May 25, 2017

Random graphs (96): Categorical variables

use S003A S002 X001 C041 C039 C038 C037 if inlist(S002, 4, 5) ///
    using WVS_Longitudinal_1981-2014_stata_v_2014_11_25.dta, clear

// Declare missing values
mvdecode C041 C039 C038 C037, mv(-5 -4 -3 -2 -1)

// Factor analysis
factor C041 C039 C038 C037, pcf
alpha C041 C039 C038 C037, item
local alph = round(`r(alpha)', .01)

// Prepare variables
scores nonworkethic = mean(C041 C039 C038 C037), nv(3) 
generate workethic = 5 - nonworkethic 
gen male = (X001 == 1) if X001 != -2
drop nonworkethic X001
// Create descriptive plot foreach var of varlist C041 C039 C038 C037 { recode `var' (1 = 4 "Strongly agree") /// (2 = 3 "Agree") /// (3 = 2 "Neither agree nor disagree") /// (4 = 1 "Disagree") /// (5 = 0 "Strongly disagree"), gen(`var'_rec) numlabel `var'_rec, add mask("# ") twoway histogram `var'_rec, discrete horizontal yla(0/4, valuelabel) percent /// title("`: variable label `var''") /// ytitle("") /// name(`var', replace) nodraw drop `var'_rec } graph combine C041 C039 C038 C037, col(2) row(2) altshrink title("Work ethic is measured as the average of four items:") /// caption("In a PCA, all items load on one dimension; explained variance = 49%, Cronbach's alpha = `alph'", span) note("{it:Source:} WVS 1999-2009, pooled", span) name(figure1, replace) drop C041 C039 C038 C037
// Calculate country differences preserve statsby mean_ = _b[_cons] /// loci = (_b[_cons] - 1.96 * _se[_cons]) /// hici = (_b[_cons] + 1.96 * _se[_cons]) /// , by(S003A) clear: /// regress workethic // Sort coefficients by size egen order_ = rank(mean_), unique labmask order_, value(S003A) decode // Plot twoway (rcap mean_ mean_ order_, horizontal) /// (rspike loci hici order_, horizontal) /// , legend(off) ylabel(1/63, valuelabels ang(h) labsize(*.8)) /// xlabel(0 (1) 4, grid format(%6.1f)) name(all, replace) /// xmtick(0 (.5) 4) /// ytitle("") xtitle("Work ethic across countries") /// title("{bf:A}", justification(left) bexpand span) /// xscale(alt) ysize(10) nodraw restore // Country differences--men only preserve statsby mean_ = _b[_cons] /// loci = (_b[_cons] - 1.96 * _se[_cons]) /// hici = (_b[_cons] + 1.96 * _se[_cons]) /// , by(S003A) clear: /// regress workethic if male == 1 // Sort coefficients by size egen order_ = rank(mean_), unique labmask order_, value(S003A) decode // Plot twoway (rcap mean_ mean_ order_, horizontal) /// (rspike loci hici order_, horizontal) /// , legend(off) ylabel(1/63, valuelabels ang(h) labsize(*.8)) /// xlabel(0 (1) 4, grid format(%6.1f)) name(men, replace) /// xmtick(0 (.5) 4) /// ytitle("") xtitle("Men's work ethic across countries") /// title("{bf:B}", justification(left) bexpand span) /// xscale(alt) ysize(10) nodraw restore // Calculate gender gap preserve statsby mean_ = _b[male] /// loci = (_b[male] - 1.96 * _se[male]) /// hici = (_b[male] + 1.96 * _se[male]) /// , by(S003A) clear: /// regress workethic male // Sort coefficients by size egen order_ = rank(mean_), unique labmask order_, value(S003A) decode // Plot twoway (rcap mean_ mean_ order_, horizontal) /// (rspike loci hici order_, horizontal) /// , legend(off) ylabel(1/63, valuelabels ang(h) labsize(*.8)) /// xlabel(-.25 (.25) .5, grid format(%6.2f)) name(gendergap, replace) /// xmtick(-.25 (.1) .5) /// text(63 .5 "Men" "higher", place(sw)) /// text( 1 -.25 "Women" "higher", place(ne)) /// ytitle("") xtitle("Gender gap in work ethic") /// title("{bf:C}", justification(left) bexpand span) /// xscale(alt) ysize(10) nodraw restore graph combine all men gendergap, note(" " "{it:Source:} WVS 1999-2009, pooled", span) col(3) ysize(12) xsize(18) altshrink /// title("Work ethic in cross-national comparison", span) name(figure2, replace)