window push version 8.0
window push set more on
window push log using 3.11.1.Framingham.log, replace
window push * 3.11.1.Framingham.log
window push *
window push *  Plot a scatterplot matrix of log(sbp), log(bmi), age and log(scl) for
window push *  women from the Framingham Heart Study who were recruited in January.
window push *
window push use 2.20.Framingham.dta
window push generate logsbp = log(sbp)
window push label variable logsbp "Log Systolic Blood Pressure"
window push generate logbmi = log(bmi)
window push label variable logbmi "Log Body Mass Index"
window push generate logscl = log(scl)
window push label variable logscl "Log Serum Cholesterol"
window push set textsize 120
window push graph matrix logsbp logbmi age logscl if month==1 & sex==2, msymbol(Oh) ///
window push    mcolor(gs10) 
window push more
window push *
window push *  Use multiple regression models to analyze the effects of log(sbp),
window push *  log(bmi), age and log(scl) on log(sbp)
window push *
window push generate woman = sex - 1
window push generate wo_lbmi = woman * logbmi
window push generate wo_age  = woman * age
window push generate wo_lscl = woman * logscl
window push regress logsbp logbmi age logscl woman  wo_lbmi wo_age wo_lscl
window push regress logsbp logbmi age logscl woman  wo_lbmi wo_age 
window push regress logsbp logbmi age logscl woman  wo_age 
window push *
window push * Calculate 95% confidence and prediction intervals for a 60 year-old 
window push * woman with a SCL of 400 and a BMI of 40.
window push *
window push edit
window push set obs 4700
window push replace scl = 400 in 4700
window push replace age = 60 in 4700
window push replace bmi = 40 in 4700
window push replace woman = 1 in 4700
window push replace id = 9999 in 4700
window push replace logbmi = log(bmi) if id == 9999	
window push replace logscl = log(scl) if id == 9999
window push replace wo_age = woman*age if id == 9999
window push predict yhat,xb	
window push predict h, leverage
window push predict std_yhat, stdp	
window push predict std_f, stdf	
window push generate cil_yhat = yhat - invttail(4658-5-1,.025)*std_yhat	
window push generate ciu_yhat = yhat + invttail(4658-5-1,.025)*std_yhat	
window push generate cil_f = yhat - invttail(4658-5-1,.025)*std_f	
window push generate ciu_f = yhat + invttail(4658-5-1,.025)*std_f
window push generate cil_sbpf = exp(cil_f)	
window push generate ciu_sbpf = exp(ciu_f)
window push list bmi age scl woman logbmi logscl yhat h std_yhat std_f cil_yhat 	///
window push     ciu_yhat cil_f ciu_f cil_sbpf ciu_sbpf if id==9999
window push display invttail(4652,.025)	
window push *
window push * Repeat the preceding analysis using an automatic forward
window push * selection algorithm
window push *
window push drop if id == 9999
window push sw regress logsbp logbmi age logscl woman wo_lbmi wo_age wo_lscl, forward pe(.1)
window push *
window push *  Draw a scatterplot of studentized residuals against the estimated expected
window push *  value of logsbp together with the corresponding lowess regression curve.
window push *
window push predict t, rstudent
window push lowess t yhat,  bwidth(0.2) msymbol(Oh) mcolor(gs10) clwidth(thick)	/// 	
window push     ylabel(-3(1)5) yline(-1.96 0 1.96) xlabel(4.7(.1)5.1)
window push more
window push generate out = t > 1.96 | t < -1.96
window push tabulate out
window push *
window push *  Perform an influence analysis on patients 2000 through 2050
window push *
window push keep if id >= 2000 & id <= 2050
window push regress logsbp logbmi age logscl woman wo_age
window push drop  t h
window push predict h, leverage
window push predict z, rstandard
window push predict t, rstudent
window push predict deltab1, dfbeta(logbmi)
window push predict cook, cooksd
window push display invttail(43,.025)
window push label variable deltab1 "Delta Beta for log[BMI]"
window push scatter deltab1 t, msymbol(Oh) ylabel(-1.5(.5)0, angle(0)) yline(0) 	///
window push    xlabel(-2(1)4) xtick(-2.5(.5)4.5) xline(-2 2)
window push sort t
window push list id h z t deltab1 cook in  -3/-1
window push regress logsbp logbmi  age logscl woman wo_age if id ~=2049
window push display (  .1659182 - .3675337 )/.1489199 
window push log close