
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use "$data_final/$patientdata", clear
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drop if dropme==1
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do "$dofiles_fig/B4_graph_vouchersXbins.do"
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use "$data_final/$patientdata", clear
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drop if dropme==1
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include "$dofiles_tab/1_table_control_group.do"
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use "$data_final/$patientdata", clear
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la var under5 "Under 5 Years Old"
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global varlist0 "nobs"
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global varlist1 "num_symptoms symptomsscreening_1 symptomsscreening_2 symptomsscreening_3 symptomsscreening_4 symptomsscreening_5 symptomsscreening_6 symptomsscreening_7 daysillness99 agepatient under5 genderpatient pregnancy RDTresult_POS pred_mal_pos"
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global varlist2 "respondent gender ethnic_bambara speak_french readwrite_fluent_french prischoolorless total_hh_members_H HH_frac_14 HH_frac_job income_percap_H rent_value_H HH_frac_nets"
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include "$dofiles_tab/2_table_balance.do"
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use "$data_final/$patientdata", clear
|
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|
drop if dropme==1
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|
g RXnone= 1 - RXtreat_sev_simple_mal
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|
g none= 1 - treat_sev_simple_mal
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|
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la var RXnone "Prescribed"
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la var none "Purchased"
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la var RXtreat_sev_simple_mal "Prescribed"
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la var treat_sev_simple_mal "Purchased"
|
|
|
la var used_vouchers_admin "Used Voucher"
|
|
|
la var RXtreat_severe_mal "Prescribed"
|
|
|
la var treat_severe_mal "Purchased"
|
|
|
|
|
|
docpat_theory_lso used_vouchers_admin RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, type(tex)
|
|
|
table("$tables/3_mal_tmt_overall_new_lso.tex") footnote($footnote0 GC, PD, and DD indicate tests of gatekeeping costs, patient-driven, and doctor-driven demand respectively. $footnote1) testof("GC PD PD DD DD") signifevidence("Yes Yes Yes No No")
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|
|
prehead1($prehead1) title("Impacts on Malaria Treatment Outcomes") lab(mal_tmt_overall_new)
|
|
|
prehead2($prehead2) widc(0.12\linewidth) texwid(.95) cluvar($cluvar) partial($date) lcont($date $clinic $patient)
|
|
|
extrahead(\\ & & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){3-4} \cmidrule(lr){5-6})
|
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|
|
use "$data_final/$patientdata", clear
|
|
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|
|
cap prog drop dome
|
|
|
prog define dome
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|
|
drop if dropme==1
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|
|
la var used_vouchers_admin "Used Voucher"
|
|
|
la var RXtreat_severe_mal "Prescribed"
|
|
|
la var treat_severe_mal "Purchased"
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|
|
la var RXtreat_sev_simple_mal "Prescribed"
|
|
|
la var treat_sev_simple_mal "Purchased"
|
|
|
end
|
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|
dome
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|
docpat_hettable_theory_lso used_vouchers_admin RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, type(tex)
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|
|
table("$tables/4_mal_tmt_het_new_lso.tex") footnote($footnoteb Standard errors are based on 1,000 bootstrap replications, with re-sampling at the clinic level. Predicted malaria risk is re-calculated on each bootstrap replication. GC, PD, and DD indicate tests of gatekeeping costs, patient-driven, and doctor-driven demand respectively. $footnote1)
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|
|
prehead1($prehead1) title("Impacts on Malaria Treatment Outcomes - Heterogeneity by Predicted Malaria Risk") lab(mal_tmt_het_new) partial($date)
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|
prehead2($prehead2) widc(0.12\linewidth) texwid(1) cluvar($cluvar) testofh("GC/DD -- -- DD DD") signifevidenceh("No -- -- No No") testofl("GC/PD PD PD -- --") signifevidencel("Yes Yes Yes -- --")
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|
|
extrahead(\\ & & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){3-4} \cmidrule(lr){5-6})
|
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|
path("$data_final/_bootstrap") setname("bs_cluCSCOM_") dodo(dome) numreps(1000) lcont($date $clinic $patient)
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|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
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|
|
la var RXexpected_mal_match_any "Overall Match"
|
|
|
la var expected_mal_match_any "Overall Match"
|
|
|
g RXexpected_mal_match_anyX= RXexpected_mal_match_any if RXmatch_treat_RDT!=.
