There is a different take on the chapter
here, but I like mine better.
// Open data set
use http://www.ats.ucla.edu/stat/stata/examples/alda/data/tolerance, clear
// Figure 2.1
list, sep(0) noobs
reshape long tol, i(id) j(age)
list if inlist(id, 9, 45, 1653), sepby(id) noobs
// Table 2.1
reshape wide
quietly estpost cor tol*, matrix listwise
esttab, unstack not noobs compress nostar b(%6.2f)
// Figure 2.2
reshape long
twoway (scatter tol age), by(id) ytitle(Tolerance) xtitle(Age) name(Figure22, replace)
// Figure 2.3
twoway (scatter tol age) ///
(lowess tol age) ///
, by(id, note("Graphs by id, lowess curves") legend(off)) ///
ytitle(Tolerance) xtitle(Age) name(Figure23, replace)
// Table 2.2
preserve
tempfile table22
generate time = age - 11
statsby initial = _b[_cons] ///
initial_se = _se[_cons] ///
change = _b[time] ///
change_se = _se[time] ///
residual = (e(rmse)^2) ///
explained = e(r2) ///
, by(id) saving(`table22', replace): regress tol time
drop time
reshape wide
merge 1:1 id using `table22', nogenerate
format initial initial_se change change_se residual explained exposure %6.2f
keep id initial initial_se change change_se residual explained male exposure
order id initial initial_se change change_se residual explained male exposure
list, sep(0) noobs abbrev(15)
tempfile figure28
save `figure28', replace
// Figure 2.4
stem initial, round(.01)
stem change, round(.01)
stem residual, round(.01)
stem explained, round(.01)
restore
// Figure 2.5
twoway (scatter tol age) ///
(lfit tol age) ///
, by(id, note("Graphs by id, OLS curves") legend(off)) ///
ytitle(Tolerance) xtitle(Age) name(Figure25, replace)
// Figure 2.6
xtset id age
xtline tol, overlay t(age) i(id) legend(off) ///
ytitle(Tolerance) ylabel(1 (1) 4) ///
addplot(lowess tol age, lwidth(thick) lpattern(solid)) ///
xtitle(Age) title("Observed data and lowess smoother") ///
xsize(3) name(Figure26A, replace) nodraw
quietly regress tol i.id##c.age
predict tolhat
xtline tolhat, overlay t(age) i(id) legend(off) ///
ytitle(Tolerance) ylabel(1 (1) 4) ///
addplot(lfit tol age, lwidth(thick) lpattern(solid)) ///
xtitle(Age) title("OLS trajectories") ///
xsize(3) name(Figure26B, replace) nodraw
graph combine Figure26A Figure26B, col(2) name(Figure26, replace)
// Table 2.2
preserve
use `table22', clear
tabstat initial change, stat(mean sd) format(%6.2f)
cor initial change
restore
// Figure 2.7
quietly sum exposure, detail
generate highexposure = (exposure >= r(p50))
generate lowexposure = (exposure < r(p50))
generate female = !male
label var male "Males"
label var female "Females"
label var lowexposure "Low exposure"
label var highexposure "High exposure"
foreach z of varlist female male lowexposure highexposure {
capture drop tolhat
quietly regress tol i.id##c.age if `z'
predict tolhat if `z'
xtline tolhat if `z', ///
overlay t(age) i(id) legend(off) ///
ytitle("Predicted tolerance") ylabel(1 (1) 4) ///
addplot(lfit tol age if `z', lwidth(thick) lpattern(solid)) ///
xtitle(Age) title(`: variable label `z'') ///
xsize(3) ysize(2) name(Figure27_`z', replace) nodraw
}
graph combine Figure27_female Figure27_male Figure27_lowexposure Figure27_highexposure, col(2) name(Figure27, replace)
// Figure 2.8
use `figure28', clear
quietly correlate initial male
local pmca = round(r(rho), .01)
quietly correlate initial exposure
local pmcb = round(r(rho), .01)
quietly correlate change male
local pmcc = round(r(rho), .01)
quietly correlate change exposure
local pmcd = round(r(rho), .01)
label define male -1 " " 1 "Male" 0 "Female" 2 " ", modify
label val male male
twoway dot initial male, ///
ytitle("Predicted intercept") ///
xtitle("Gender") ///
xlabel(-1 0 1 2, val) ///
ysize(2) xsize(3) ///
note("{it:r} = `pmca'") ///
name(Figure28A, replace) nodraw
twoway scatter initial exposure, ///
ytitle("Predicted intercept") ///
xtitle("Exposure") ///
ysize(2) xsize(3) ///
note("{it:r} = `pmcb'") ///
name(Figure28B, replace) nodraw
twoway dot change male, ///
ytitle("Predicted change") ///
xtitle("Gender") ///
ysize(2) xsize(3) ///
xlabel(-1 0 1 2, val) ///
note("{it:r} = `pmcc'") ///
name(Figure28C, replace) nodraw
twoway scatter change exposure, ///
ytitle("Predicted change") ///
xtitle("Exposure") ///
ysize(2) xsize(3) ///
note("{it:r} = `pmcd'") ///
name(Figure28D, replace) nodraw
graph combine Figure28A Figure28B Figure28C Figure28D, col(2) row(2) name(Figure28, replace)
Reference
Singer, Judith D., and John B. Willett. 2003.
Applied Longitudinal Data Analysis. Modeling Change and Event Occurrence. Oxford University Press. doi: 10.1093/acprof:oso/9780195152968.001.0001
