capture log close
log using FRIP_suppanalyses, replace text

//  program:    FRIP_suppanalyses
//  task:       Supplemental analyses for replication materials
//  project:    FRIP
//  author:     lkd 20140321

version 12.1
clear all 
macro drop _all
set linesize 80

local pgm "FRIP_suppanalyses"
local dte "20140321"
local tag "`pgm'.do lkd `dte'"

//  #1
//  open data
/*
Data will be available from the TESS website. TESS provides data in SPSS
format. You will need to convert to STATA format and change the name below
to whatever you call the dataset.
The following code uses our naming convention for variables.
The TESS data will use TESS's naming convention. Below are the links between
the two naming conventions.

Our name	TESS	Construction instructions
rmanvles	---		sex = male, sexo = heterosexual, condition = lesbian
rmanvgay	---		sex = male, sexo = heterosexual, condition = gay
rfemvhet	---		sex = female, sexo = heterosexual, condition = heterosexual
rfemvles	---		sex = female, sexo = heterosexual, condition = lesbian
rfemvgay	---		sex = female, sexo = heterosexual, condition = gay
rlesvhet	---		sex = female, sexo = lesbian, condition = heterosexual
rlesvles	---		sex = female, sexo = lesbian, condition = lesbian
rlesvgay	---		sex = female, sexo = lesbian, condition = gay
rgayvhet	---		sex = male, sexo = gay, condition = heterosexual
rgayvles	---		sex = male, sexo = gay, condition = lesbian
rgayvgay	---		sex = male, sexo = gay, condition = gay

age			age
white		race	race = white
lhs			educat	educat = less than hs
hs			educat	educat = hs & some college
coll		educat	educat = ba or higher
inc49		income	income < $50,000
inc50		income	income >= $50,000
married		marital	marital = married
childyn		---		sum of ch0_1, ch2_5, ch6_12, ch13_17 at least 1
children	---		sum of ch0_1, ch2_5, ch6_12, ch13_17
ideo		ideo
evangel		---		[rel = baptist or pentecostal] OR [rel = protestant or other
					christian AND attend at least once a mo] AND [race not black]
mainline	---		[rel = protestant or other christian AND attend < once a mo]
					 AND [race not black]
blackprot	---		[rel = baptist or pentecostal] OR [rel = protestant or other
					christian] AND [race = black] 
catholic	---		[rel = catholic]
ofaith		---		rel = mormon, jewish, hindu, buddhist, e. orthodox,
					o. non-chrisitian
noaffil		---		rel = none

leave		Q9		reverse-coded
visit		Q10		reverse-coded
will		Q11		reverse-coded
insure		Q12		reverse-coded
tell		Q5		reverse-coded
hands		Q6		reverse-coded
cheek		Q7		reverse-coded
french		Q8		reverse-coded
marry		Q13		reverse-coded
*/
use FRIP_analysisDS, clear	// make sure to change name as needed

//  #2
//  define locals
local iv "rmanvles rmanvgay rfemvhet rfemvles rfemvgay rlesvhet rlesvles"
local iv "`iv' rlesvgay rgayvhet rgayvles rgayvgay"

local demographics "age white lhs hs coll inc49 inc50 married childyn children"
local demographics "`demographics' ideo evangel mainline blackprot catholic"
local demographics "`demographics' ofaith noaffil"

local controls "age white hs coll inc50 married childyn children ideo"
local controls "`controls' evangel mainline blackprot catholic ofaith"

local formal "leave visit will insure"
local informal "tell hands cheek french"

//  #3
//	Table S2. ologits of Formal Rights with controls
foreach var in `formal' {
	di ". ologit `var' `iv' `controls'"
	eststo: ologit `var' `iv' `controls', vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
	}

esttab using FRIP_TS2.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none) stats(rmanvlesvgay p1 rfemvhetvles p2 rfemvhetvgay p3 ///
	rfemvlesvgay p4 rlesvhetvles p5 rlesvhetvgay p6 ///
	rlesvlesvgay p7 rgayvhetvles p8 rgayvhetvgay p9 rgayvlesvgay p10)

eststo clear

//	#4
//	Table S3. ologits of Informal Privileges with Controls
foreach var in `informal' {
	di ". ologit `var' `iv' `controls'"
	eststo: ologit `var' `iv' `controls', vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
	}