|
|
|
g expected_mal_match_anyX= expected_mal_match_any if RXmatch_treat_RDT!=.
|
|
|
la var expected_mal_match_any_pos "Malaria Positive"
|
|
|
la var RXexpected_mal_match_any_pos "Malaria Positive"
|
|
|
la var expected_mal_match_any_neg "Malaria Negative"
|
|
|
la var RXexpected_mal_match_any_neg "Malaria Negative"
|
|
|
la var RXexpected_mal_match_anyX "Prescribed"
|
|
|
la var expected_mal_match_anyX "Purchased"
|
|
|
la var RXmatch_treat_RDT "Prescribed"
|
|
|
la var match_treat_RDT "Purchased"
|
|
|
|
|
|
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|
|
docpat_p1_lso RXexpected_mal_match_any_pos RXexpected_mal_match_any_neg RXexpected_mal_match_any expected_mal_match_any_pos expected_mal_match_any_neg expected_mal_match_any, type(tex)
|
|
|
table("$tables/5_expected_match_decomp_lso.tex") footnote($footnoteb The expected match for malaria positive is equal to predicted malaria risk times the relevant malaria treatment/purchase dummy. The expected match for malaria negative is equal to one minus predicted malaria risk times one minus the malaria prescription/purchase dummy. The overall expected match is the sum of these two variables. $footnote1)
|
|
|
prehead1($prehead1) title("Impacts on Match Between Treatment and Illness") lab(expected_match_decomp)
|
|
|
prehead2($prehead2) widc(0.1\linewidth) texwid(1.25) cluvar($cluvar) partial($date) lcont($date $clinic $patient)
|
|
|
extrahead(\\ & \multicolumn{3}{c}{Expected Match: Prescribed} & \multicolumn{3}{c}{Expected Match: Purchased} \\ \cmidrule(lr){2-4} \cmidrule(lr){5-7})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$censusdata", clear
|
|
|
|
|
|
do "$dofiles_tab/B1_table_clinic_census.do"
|
|
|
|
|
|
|
|
|
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|
|
use "$data_final/$doctorendline", clear
|
|
|
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|
|
do "$dofiles_tab/B2_table_means_doctor.do"
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
|
|
la var RXtreat_sev_simple_mal "Prescribed"
|
|
|
la var treat_sev_simple_mal "Purchased"
|
|
|
la var RXtreat_severe_mal "Prescribed"
|
|
|
la var treat_severe_mal "Purchased"
|
|
|
|
|
|
gen doctor_voucher_x_patient_info=doctor_voucher*patient_info
|
|
|
gen patient_voucher_x_patient_info=patient_voucher*patient_info
|
|
|
|
|
|
docpat_pat_lso RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, type(tex)
|
|
|
table("$tables/B3_mal_tmt_pat_info_lso.tex") footnote($footnoteb $footnote1)
|
|
|
prehead1($prehead1) title("Impacts of Patient Information on Malaria Treatment Outcomes") lab(mal_tmt_pat_info_lso)
|
|
|
prehead2($prehead2) widc(0.12\linewidth) texwid(0.8) cluvar($cluvar)
|
|
|
extrahead(\\ & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){2-3} \cmidrule(lr){4-5})
|
|
|
partial($date) lcont($date $clinic $patient)
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
|
|
la var RXtreat_sev_simple_mal "Prescribed"
|
|
|
la var treat_sev_simple_mal "Purchased"
|
|
|
la var RXtreat_severe_mal "Prescribed"
|
|
|
la var treat_severe_mal "Purchased"
|
|
|
|
|
|
docpat_doc_lso RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, type(tex)
|
|
|
table("$tables/B4_mal_tmt_doc_info_lso.tex") footnote($footnoteb $footnote1)
|
|
|
prehead1($prehead1) title("Impacts of Doctor Information on Malaria Treatment Outcomes") lab(mal_tmt_doc_info_lso)
|
|
|
prehead2($prehead2) widc(0.1\linewidth) texwid(.8) cluvar($cluvar)
|
|
|
extrahead(\\ & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){2-3} \cmidrule(lr){4-5})
