用stata做图时，可能需要调整一些细节。比如图的长宽，换个marker的形状等。因为用的不多，经常是用到的时候想不起来，搜索起来又得费时间，干脆在这里写一个例子。以后用的时候直接来看一眼。这个主要是写给自己用的，懂得人自然懂其价值，也欢迎收藏。
coefplot (enrolled, label(Enrolled group) m(O) mcolor(black) mfcolor(black) msize(*1.5) mlcolor(black)) ///
(nonenrolled, label(Non-enrolled group) m(O) mcolor(black) mfcolor(white) msize(*1.5) mlcolor(black) lcolor(*2)), ///
drop(_cons) xline(0,lpattern(dash)) xlabel(-1.5(0.5)0.5) ///
legend(col(1) pos(11) ring(0)) scheme(s2mono) graphregion(color(white)) ///
coeflabels( Gender="Female") ///
scale(*.9) ///
xsize(4.5) ysize(3.6) ///
headings(Age = " " 2.Education = "{bf:Education}" 2.Income = "{bf:Income}" ///
2.Cliniccheck = "{bf:Clinic check-up}" 2.Duration = "{bf:Duration}", gap(-1) labgap(2)) ///
groups(Age = " "?.Education = " " ?.Income = " " ?.Cliniccheck = " " ?.Duration = " ", gap(1))
graph save figure_1.gph, replace
graph export "figure_1.png", as(png) replace
logit Adherence Gender Age i.Education i.Income ///
Urbanity i.Cliniccheck Diabete i.Duration BP, or, if Enrollment == 0
estimates store enrolled
logit Adherence Gender Age i.Education i.Income ///
Urbanity i.Cliniccheck Diabete i.Duration BP, or, if Enrollment == 1
estimates store nonenrolled
coefplot (enrolled, label(enrolled group)) ///
(nonenrolled, label(non-enrolled group)), drop(_cons) xline(0) ///
xlabel(-1.5(0.5)0.5)
coefplot (enrolled, mlabels(length = 1 "+" * =11 "0")) ///
(nonenrolled, mlabels(trunk length = 1 "+" * =11 "0")) ///
, drop(_cons) xline(0) ///
subti("Hypotheses: 0 no effect, + positive effect, - negative effect", size(small))
coefplot (enrolled, label(enrolled group)) ///
(nonenrolled, label(non-enrolled group)), drop(_cons) xline(1) ///
xlabel(0(0.5)1.5) eform xtitle(Odds ratio)
coefplot (enrolled, offset(.15)) (nonenrolled, drop(*#*) offset(-.15)) (nonenrolled, keep(*#*) pstyle(p2)), ///
xline(0) legend(off) msymbol(D) mfcolor(white) ciopts(lwidth(*2) lcolor(*.9)) ///
coeflabels(_cons = ”Constant”, wrap(30) notick labcolor(black) labsize(medlarge) labgap(2)) xlabel(-2(1)4)
coefplot (enrolled, offset(.15)) (nonenrolled, drop(*#*) offset(-.15)) (nonenrolled, keep(*#*) pstyle(p2)), ///
xline(0) legend(off) msymbol(D) mfcolor(white) ciopts(lwidth(*2) lcolor(*.9)) ///
grid(between glcolor(black) glpattern(dash)) ///
coeflabels(_cons = ”Constant”, wrap(30) notick labcolor(black) labsize(medlarge) labgap(2)) xlabel(-2(1)4)
coefplot, xline(0) drop(_cons) omitted baselevels ///
headings(1.Education = ”{bf:Education}” 1.Income = ”{bf:Annual Household Income}” ///
1.Duration = ”{bf:Duration}” 1.Cliniccheck = ”{bf:Frequency of clinic check-up}”, labcolor(orange))
* boxplot to check if there are outlier
foreach var of varlist a b c {
graph box `var', scheme(s1mono) ylabel(0(4)24) xsize(5) ysize(5)
graph save "`var'.gph", replace
}
graph combine a.gph b.gph c.gph, rows(1) xsize(20) ysize(7)
graph export boxplot.png, replace
* density plot to show the distributions
foreach var of varlist a b c d {
kdensity `var', scheme(s1mono) xtitle("`var'")
graph save "den_`var'.gph", replace
}
graph combine ///
den_a.gph den_b.gph den_c.gph den_d.gph, ///
rows(2) xsize(20) ysize(18)
graph export density.png, replace
clear
set more off
cap log off
input time rural urban
2005 .77 .94
2006 .73 .93
2008 .63 .80
2009 .57 .81
2010 .53 .74
end
gen area = urban - rural
tw (connected rural time, msymbol(S)) ///
(connected urban time) ///
(area area time, blwidth(*.001)), ///
yscale(range(0 1)) ylabel(0(0.1)1, nogrid format(%7.1f)) ///
xlabel(2005 2006 2008 2009 2010) xticks(2005 2006 2008 2009 2010) ///
plotregion(margin(zero)) scheme(s1color) ///
legend(pos(6) ring(1) rows(1) order(2 1) hol(2 3 4)) ///
xtitle("") title("")
