# leading question re gun permit example
# success = favor
# neutral versus leading
favor <- c(463,403)
size <- c(615,585)
prop.test(favor,size,correct=0)
prop.test(favor,size,correct=1)
# HIV vaccine trial
# success = HIV positive
# control versus vaccine
hivpositive <- c(126,241)
size <- c(1691,3598)
prop.test(hivpositive,size,correct=0)
prop.test(hivpositive,size,correct=1)
# West of Scotland coronary prevention study
# Initial 5 year study period
# success = has coronary event
# pravastatin versus placebo
coronaryevent <- c(174,248)
size <- c(3302,3293)
prop.test(coronaryevent,size,correct=0)
prop.test(coronaryevent,size,correct=1)
# West of Scotland coronary prevention study
# 5 years plus 10 year followup study
# success = has coronary event
# pravastatin versus placebo
coronaryevent <- c(390,509)
size <- c(3302,3293)
prop.test(coronaryevent,size,correct=0)
prop.test(coronaryevent,size,correct=1)


--------------- results -----------------------

>
> # leading question re gun permit example
> # success = favor
> # neutral versus leading
> favor <- c(463,403)
> size <- c(615,585)
> prop.test(favor,size,correct=0)

	2-sample test for equality of proportions without
	continuity correction

data:  favor out of size
X-squared = 6.1055, df = 1, p-value = 0.01348
alternative hypothesis: two.sided
95 percent confidence interval:
 0.01326543 0.11464785
sample estimates:
   prop 1    prop 2
0.7528455 0.6888889

> prop.test(favor,size,correct=1)

	2-sample test for equality of proportions with
	continuity correction

data:  favor out of size
X-squared = 5.7912, df = 1, p-value = 0.01611
alternative hypothesis: two.sided
95 percent confidence interval:
 0.01159773 0.11631555
sample estimates:
   prop 1    prop 2
0.7528455 0.6888889

> # HIV vaccine trial
> # success = HIV positive
> # control versus vaccine
> hivpositive <- c(126,241)
> size <- c(1691,3598)
> prop.test(hivpositive,size,correct=0)

	2-sample test for equality of proportions without
	continuity correction

data:  hivpositive out of size
X-squared = 1.0102, df = 1, p-value = 0.3149
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.00741547  0.02247640
sample estimates:
    prop 1     prop 2
0.07451212 0.06698166

> prop.test(hivpositive,size,correct=1)

	2-sample test for equality of proportions with
	continuity correction

data:  hivpositive out of size
X-squared = 0.897, df = 1, p-value = 0.3436
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.007850119  0.022911052
sample estimates:
    prop 1     prop 2
0.07451212 0.06698166

> # West of Scotland coronary prevention study
> # Initial 5 year study period
> # success = has coronary event
> # pravastatin versus placebo
> coronaryevent <- c(174,248)
> size <- c(3302,3293)
> prop.test(coronaryevent,size,correct=0)

	2-sample test for equality of proportions without
	continuity correction

data:  coronaryevent out of size
X-squared = 14.08, df = 1, p-value = 0.0001752
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.03441898 -0.01081288
sample estimates:
    prop 1     prop 2
0.05269534 0.07531127

> prop.test(coronaryevent,size,correct=1)

	2-sample test for equality of proportions with
	continuity correction

data:  coronaryevent out of size
X-squared = 13.705, df = 1, p-value = 0.0002139
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.03472224 -0.01050962
sample estimates:
    prop 1     prop 2
0.05269534 0.07531127

> # West of Scotland coronary prevention study
> # 5 years plus 10 year followup study
> # success = has coronary event
> # pravastatin versus placebo
> coronaryevent <- c(390,509)
> size <- c(3302,3293)
> prop.test(coronaryevent,size,correct=0)

	2-sample test for equality of proportions without
	continuity correction

data:  coronaryevent out of size
X-squared = 18.6161, df = 1, p-value = 1.599e-05
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.05300154 -0.01991859
sample estimates:
   prop 1    prop 2
0.1181102 0.1545703

> prop.test(coronaryevent,size,correct=1)

	2-sample test for equality of proportions with
	continuity correction

data:  coronaryevent out of size
X-squared = 18.3077, df = 1, p-value = 1.879e-05
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.05330480 -0.01961533
sample estimates:
   prop 1    prop 2
0.1181102 0.1545703

>