Random graphs (72): Dot plots with the by() option

clear
input str20 cntry bindirect blbindirect ulbindirect bdirect blbdirect ulbdirect
Austria 0.002 -0.002 0.005 0.008 -0.016 0.032
Germany 0.006 0.000 0.012 0.040 0.017 0.063
Sweden 0.001 -0.005 0.007 0.054 0.031 0.076
Netherlands 0.000 -0.006 0.006 0.039 0.017 0.061
Spain 0.005 0.002 0.009 0.016 -0.001 0.033
Italy 0.000 -0.005 0.005 0.029 0.011 0.047
France 0.001 -0.003 0.006 0.043 0.025 0.061
Denmark 0.001 0.000 0.003 0.015 0.001 0.029
Greece 0.000 -0.003 0.003 0.041 0.026 0.057
Switzerland 0.002 -0.002 0.006 0.003 -0.020 0.026
Belgium 0.000 -0.003 0.004 0.033 0.016 0.050
"Czech Republic" 0.004 -0.001 0.010 0.073 0.031 0.115
Poland -0.004 -0.010 0.002 0.034 -0.003 0.071
end

// Reshape to long format
reshape long b blb ulb, j(fx "indirect" "direct") i(cntry) string

// Encode variables
encode cntry, gen(country)
encode fx, gen(effect)
label define effect 1 "Direct effect" 2 "Indirect effect", modify

// Sort by biggest direct effect size
egen order_ = rank(b) if effect == 1, unique
labmask order_, val(country) decode
bysort country (order_): replace order_ = order_[1] // Copy value to all cases 

// xrescale makes sure that x-axis fits both by() plots
twoway (dot b order_, horizontal by(effect, legend(off) note(" ") xrescale)) ///
       (rspike blb ulb order_, horizontal by(effect)) ///
      , ylabel(1 (1) 13, val) xscale(alt) ///
        ytitle(" ") xline(0) 
    

Random graphs (71): Proportions with confidence intervals

use sharew5_rel1-0-0_it.dta, clear

// Prepare variables
recode it004_ (1 = 1 "Yes") (5 = 0 "No") (-1 -2 . = .), generate(internetuser)
label var internetuser "Internet use in last 7 days"
decode country, gen(cntry)

// Define stuff
tempname foo
postfile `foo' str25 cntry perc perc_ll perc_ul using "C:\Windows\Temp\test.dta", replace
levelsof cntry, local(levels)

// Calculate proportions by country
foreach country of local levels {

    capture proportion internetuser if cntry == "`country'"
    matrix fcoefs  = r(table)
    local fperc    = fcoefs[1,2] * 100
    local fperc_ll = fcoefs[5,2] * 100
    local fperc_ul = fcoefs[6,2] * 100

    di "`country'"  _skip(2)  `fperc_ll' _skip(2) `fperc' _skip(2) `fperc_ul'

    if "`fperc'" != "" {    // Make sure that the loop doesn't break if empty
    post `foo' ("`country'") (`fperc') (`fperc_ll') (`fperc_ul')
    }
}
postclose `foo'

// Use posted data set
use "C:\Windows\Temp\test.dta", clear

// Sort countries by size
egen order_ = rank(perc), unique
labmask order_, value(cntry) 

// Plot
twoway (dot perc order_, horizontal) ///
       (rspike perc_ll perc_ul order_, horizontal), ///
       ylabel(1/15, val) legend(off) xscale(range(20 80) alt) ///
       ytitle("") xtitle("% Internet users (in last 7 days)") ///
       xlabel(20(10)80, grid) ///
       note(" " "{it:Source:} SHARE wave 5, doi:10.6103/SHARE.w5.100", span)

Random graphs (69): ICC's with confidence intervals

use sharew1_rel2-6-0_gv_isced.dta, clear

// Reshape data into long format
reshape long iscedy_c, i(mergeid) j(child)
// Fix variable of interest
recode iscedy_c (-7 = .a "not yet coded (temporary)") ///
                (-2 = .b "refusal") ///
                (-1 = .c "don't know") ///
                (95 = .d "still in school") ///
                (97 = .e "other") ///
                ( . = .f "missing") ///
               , gen(years)
label var years "Years of education"
    
// Israel doesn't provide a ISCED-to-years conversion, thus it's dropped here
drop if country == 25

// Fix country variable
decode country, gen(cntry)

// Calculate ICC's per country
tempname foo
postfile `foo' str100 commandline_str str20 cntry icc icclb iccub N N_groups using "C:\Windows\Temp\test.dta", replace    
    
levelsof cntry, local(country)

foreach x of local country {
  *di "`x'"
  qui mixed years || mergeid: if cntry == "`x'", reml
  qui estat icc
  
  matrix groups = e(N_g)
  scalar n_g = groups[1,1]
  matrix cis =  r(ci2)
  scalar icclb = cis[1,1]
  scalar iccub = cis[1,2]
  
  post `foo' (e(cmdline)) ("`x'") (r(icc2)) (icclb) (iccub) (e(N)) (n_g)
  
  matrix stuff1 = (r(icc2), icclb, iccub, e(N), n_g)
  if "`x'" == "Austria" matrix table1 = stuff1
  else matrix table1 = (table1\stuff1)
}

postclose `foo'

matrix rownames table1 = `country'
matrix colnames table1 = "ICC" "CI lower" "CI upper" "Children" "Families"
esttab matrix(table1, fmt(2 2 2 0 0))

use "C:\Windows\Temp\test.dta", clear

egen order_ = rank(-icc), unique
labmask order_, value(cntry)

twoway (rcap   icc icc order_, horizontal) ///
       (rspike icclb iccub order_, horizontal) ///
      , ylabel(1/11, val) legend(off) ytitle("") xscale(alt) ///
        xtitle("Sibling correlations in educational attainment") ///
        note(" " "{it:Source:} SHARE wave 1, doi:10.6103/SHARE.w1.260", span)

erase "C:\Windows\Temp\test.dta"

Random graphs (68): Bar graph

use sharew1_rel2-6-0_ch.dta, clear

recode ch001_ (0/4  =  0   "Less than five children") ///
              (5/17 =  100 "Five children and more") ///
              (-1   = .a "Refusal") ///
              (-2   = .b "Don't know") ///
             , gen(largefamilies)
   
graph bar largefamilies if country != 25, over(country, sort(largefamilies)) ///
          horizontal ytitle("% with five and more children") ///
   note(" " "{it:Source:} SHARE wave 1, doi:10.6103/SHARE.w1.260", span) ///
          yalternate