clear
input str50 study year r n
"Duncan et al." 1972 .573 14347
"Chamberlain & Griliches" 1977 .508 584
"Hauser et al." 1982
"Hauser" 1984 .404 518
"Hauser & Mossel" 1985 .404 518
"Hauser & Sewell" 1986 .459 532
"Hauser & Wong" 1989 .57 164
"Dronkers" 1993 .6 244
"Scarr & Weinberg" 1994 .32 105
"Hauser et al." 1999 .421 1100
"Ashenfelter & Zimmerman" 1997 .51 143
"Sieben & de Graaf" 2001 .515 2200
"Sieben & de Graaf" 2003 .342 152618
"Conley & Glauber" 2007 .576 1777
"Beenstock" 2008 .435 6926
"Conley" 2008 .578 1777
"Conley & Glauber" 2008 .627 1127
"Mazumder" 2008 .602 6097
"Olneck" 1977 .549 346
"Lee" 2009 .478 4561
"Ermisch & Pronzanto" 2010 .37 68957
"Bjorklund & Salvanes" 2011 .39 34476
"Lindahl" 2011 .411 9864
"Mazumder" 2011 .665 671
"Adermon" 2012 .424 338222
"Schnitzlein" 2014 .656 1480
"Andrade" 2016 .122 1632366
"Bredtman & Smith" 2016 .327 3087
"Pfeffer et al." 2016 .46 5215
end
generate z = atanh(r) // r-to-z = inverse hyperbolic tangent
generate sez = sqrt(1/(n - 3))
admetan z sez
display _newline ///
" Pooled estimate of r = " tanh(r(eff)) _newline ///
"Lower Limit of 95% CI = " tanh(r(eff) - (1.96 * r(se_eff))) _newline ///
"Upper Limit of 95% CI = " tanh(r(eff) + (1.96 * r(se_eff)))
// Prepare data for -forestplot-
generate _USE = 1
// Generate CI's for r
generate lb = tanh(_LCI)
generate ub = tanh(_UCI)
// Generate study labels for -forestplot-
generate _LABELS = study + " (" + string(year, "%02.0f") + ")"
label var n "Sample size"
// Add effect size to data set
local new = _N + 1
set obs `new'
replace _LABELS = "{bf:Overall}" if _n == _N
replace r = tanh(r(eff)) if _LABELS == "{bf:Overall}"
replace lb = tanh(r(eff) - (1.96 * r(se_eff))) if _LABELS == "{bf:Overall}"
replace ub = tanh(r(eff) + (1.96 * r(se_eff))) if _LABELS == "{bf:Overall}"
replace _USE = 5 if _LABELS == "{bf:Overall}"
// Forest plot
forestplot r lb ub, effect("Correlation") rcol(n) leftjustify nowt nonull xlabel(0 .1 .2 .3 .4 .5 .6 .7)