|
|
|
partial($date) lcont($date $clinic $patient)
|
|
|
|
|
|
|
|
|
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|
|
use "$data_final/$patientdata", clear
|
|
|
la var has_valid_rdt_H "Has Valid RDT (Home Survey)"
|
|
|
|
|
|
|
|
|
global varlist0 "nobs in_home_survey has_valid_rdt_H"
|
|
|
|
|
|
global varlist1 "num_symptoms symptomsscreening_1 symptomsscreening_2 symptomsscreening_3 symptomsscreening_4 symptomsscreening_5 symptomsscreening_6 symptomsscreening_7 daysillness99 agepatient under5 genderpatient pregnancy RDTresult_POS pred_mal_pos"
|
|
|
|
|
|
global varlist2 "respondent gender ethnic_bambara speak_french readwrite_fluent_french prischoolorless total_hh_members_H HH_frac_14 HH_frac_job income_percap_H rent_value_H HH_frac_nets"
|
|
|
|
|
|
include "$dofiles_tab/B5_table_selection.do"
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
|
|
|
|
|
do "$dofiles_tab/B6_table_diff_test_consent.do"
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
|
|
|
|
|
do "$dofiles_tab/B7_table_mal_prob_probit.do"
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
|
|
|
|
|
la var RXtreat_sev_simple_mal "Prescribed"
|
|
|
la var treat_sev_simple_mal "Purchased"
|
|
|
la var used_vouchers_admin "Used Voucher"
|
|
|
la var RXtreat_severe_mal "Prescribed"
|
|
|
la var treat_severe_mal "Purchased"
|
|
|
|
|
|
docpat_p1_theory used_vouchers_admin RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, extra($date) type(tex)
|
|
|
table("$tables/B8_mal_tmt_overall_nc.tex") footnote($footnote0_nl GC, PD, and DD indicate tests of gatekeeping costs, patient-driven, and doctor-driven demand respectively. $footnote1) testof("GC PD PD DD DD") signifevidence("Yes Yes Yes No No")
|
|
|
prehead1($prehead1) title("Impacts on Malaria Treatment Outcomes, No Additional Controls") lab(mal_tmt_overall_new_nc)
|
|
|
prehead2($prehead2) widc(0.12\linewidth) texwid(.8) cluvar($cluvar)
|
|
|
extrahead(\\ & & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){3-4} \cmidrule(lr){5-6})
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
|
|
|
cap prog drop dome
|
|
|
prog define dome
|
|
|
drop if dropme==1
|
|
|
la var used_vouchers_admin "Used Voucher"
|
|
|
la var RXtreat_severe_mal "Prescribed"
|
|
|
la var treat_severe_mal "Purchased"
|
|
|
la var RXtreat_sev_simple_mal "Prescribed"
|
|
|
la var treat_sev_simple_mal "Purchased"
|
|
|
end
|
|
|
|
|
|
dome
|
|
|
|
|
|
docpat_hettable_theory used_vouchers_admin RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, extrac($date) type(tex)
|
|
|
table("$tables/B9_mal_tmt_het_nc.tex") footnote($footnote0_nl Standard errors based GC, PD, and DD indicate tests of gatekeeping costs, patient-driven, and doctor-driven demand respectively. $footnote1)
|
|
|
prehead1($prehead1) title("Impacts on Malaria Treatment Outcomes - Heterogeneity by Predicted Malaria Risk, No Additional Controls") lab(mal_tmt_het_new_nc)
|
|
|
prehead2($prehead2) widc(0.12\linewidth) texwid(.8) cluvar($cluvar) testofh("GC/DD -- -- DD DD") signifevidenceh("No -- -- No No") testofl("GC/PD PD PD -- --") signifevidencel("Yes Yes Yes -- --")
|
|
|
extrahead(\\ & & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){3-4} \cmidrule(lr){5-6})
|
|
|
path("$data_final/_bootstrap") setname("bs_cluCSCOM_") dodo(dome) numreps(1000)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
use "$data_final/$patientdata", clear
|
|
|
drop if dropme==1
|
|
|
|
|
|
sum pregnancy
|
|
|
replace pregnancy=r(mean) if pregnancy==.
