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文件名:  DATA.xls
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总是提示where 子句运算符要求兼容的变量，我做的是一个10-fold cross- validation 交叉验证，因变量是字符型，自变量是数字，
  1. %macro xval(dsn=,outcome=,covars=,k=10,sel=stepwise,outdsn=_xval_,outdsn2=comparison);

  3. data _modif;
  4. set &dsn;
  5. unif=&k*ranuni(20052905);
  6. xv=ceil(unif);
  7. run;

  9. %do i=1 %to &k;
  10. proc logistic data=_modif(where=(xv ne &i)) outmodel=_mod&i;
  11. model &outcome (event="1") =&covars / selection=&sel;
  12. ods output association=assoc&i;
  13. run;
  14. %if print^=0 %then %do;proc printto file='junk.txt';%end;
  15. proc logistic inmodel=_mod&i;
  16. score data=_modif(where=(xv=&i)) out=out&i;
  17. run;

  19. ods select none;
  20. ods output KolSmir2Stats=KS&i;
  21. proc npar1way data= out&i edf;
  22. where &outcome^=.;
  23. class &outcome;
  24. varP_1;
  25. run;
  26. ods select all;

  28. ods select none;
  29. ods output WilcoxonScores=Wil&i;
  30. proc npar1way wilcoxon data= out&i;
  31. where &outcome^=.;
  32. class &outcome;
  33. varP_1;
  34. run;
  35. ods select all;

  37. data AUC&i;
  38. set Wil&i end=eof;
  39. retain v1 v2 1;
  40. if _n_=1 then v1=abs(ExpectedSum - SumOfScores);
  41. v2=N*v2;
  42. if eof then do;
  43. d=v1/v2;
  44. /*Gini=d * 2; */
  45. Scoring_AUC= d + 0.5;
  46. put Scoring_AUC=;
  47. put "****Open work.results dataset to see results of training datasets....";
  48. keep Scoring_AUC;
  49. output;
  50. end;
  51. run;

  53. %if print^=0 %then %do;proc printto;run;%end;
  54. %end;
  55. data &outdsn;
  56. set %do j=1 %to &k;out&j %end;;
  57. run;

  59. data training (keep =label2 nvalue2 rename= (nvalue2=Training_AUC));
  60. set %do j=1 %to &k;assoc&j %end;;
  61. where label2= 'c';
  62. if label2='c' then label2 ='AUC';
  63. run;

  65. data ks (keep =label2 nvalue2 rename= (nvalue2=Scoring_KS));
  66. set %do j=1 %to &k;ks&j %end;;
  67. where label2= 'D';
  68. if label2='D' then label2 ='KS';
  69. run;

  71. data validation;
  72. set %do j=1 %to &k;AUC&j %end;;
  73. run;

  75. data &outdsn2 (drop = label2);
  76. merge training validation ks;
  77. run;

  79. ods select none;
  80. ods output WilcoxonScores=WilcoxonScore;
  81. proc npar1way wilcoxon data= &outdsn;
  82. where &outcome^=.;
  83. class &outcome;
  84. varP_1;
  85. run;
  86. ods select all;

  88. data AUC;
  89. set WilcoxonScore end=eof;
  90. retain v1 v2 1;
  91. if _n_=1 then v1=abs(ExpectedSum - SumOfScores);
  92. v2=N*v2;
  93. if eof then do;
  94. d=v1/v2;
  95. Gini=d * 2;
  96. AUC= d + 0.5;
  97. put AUC=GINI=;
  98. put "****Open work.results dataset to see results of training datasets....";
  99. keep AUC Gini;
  100. output;
  101. end;
  102. run;

  104. %mend;

  106. %xval(dsn=data,outcome=var_13,covars= t569 t868 t725 t291 t323,k=10,sel=stepwise, outdsn=kfold, outdsn2=comparison);
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