/* ragwortD.sas */
option ls=72 ps=60;
data ragwort1;
   input load mass;
   loadsq = load*load;
   logmass = log(mass);
   logload = log(load);
   logldsq = logload*logload;
cards;
12.2 18.200
14.6 17.500
15.8  7.220
25.3 30.600
38.6  6.660
76.4  6.140
163   5.210
182    .502 
377    .011 
415    .611 
446    .630 
628    .427 
770    .012 
1012   .002 
1446   .006 
;   
proc print data=ragwort1;
title 'ragwort data';
proc plot data=ragwort1;
   plot mass*load;
   title 'plot of mass versus load';
proc plot data=ragwort1;
   plot logmass*load;
   title 'plot of log(mass) versus load';
proc plot data=ragwort1;
   plot logmass*logload;
   title 'plot of log(mass) versus log(load)';
/* add points for plotting fitted curves */
data addon1;
   input load mass;
   loadsq = load*load;
   logmass = log(mass);
   logload = log(load);
   logldsq = logload*logload;
cards;  
13 .
15 .
20 .
30 .
50 .
60 .
80 .
100 .
150 .
200 .
350 .
420 .
500 .
550 .
670 .
720 .
800 .
900 .
950 .
1050 .
1250 .
1350 .
1390 .
;
proc print data=addon1;
   var load logload;
title 'additional values for plotting fitted curves';
data ragwort;
   set ragwort1 addon1;
/* quadratic regression of mass on load */
proc glm data=ragwort;
   model mass = load loadsq /ss1 ss2;
      output out=new1 predicted=yhat residual=resid lcl=clpl
             ucl=clpu lclm=clml uclm=clmu;
title 'quadratic regression of mass on load';
proc print data=new1;
   var load mass clml clmu clpl clpu yhat resid;
data new1b;
   set new1;
   code = '*';
   if mass = . then code = '+';
   newy = mass;
   if mass = . then newy = yhat;
proc plot data=new1b;
   plot newy*load = code;   
proc plot data=new1;
   plot resid*load / vref=0;
proc rank data=new1 normal=blom out=new1a;
   var resid;
   ranks nscore;
proc plot data=new1a;
   plot nscore*resid;
proc univariate data=new1 plot normal;
   var resid;
/* quadratic regression of log(mass) on load */
proc glm data=ragwort;
   model logmass = load loadsq / ss1 ss2;
      output out=new2 predicted=yhat residual=resid lcl=clpl
             ucl=clpu lclm=clml uclm=clmu;
title 'quadratic regression of log(mass) on load';
proc print data=new2;
   var load mass clml clmu clpl clpu yhat resid;
data new2b;
   set new2;
   code = '*';
   if logmass = . then code = '+';
   newy = logmass;
   if logmass = . then newy = yhat;
proc plot data=new2b;
   plot newy*load = code;   
proc plot data=new2;
   plot resid*load / vref=0;
proc rank data=new2 normal=blom out=new2a;
   var resid;
   ranks nscore;
proc plot data=new2a;
   plot nscore*resid;
proc univariate data=new2 plot normal;
   var resid;
/*  quadratic regression of log(mass) on log(load) */ 
proc glm data=ragwort;
   model logmass = logload logldsq / ss1 ss2;
      output out=new3 predicted=yhat residual=resid lcl=clpl
             ucl=clpu lclm=clml uclm=clmu;
title 'quadratic regression of log(mass) on log(load)';
proc print data=new3;
   var load mass clml clmu clpl clpu yhat resid;
data new3b;
   set new3;
   code = '*';
   if logmass = . then code = '+';
   newy = logmass;
   if logmass = . then newy = yhat;
proc plot data=new3b;
   plot newy*logload = code;   
proc plot data=new3;
   plot resid*logload / vref=0;
proc rank data=new3 normal=blom out=new3a;
   var resid;
   ranks nscore;
proc plot data=new3a;
   plot nscore*resid;
proc univariate data=new3 plot normal;
   var resid;
run;