|
|
|
sum ethnic_bambara
|
|
|
replace ethnic_bambara=r(mean) if ethnic_bambara==.
|
|
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global mycont0 "date_1-date_35"
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global covariates "num_symptoms symptomsscreening_1 symptomsscreening_2 symptomsscreening_3 symptomsscreening_4 symptomsscreening_5 symptomsscreening_6 daysillness99 agepatient under5 genderpatient pregnancy MSSpregnancy respondent gender ethnic_bambara MSSethnic_bambara speak_french readwrite_fluent_french prischoolorless"
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global mycont "$mycont0 $covariates"
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la var RXtreat_sev_simple_mal "Prescribed"
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la var treat_sev_simple_mal "Purchased"
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la var used_vouchers_admin "Used Voucher"
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la var RXtreat_severe_mal "Prescribed"
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la var treat_severe_mal "Purchased"
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docpat_p1_theory used_vouchers_admin RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, extra($mycont) type(tex)
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table("$tables/B10_mal_tmt_overall_nl.tex") footnote($footnote0_nl_new GC, PD, and DD indicate tests of gatekeeping costs, patient-driven, and doctor-driven demand respectively. $footnote1) testof("GC PD PD DD DD") signifevidence("Yes Yes Yes No No")
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prehead1($prehead1) title("Impacts on Malaria Treatment Outcomes") lab(mal_tmt_overall_nl)
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prehead2($prehead2) widc(0.12\linewidth) texwid(.8) cluvar($cluvar)
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extrahead(\\ & & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){3-4} \cmidrule(lr){5-6})
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use "$data_final/$patientdata", clear
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cap prog drop dome
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prog define dome
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drop if dropme==1
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la var used_vouchers_admin "Used Voucher"
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la var RXtreat_severe_mal "Prescribed"
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la var treat_severe_mal "Purchased"
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la var RXtreat_sev_simple_mal "Prescribed"
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la var treat_sev_simple_mal "Purchased"
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sum pregnancy
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replace pregnancy=r(mean) if pregnancy==.
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sum ethnic_bambara
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replace ethnic_bambara=r(mean) if ethnic_bambara==.
