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***SOCI 600: INTRODUCTION TO SOCIOLOGICAL DATA ANALYSIS
***HYPOTHESIS TESTING: ONE- AND TWO-SAMPLE CASES
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***CLEAR MEMORY
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clear all

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***CREATE SHORTCUTS AND LOG FILE
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***Shortcut for folders
global codes  = "H:\course\codes"
global data   = "H:\course\data"
global output = "H:\course\output"

***Start saving results window
log using "$codes\Stata05.log", replace text

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***OPENING COMMANDS
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***Tell Stata to not pause for "more" messages
set more off

***Open 2019 ACS (only Texas)
use "$data\ACS2019.dta", clear

***Complex survey design
svyset cluster [pweight=perwt], strata(strata) singleunit(scaled)

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***GENERATE VARIABLES
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***Sex
gen female=.
  replace female=0 if sex==1 // Male
  replace female=1 if sex==2 // Female

label define female 0 "Male" 1 "Female"
label values female female

***Race/ethnicity
gen raceth=.
  replace raceth=1 if race==1 & hispan==0 // White
  replace raceth=2 if race==2 & hispan==0 // Black
  replace raceth=3 if hispan>=1 & hispan<=4 // Hispanic
  replace raceth=4 if (race==4 | race==5 | race==6) & hispan==0 // Asian
  replace raceth=5 if race==3 & hispan==0 // Native American
  replace raceth=6 if (race==7 | race==8 | race==9) & hispan==0 // Other

label define raceth 1 "White" 2 "African American" 3 "Hispanic" ///
                    4 "Asian" 5 "Native American" 6 "Ohter races"
label values raceth raceth

***Age
egen agegr = cut(age), at(0,16,20,25,35,45,55,65,100)

label define agecode 0 "0-15" 16 "16-19" 20 "20-24" 25 "25-34" ///
                     35 "35-44" 45 "45-54" 55 "55-64" 65 "65-100"
label values agegr agegr

***Educational attainment
gen educgr=.
  replace educgr=1 if educ>=0 & educ<=5 // Less than high school
  replace educgr=2 if educ==6 // High school
  replace educgr=3 if educ==7 | educ==8 // Some college
  replace educgr=4 if educ==10 // College
  replace educgr=5 if educ==11 // 5+ years of college, graduate school

label define educgr 1 "Less than high school" 2 "High school" ///
                    3 "Some college" 4 "College" 5 "Graduate school"
label values educgr educgr

***Marital status
gen marital=.
  replace marital=1 if marst==1 | marst==2 // Married
  replace marital=2 if marst>=3 & marst<=5 // Separated, divorced, widowed
  replace marital=3 if marst==6 // Never married, single

label define marital 1 "Married" 2 "Separated, divorced, widowed" 3 "Never married"
label values marital marital

***Migration status
gen migrant=.
  replace migrant=1 if migrate1d==10 | migrate1d==23 // same house or within PUMA
  replace migrant=2 if migrate1d>=24 & migrate1d<=32 // internal migrant
  replace migrant=3 if migrate1d==40 // international migrant

label define migrant 1 "Non-migrant" 2 "Internal migrant" 3 "International migrant"
label values migrant migrant

***Wage and salary income
gen income=.
  replace income=incwage if incwage!=999999

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***ONE-SAMPLE Z-TEST AND t-TEST
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***Personal income of Veterans in Texas (ACS)
***compared to US population 15+ (U.S. Census Bureau)
***https://fred.stlouisfed.org/series/MAPAINUSA646N#

***Mean personal income of US population in 2019 (U.S. Census Bureau) = 54,129

***Generate dummy variable for Veterans
tab vetstat, m

gen veteran=.
  replace veteran=1 if vetstat==2 // Veteran
  replace veteran=0 if vetstat==1 // Not a Veteran
  
tab vetstat veteran, m

***Mean wage and salary income of Veterans in Texas in 2019 (ACS)
svy, subpop(if veteran==1): mean income
mean income if veteran==1

***Is the mean income of Veterans in Texas ($30,511.68) significantly lower
***than mean income of US population 15+ ($54,129)?

***Z-test (it does not allow the use of weight or complex survey design)
ztest income=54129 if veteran==1

***t-test (it does not allow the use of weight or complex survey design)
ttest income=54129 if veteran==1

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***ONE-SAMPLE TEST OF PROPORTIONS
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***Gender composition of sample of adult population (18+) in Texas (ACS)
***compared to US population
***https://www.census.gov/quickfacts/fact/table/US/PST045221 (U.S. Census Bureau)
***https://data.worldbank.org/indicator/SP.POP.TOTL.FE.ZS?locations=US (World Bank)

***Percentage of women in the US population in 2019 (U.S. Census Bureau) = 50.5%

***Percentage of 18+ women in Texas in 2019 (ACS)
tab female [fweight=perwt] if age>=18 & age<=92
tab female if age>=18 & age<=92

***Is the percentage of women 18+ in Texas (51.35%) significantly higher
***than the percentage of women in the total population (50.5%)?

***Proportion test (it does not allow the use of weight or complex survey design)
prtest female=.505

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***TWO-SAMPLE t-TEST
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***Mean of wage and salary income by sex
tabstat income if income!=0 [fweight=perwt], by(sex)

***t-test of personal income by sex
***Weights are not allowed
tabstat income if income!=0, by(sex)
ttest income if income!=0, by(sex)

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***TWO-SAMPLE TEST OF PROPORTIONS
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***Migration status by sex
***Independent variable (sex): column
***Dependent variable (migrant): row
tab migrant sex [fweight=perwt]

***Percentage distribution is estimated
***within categories of independent variable (sex)
***Add up to 100% within each sex category
tab migrant sex [fweight=perwt], col nofreq

***Proportion is tested for a dummy dependent variable
***by categories of a dummy independent variable (sex) 

***Need to create variable only for internal migrant vs. non-migrant
***as well as only for international migrant vs. non-migrant

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***Internal migration
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***Dummy variable for internal migration (domestic migration)
gen dommig=.
  replace dommig=0 if migrant==1 // non-migrant
  replace dommig=1 if migrant==2 // internal migrant
  
label define dommig 0 "Non-migrant" 1 "Internal migrant"
label values dommig dommig

tab migrant dommig, m

***Proportion of internal migrants by sex
tab dommig sex [fweight=perwt], col nofreq
tabstat dommig [fweight=perwt], by(sex)

***Sample size for internal migration test
count if dommig!=. & sex!=.

***Test of proportions of internal migrants by sex
***Weights are not allowed
tab dommig sex, col nofreq
prtest dommig, by(sex)

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***International migration
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***Dummy variable for international migration
gen intmig=.
  replace intmig=0 if migrant==1 // non-migrant
  replace intmig=1 if migrant==3 // international migrant
  
label define intmig 0 "Non-migrant" 1 "International migrant"
label values intmig intmig

tab migrant intmig, m

***Proportion of international migrants by sex
tab intmig sex [fweight=perwt], col nofreq
tabstat intmig [fweight=perwt], by(sex)

***Sample size for international migration test
count if intmig!=. & sex!=.

***Test of proportions of international migrants by sex
***Weights are not allowed
tab intmig sex, col nofreq
prtest intmig, by(sex)

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***CLOSING COMMANDS
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***Save data
save "$data\Stata05.dta", replace

***Save log
log close