CA1	as.vector	c	cbind	diag	exp	library	matrix	mvrnorm	rbinom	return	rnorm	set.seed
CA2	Mu	Sigma	t
CA2a	be	c	Mu	psi	sum	X.M
CA3a	~	==	boxplot	c	mean	mu0	mu1	par	points	Y	Z
CA3b	~	cbind	coef	lm	round	summary	true.vals
CA3c	c	data.frame	fit0	mean	predict	X1	X2
CA3d	c	fit0	predict	sum	Z
CA4	~	c	coef	data.frame	lm	mean	predict	round	summary	X1	X2
CA5	~	c	data.frame	lm	mean	predict	X1
CA6a	box	c	hist	par	ps.true	seq
CA6b	as.numeric	cut	ps.true	quantile	seq	table	Z
CA6c	&	[<-	==	for	matrix	mean	nstrata	ps.strat.true	Y	Z
CA6d	apply	mean	mu.strat.true
CA7a	~	binomial	fitted	glm
CA7b	&	[<-	==	apply	as.numeric	cut	for	matrix	mean	nstrata	ps.fit.c	quantile	seq	table	Y	Z
CA7c	&	[<-	~	==	apply	as.numeric	binomial	cut	fitted	for	glm	matrix	mean	nstrata	quantile	seq	table	Y	Z
CA8a	$	aggregate	c	list	matrix	mean	nstrata	ps.strat.fit.c	X1	X2	X3	Z
CA8b	$	aggregate	c	list	matrix	mean	nstrata	ps.strat.fit.i	X1	X2	X3	Z
CA9a	library	Match	ps.true	summary	Y	Z
CA9b	Match	ps.true	summary	Y	Z
CA10	~	lm	summary
CA11	~	c	coef	data.frame	lm	mean	predict	ps.fit.c	round	summary	X1	X2
CA12	~	c	coef	data.frame	lm	mean	predict	round	summary	X1	X2
CA13	~	c	coef	data.frame	lm	mean	predict	ps.fit.c	round	summary	X1	X2
CA14	c	cbind	coef	fit.psr.3	psi	round	summary
CA14a	c	ps.fit.c	sum	Y	Z
CA14b	c	mean	w0	w1	Y
CA14c	~	coef	lm	round	summary	w0	w1
CA15a	be	c	mean	psi	sum	w0	W0	w1	W1	Xb	Xp	Y
CA15b	~	c	data.frame	lm	mean	predict	sum	w0	W0	w1	W1	X1	X2	Y
CA15c	~	c	data.frame	lm	mean	predict	sum	w0	W0	w1	W1	X1	X2	Y
CA15d	~	c	data.frame	lm	mean	predict	ps.fit.i	sum	X1	X2	Y	Z
CA16	~	c	coef	data.frame	lm	mean	predict	ps.fit.c	round	summary	X1	X2
CA17	~	coef	data.frame	drgee	formula	library	round	summary	X1	X2	Y	Z
CA18	$	~	drgee	formula	mydata
CA19	alpha.hat	beta.hat	c	cbind	exp	mean	psi.hat	psi.prime.hat	X1	X2
CA20	~	alpha.hat	beta.hat	binomial	cbind	coef	diag	fitted	glm	lm	psi.hat	psi.prime.hat	solve	t	X1	X2	Y	Z