esttab using FRIP_TS3.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none) stats(rmanvlesvgay p1 rfemvhetvles p2 rfemvhetvgay p3 ///
	rfemvlesvgay p4 rlesvhetvles p5 rlesvhetvgay p6 ///
	rlesvlesvgay p7 rgayvhetvles p8 rgayvhetvgay p9 rgayvlesvgay p10)

eststo clear

//	#5
//	Table S4. ologit of Marry with Controls
eststo: ologit marry `iv' `controls', vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)

esttab using FRIP_TS4.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none) stats(rmanvlesvgay p1 rfemvhetvles p2 rfemvhetvgay p3 ///
	rfemvlesvgay p4 rlesvhetvles p5 rlesvhetvgay p6 ///
	rlesvlesvgay p7 rgayvhetvles p8 rgayvhetvgay p9 rgayvlesvgay p10)
	
eststo clear

//	#6
//  Table S5A. Weighted Description of Dependent Measures
/*
Stata's summarize command does not support pweights. See discussion on
Stata's website for differences between aw and pw:
http://www.stata.com/support/faqs/statistics/weights-and-summary-statistics/
*/
estpost sum `formal' `informal' marry [aw=weight1]
esttab using FRIP_TS5A.csv, replace ///
	title(Table S5A. Weighted Description of Dependent Measures) ///
	addnote("Note: N = 1,073") cell("mean sd min max count") ///
	nomtitle nonumber noobs plain
eststo clear

//	Compare means across conditions
foreach var in `formal' `informal' marry {
mean `var' [pw=weight1], ///
	over(SRcon) vce(cluster hhid) // cluster SEs by household ID
}

//	#7
//	Table S5B. Weighted Descriptive Statistics
/*
Stata's summarize command does not support pweights. See discussion on
Stata's website for differences between aw and pw:
http://www.stata.com/support/faqs/statistics/weights-and-summary-statistics/
*/
estpost tab sexo [aw=weight1], m
esttab using FRIP_TS5B.csv, replace ///
	title(Table S5B. Weighted Descriptive Statistics) ///
	cell("pct") nomtitle nonumber noobs plain
eststo clear

estpost sum `demographics' [aw=weight1]
esttab using FRIP_TS5B.csv, append ///
	cell("mean sd min max") nomtitle nonumber noobs plain
eststo clear

//	#8
//	Table S5C. Weighted EFA
/*
For the EFA, create a .txt document with the factor loadings and import into
Excel with spaces as delimiters. Make sure to check "Treat consecutive
delimiters as one." Then, you can change the number of decimal places for easy
import into a Table.

H2 is 1 - uniqueness. Once in Excel, create a new column with 1 - uniqueness
to report H2

Weight1 makes sample representative on all covariates, including sexual ID.
For use with full sample.

Weight2 makes sample representative EXCEPT for sexual ID. For use with
subsamples to maintain cell sizes by sexual ID.
*/
//	Full sample
polychoric `formal' `informal' marry [pw=weight1]
matrix polymat = r(R)
//	Generate mean and sd vectors for factormat
mat accum sdmat = `formal' `informal' marry [aw=weight1], means(meanmat) ///
	noconstant deviations
local n r(N)
di `n'

matrix sdmat = sdmat/(r(N)-1)
matrix sdmat = vecdiag(sdmat)
factormat polymat, n(1045) means(meanmat) sds(sdmat)
rotate

//	Heterosexual sample
polychoric `formal' `informal' marry if sexo<=2 [pw=weight2]
matrix polymat = r(R)
//	Generate mean and sd vectors for factormat
mat accum sdmat = `formal' `informal' marry if sexo<=2 [aw=weight2], means(meanmat) ///
	noconstant 
local n r(N)
di `n'

matrix sdmat = sdmat/(r(N)-1)
matrix sdmat = vecdiag(sdmat)
factormat polymat, n(487) means(meanmat) sds(sdmat)
rotate

