/***********************************************************************
***********/
	/**  author       :  G.Eckert
**/
	/**  title        :  Z-Score Macro for comparing means from 2
log-normal samples **/
	/**  program      :  zscore.mac
**/
	/**  date         :  03/06/97
**/
	/**
**/
	/**  Implementation of method used on Biometrics 53, September
1997 'Methods     **/
	/**  for Comparing the Means of Two Independent Log-Normal
Samples' by           **/
	/**  XH Zhou, S Gao, and SL Hui, pp 1129-1135.
**/
	
/***********************************************************************
***********/



	%macro zscore(data, class, response, offset);

	  /* offset variable used to add value to data so log
transformation can be done */
	  %if &OFFSET = %then &OFFSET = 0;

	  data dsn; set &DATA;
	    logdata = log(&RESPONSE + &OFFSET);
	  proc sort data=dsn out=dsn; by &CLASS;
	  proc means n mean var noprint data=dsn;
	    var logdata;
	    output out=zscore (drop=_TYPE_ _FREQ_) n=n mean=mean
var=var;
	      by &CLASS;
	  run;

	  data _NULL_; set zscore;
	    if &CLASS = 0 then do;
	      call symput('n0', n);
	      call symput('mu0', mean);
	      call symput('var0', var);
	      end;
	    else if &CLASS = 1 then do;
	      call symput('n1', n);
	      call symput('mu1', mean);
	      call symput('var1', var);
	      end;
	  run;

	  data zscore; set zscore;
	    if &CLASS = 0 then do;
	      zscore = (&MU1 - &MU0 + 0.5 * (&VAR1 - &VAR0)) /
	      sqrt( &VAR0/&N0 + &VAR1/&N1 + 0.5 * ( &VAR0*&VAR0/(&N0-1)
+ &VAR1*&VAR1/(&N1-1) ) );
	      pvalue = 2 * probnorm( -1 * abs(zscore));
	      variable = "&RESPONSE";
	      end;
	  proc print data=zscore;
	  run;
	%mend zscore;