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end
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dome
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global covariates "num_symptoms symptomsscreening_1 symptomsscreening_2 symptomsscreening_3 symptomsscreening_4 symptomsscreening_5 symptomsscreening_6 daysillness99 agepatient under5 genderpatient pregnancy MSSpregnancy respondent gender ethnic_bambara MSSethnic_bambara speak_french readwrite_fluent_french prischoolorless"
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global mycont "$mycont0 $covariates"
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docpat_hettable_theory used_vouchers_admin RXtreat_sev_simple_mal treat_sev_simple_mal RXtreat_severe_mal treat_severe_mal, extrac($mycont) type(tex)
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table("$tables/B11_mal_tmt_het_nl.tex") footnote($footnote0_nl_new GC, PD, and DD indicate tests of gatekeeping costs, patient-driven, and doctor-driven demand respectively. $footnote1)
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prehead1($prehead1) title("Impacts on Malaria Treatment Outcomes - Heterogeneity by Predicted Malaria Risk") lab(mal_tmt_het_nl)
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prehead2($prehead2) widc(0.12\linewidth) texwid(.8) cluvar($cluvar) testofh("GC/DD -- -- DD DD") signifevidenceh("No -- -- No No") testofl("GC/PD PD PD -- --") signifevidencel("Yes Yes Yes -- --")
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extrahead(\\ & & \multicolumn{2}{c}{Any Malaria Treatment} & \multicolumn{2}{c}{Severe Malaria Treatment} \\ \cmidrule(lr){3-4} \cmidrule(lr){5-6})
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dodo(dome) path("$data_final/_bootstrap") setname("bs_cluCSCOM_") numreps(1000)
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use "$data_final/$patientdata", clear
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drop if dropme==1
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docpat_theory_lso treat_severe_mal_voucher treat_severe_mal_NOvoucher treat_simple_mal_voucher treat_simple_mal_NOvoucher , type(tex)
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table("$tables/B12_vouchers_tmt_lso.tex") footnote($footnoteb DD and PD indicates a test of doctor and patient-driven demand respectively. $footnote1) testof("DD DD PD PD") signifevidence("No No No Yes")
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prehead1($prehead1) title("Use of Voucher for Purchased Malaria Treatment") lab(vouchers_tmt)
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prehead2($prehead2) widc(0.1\linewidth) texwid(.8) cluvar($cluvar) partial($date) lcont($date $clinic $patient)
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use "$data_final/$patientdata", clear
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drop if dropme==1
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gen taking_ACT_simple= taking_ACT_t if treat_simple_mal==1
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label var taking_ACT_t "All Prescribed ACTs"
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label var taking_ACT_simple "Prescribed ACT for Simple Malaria"
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docpat_p1_lso taking_ACT_t taking_ACT_simple, type(tex)
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table("$tables/B13_stockpiling_lso.tex") footnote($footnoteb The first column is limited to individuals who purchased an ACT treatment at the CSCom as part of either simple or severe malaria treatment. The second column is limited to individuals who purchased an ACT as part of simple malaria treatment. $footnote1)
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prehead1($prehead1) title("Share of Patients Taking An ACT at Home Survey") lab(stockpiling)
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prehead2($prehead2) widc(0.12\linewidth) texwid(1) cluvar($cluvar) partial($date) lcont($date $clinic $patient)
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use "$data_final/$patientdata", clear
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drop if dropme==1
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gen no_voucher=.
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replace no_voucher=1 if doctor_voucher==0 & patient_voucher==0
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replace no_voucher=0 if doctor_voucher==1 | patient_voucher==1
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gen pat_infoXno_voucher=patient_info*no_voucher
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gen pat_infoXdoc_voucher=patient_info*doctor_voucher
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gen pat_infoXpat_voucher=patient_info*patient_voucher
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gen doctor_voucher_x_patient_info= doctor_voucher*patient_info
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gen patient_voucher_x_patient_info = patient_voucher*patient_info
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gen reported_Malaria_test_RX=reported_Malaria_test if RXtreat_sev_simple_mal==1
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gen reported_RDT_RX=reported_RDT if RXtreat_sev_simple_mal==1
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gen reported_GE_FS_RX=reported_GE_FS if RXtreat_sev_simple_mal==1
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la var reported_Malaria_test_RX "Any Malaria Test"
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la var reported_RDT_RX "RDT Test"
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la var reported_GE_FS_RX "Microscopy Test"
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la var RXtreat_sev_simple_mal "Prescribed Antimalarial"
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la var treat_sev_simple_mal "Purchased Antimalarial"