//	LG sample
polychoric `formal' `informal' marry if sexo>=3 [pw=weight2]
matrix polymat = r(R)
//	Generate mean and sd vectors for factormat
mat accum sdmat = `formal' `informal' marry if sexo>=3 [aw=weight2], means(meanmat) ///
	noconstant 
local n r(N)
di `n'

matrix sdmat = sdmat/(r(N)-1)
matrix sdmat = vecdiag(sdmat)
factormat polymat, n(558) means(meanmat) sds(sdmat)
rotate

//	#9
//	Table S5D. Weighted ologits of Formal Rights
foreach var in `formal' {
	di ". ologit `var' `iv' [pw=weight1]"
	eststo: ologit `var' `iv' [pw=weight1], vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
		
	di ". ologit `var' `iv' `controls' [pw=weight1]"
	eststo: ologit `var' `iv' `controls' [pw=weight1], vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
	}

esttab using FRIP_TS5D.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none) stats(rmanvlesvgay p1 rfemvhetvles p2 rfemvhetvgay p3 ///
	rfemvlesvgay p4 rlesvhetvles p5 rlesvhetvgay p6 ///
	rlesvlesvgay p7 rgayvhetvles p8 rgayvhetvgay p9 rgayvlesvgay p10)

eststo clear

//	#10
//	Table S5E. Weighted ologits of Informal Privileges
foreach var in `informal' {
	di ". ologit `var' `iv' [pw=weight1]"
	eststo: ologit `var' `iv' [pw=weight1], vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
		
	di ". ologit `var' `iv' `controls' [pw=weight1]"
	eststo: ologit `var' `iv' `controls' [pw=weight1], vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
	}

esttab using FRIP_TS5E.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none) stats(rmanvlesvgay p1 rfemvhetvles p2 rfemvhetvgay p3 ///
	rfemvlesvgay p4 rlesvhetvles p5 rlesvhetvgay p6 ///
	rlesvlesvgay p7 rgayvhetvles p8 rgayvhetvgay p9 rgayvlesvgay p10)

eststo clear

//	#11
//	Table S5F. Weighted ologit of Marry
eststo: ologit marry `iv' [pw=weight1], vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)
		
eststo: ologit marry `iv' `controls' [pw=weight1], vce(cluster hhid)
	test rmanvles = rmanvgay
		estadd scalar rmanvlesvgay = r(chi2)
		estadd scalar p1 = r(p)
	test rfemvhet = rfemvles
		estadd scalar rfemvhetvles = r(chi2)
		estadd scalar p2 = r(p)
	test rfemvhet = rfemvgay
		estadd scalar rfemvhetvgay = r(chi2)
		estadd scalar p3 = r(p)
	test rfemvles = rfemvgay
		estadd scalar rfemvlesvgay = r(chi2)
		estadd scalar p4 = r(p)
	test rlesvhet = rlesvles
		estadd scalar rlesvhetvles = r(chi2)
		estadd scalar p5 = r(p)
	test rlesvhet = rlesvgay
		estadd scalar rlesvhetvgay = r(chi2)
		estadd scalar p6 = r(p)
	test rlesvles = rlesvgay
		estadd scalar rlesvlesvgay = r(chi2)
		estadd scalar p7 = r(p)
	test rgayvhet = rgayvles
		estadd scalar rgayvhetvles = r(chi2)
		estadd scalar p8 = r(p)
	test rgayvhet = rgayvgay
		estadd scalar rgayvhetvgay = r(chi2)
		estadd scalar p9 = r(p)
	test rgayvles = rgayvgay
		estadd scalar rgayvlesvgay = r(chi2)
		estadd scalar p10 = r(p)

esttab using FRIP_TS5F.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none) stats(rmanvlesvgay p1 rfemvhetvles p2 rfemvhetvgay p3 ///
	rfemvlesvgay p4 rlesvhetvles p5 rlesvhetvgay p6 ///
	rlesvlesvgay p7 rgayvhetvles p8 rgayvhetvgay p9 rgayvlesvgay p10)
	
eststo clear

//	#12
//	Table S6A. Brant test
foreach var in leave tell french {
	eststo: ologit `var' `iv' `controls', vce(cluster hhid)
	estadd brant, detail
	}
	
foreach var in will3 hands3 cheek3 {
	eststo: ologit `var' `iv' `controls', vce(cluster hhid)
	estadd brant, detail
	}

esttab using FRIP_TS6A.csv, replace ///
	b(%12.2f) nogaps se plain nolz cell(brant[chi2] brant[p>chi2])
		
