c	
c	trace data  model #1
c
	COMMON /FUN/ pr(9),ob(9)
c	number of predicted and observed data points for each subject
	real d(9,2)
c	num of observations per subject, number of data sets (subjects)
	external funk,pp
	call sas('trace1.dat','tdm1.lst','tdm1.fit')
c	data and model names
	write(7,"(' *** tracedat model 1: FLMP ***')")
	read(9,"(f4.2)")d
	call runstp(funk,6,9,2,d,ob,pr,pp)
c	number of parameters, number of data points, number of data sets
	stop
	end
	SUBROUTINE FUNK
	COMMON /STEP/ NV,NTRACE,MATRIX,CHISQ,MASK(100),X(100)
	COMMON /FUN/ pr(9),ob(9)
c              g w
	real d(3,3)
c	labeling factorial design
	equivalence (pr,d)
	integer g,w
	real xg(3),xw(3)
c	3 levels of g and 3 levels of w
	equivalence (x(1),xg),(x(4),xw)
c	this instruction defines the free parameters: 1-3 for g and 4-6 for w
c
c	what follows is model
	do 60 g=1,3
	do 60 w=1,3
	   t=xg(g)*xw(w)
	   tn=(1.-xg(g))*(1.-xw(w))
60	   d(g,w)=t/(t+tn)
c	  compute sum of squared deviations between observed and predicted values (9 of them here)
	call cchi(ob,pr,9)
	RETURN
	entry pp(is,rmsd)
c            write out rmsd and parameters
	write(7,117)is,rmsd,xg,xw
117	format(/' Sub  'i2' rmsd= 'f7.4,/' g  = '3f7.4/,
&	' w  = '3f7.4/)
	return
	end