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la var reported_Malaria_test "Any Malaria Test"
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la var reported_GE_FS "Microscopy Test"
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la var reported_RDT "RDT Test"
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docpat_pat_aux_lso reported_Malaria_test reported_RDT reported_GE_FS reported_Malaria_test_RX reported_RDT_RX reported_GE_FS_RX, type(tex)
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table("$tables/B14_mal_testing_info_RX_lso.tex") footnote($footnoteb $footnote1)
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prehead1($prehead1) title("Impacts of Patient Information on Malaria Testing at the Clinic") lab(mal_testing_info_RX_lso)
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prehead2($prehead2) widc(0.1\linewidth) texwid(1.3) cluvar($cluvar)
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extrahead(\\ & \multicolumn{3}{c}{All Patients} & \multicolumn{3}{c}{If Prescribed Antimalarial} \\ \cmidrule(lr){2-4} \cmidrule(lr){5-7})
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partial($date) lcont($date $clinic $patient)
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use "$data_final/$patientdata", clear
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cap prog drop dome
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prog define dome
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drop if dropme==1
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g reported_cost_mal= reported_totalcost if RXtreat_sev_simple_mal
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g reported_cost_sev= reported_totalcost if RXtreat_severe_mal
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la var reported_totalcost "Patient Costs"
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la var reported_cost_mal "Malaria Patients"
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la var reported_cost_sev "Severe Malaria Patients"
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la var reported_totalcost_pre "Clinic Revenues"
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end
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dome
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docpat_pantable_lso reported_totalcost_pre reported_totalcost, type(tex)
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table("$tables/B15_cost_overall_lso.tex") footnote($footnoteb In Panel B, standard errors are based on 1,000 bootstrap replications, with re-sampling at the clinic level. Predicted malaria risk is re-calculated on each bootstrap replication. All variables measured in CFA top-coded at the 99th percentile. CFA610 $\approx$ USD1. Malaria cases classified based on doctor prescriptions. $footnote1)
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prehead1($prehead1) title("Impacts on Clinic Revenues and Patient Costs (CFA)") lab(cost_overall)
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prehead2($prehead2) widc(0.12\linewidth) texwid(.8) cluvar($cluvar)
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path("$data_final/_bootstrap") setname("bs_cluCSCOM_") dodo(dome) numreps(1000) partial($date) lcont($date $clinic $patient)
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use "$data_final/$patientdata", clear
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drop if dropme==1
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la var RXexpected_mal_match_any "Overall Match"
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la var expected_mal_match_any "Overall Match"
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g RXexpected_mal_match_anyX= RXexpected_mal_match_any if RXmatch_treat_RDT!=.
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g expected_mal_match_anyX= expected_mal_match_any if RXmatch_treat_RDT!=.
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la var expected_mal_match_any_pos "Malaria Positive"
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la var RXexpected_mal_match_any_pos "Malaria Positive"
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la var expected_mal_match_any_neg "Malaria Negative"
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la var RXexpected_mal_match_any_neg "Malaria Negative"
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la var RXexpected_mal_match_anyX "Prescribed"
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la var expected_mal_match_anyX "Purchased"
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la var RXmatch_treat_RDT "Prescribed"
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la var match_treat_RDT "Purchased"
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docpat_p1_lso RXexpected_mal_match_anyX expected_mal_match_anyX RXmatch_treat_RDT match_treat_RDT, type(tex)
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table("$tables/B16_expected_match_lso.tex") footnote($footnoteb In columns 3 and 4 match quality is equal to 1 if an individual is malaria positive and was prescribed/bought an antimalarial or is malaria negative and was not prescribed/did not buy an antimalarial and is zero otherwise. In columns 1-2 the value of one is replaced with either the probability an individual is positive (for antimalarial receipt) or the probability an individual is negative (for non-receipt). $footnote1)
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prehead1($prehead1) title("Impacts on Match Between Treatment and Illness - RDT Sub-Sample") lab(expected_match_lso)
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prehead2($prehead2) widc(0.1\linewidth) texwid(1.25) cluvar($cluvar) partial($date) lcont($date $clinic $patient)
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extrahead(\\ & \multicolumn{2}{c}{Expected Match} & \multicolumn{2}{c}{Actual Match} \\ \cmidrule(lr){2-3} \cmidrule(lr){4-5})
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