eststo clear

//	#13
//	Table S6B. gologits
eststo: gologit2 leave `iv' `controls', vce(cluster hhid) ///
	npl(rmanvgay rlesvgay rgayvles age)
eststo: gologit2 tell `iv' `controls', vce(cluster hhid) ///
	npl(childyn)
eststo: gologit2 hands3 `iv' `controls', vce(cluster hhid) ///
	npl(evangel)
eststo: gologit2 cheek3 `iv' `controls', vce(cluster hhid) ///
	npl(rgayvles)
eststo: gologit2 french `iv' `controls', vce(cluster hhid) ///
	npl(children)

esttab using FRIP_TS6B.csv, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se nolz

eststo clear

//	#14
//	Table S6C-S6E. mlogits
eststo leave: mlogit leave `iv' `controls', vce(cluster hhid) base(1)
eststo visit: logit visit2 `iv' `controls', vce(cluster hhid)
eststo will: mlogit will3 `iv' `controls', vce(cluster hhid) base(1)
eststo insure: logit insure2 `iv' `controls', vce(cluster hhid)
eststo tell: mlogit tell `iv' `controls', vce(cluster hhid) base(1)
eststo hands: mlogit hands3 `iv' `controls', vce(cluster hhid) base(1)
eststo cheek: mlogit cheek3 `iv' `controls', vce(cluster hhid) base(1)
eststo french: mlogit french `iv' `controls', vce(cluster hhid) base(1)
eststo marry: logit marry2 `iv' `controls', vce(cluster hhid)

esttab using FRIP_TS6C-S6E.csv, replace ///
    b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se nolz

eststo clear

//	#15
//	Table S6F-S6H. ols
foreach var in `formal' {
	di ". reg `var' `iv' `controls'"
	eststo: reg `var' `iv' `controls', vce(cluster hhid)
	}

esttab using FRIP_TS6F.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none)
		
eststo clear
	
foreach var in `informal' {
	di ". reg `var' `iv' `controls'"
	eststo: reg `var' `iv' `controls', vce(cluster hhid)
	}

esttab using FRIP_TS6G.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none)
		
eststo clear

eststo: reg marry `iv' `controls', vce(cluster hhid)
	
esttab using FRIP_TS6H.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none)
	
eststo clear

//	Online Supplement 7
/*	This portion of the online supplement requires that the 2010 GSS
be appended to the TESS data file. Code reltrad using Steensland and
colleagues' code and name the variable reltrad to run comparisons.

Simply comment out this part to run the rest of the do-file if not
interested in this comparison.
*/

//	#16
//	open data
use FRIP_gssappended, clear

//	#17
//	Table S7A. Prevalence Comparison
/*
Create a .txt document with the output and import into
Excel with spaces as delimiters. Make sure to check "Treat consecutive
delimiters as one." Then, you can change the number of decimal places for easy
import into a Table.
*/
tab reltrad gss, column // gss is an indicator for GfK vs. GSS (1 = GSS)

//	#18
//	Table S7B. Comparison of Respondent Characteristics
local demo "rman rfem rgay rles age rce_wht ed_coll ed_hs ed_lhs inc_50k"
local demo "`demo' married ideo childyn children"
local relig "evangel mainline blackprot catholic ofaith noaffil"

foreach r in `relig' {
di "`r'"
di "TESS Sample"
mean `demo' [pw=weight1] if `r'==1 & gss==0
di "GSS Sample"
mean `demo' if `r'==1 & gss==1
}

//	#19
//	Table S7C. Models with Alternative Controls
use FRIP_analysisDS, clear
local altcontrols "age white hs coll inc50 married childyn children ideo"
local altcontrols "`altcontrols' altprot altcath altother attendm"
//	alternate controls do not include attendance info or race in rel var code

foreach var in `formal' `informal' marry {
	di ". ologit `var' `iv' `altcontrols'"
	eststo: ologit `var' `iv' `altcontrols', vce(cluster hhid)
	}
	
esttab using FRIP_TS7C.rtf, replace ///
	b(%12.3f) nogaps star(* 0.05 ** 0.01 *** 0.001) se one compress nolz ///
	eqlabels(none)
		
eststo clear


log close
exit