decision_eval {BACCT} | R Documentation |
Applies a decision rule to a "BAC" class object and provides rule evaluation
decision_eval(object, decision.rule, control.range, es, csv.name = NULL)
object |
An object of class "BAC". |
decision.rule |
A vector of |
control.range |
A vector of control rates at which the decision rule is evaluated. |
es |
A vector of treatment arm effect sizes, compared to control arm. |
csv.name |
If a name is specified, the output data set is exported in CSV format. |
The decision rules specified in c(a,b)
may be in the context
of either interim or final analysis. At the interim, a "go" decision is made
if the criterion in the "BAC" object exceeds b
and a "no go" decision
if such criterion is below a
. Otherwise, the decision falls in the
gray zone.
For the final analysis, the decision rule should satisfy a
=b
.
Significance is claimed if the criterion in the "BAC" object exceeds
a
. Specifying an a
larger than b
will lead to an error.
For interim analysis, specified decision rule is evaluated by the probability of making a correct go or no go decision. For final analysis, power or type-I error is computed.
Negative es
values are allowed if a lower rate is desirable.
An object of class "BACdecision".
Hongtao Zhang
## Not run:
#borrow from 3 historical trials#
yh = c(11,300,52);nh = c(45,877,128)
#specify current trial sample sizes#
n1 = 20;n2 = 30
obj = BAC_binom(yh=yh,nh=nh,n1=n1,n2=n2,n.chain=5,
criterion.type="prob",prob.threshold=0.1,sim.mode="express")
rule = decision_eval(obj,decision.rule=c(0.05,0.15),
control.range=seq(0.3,0.5,0.01),es=c(0,0.1,0.2),csv.name="result.csv")
#S3 method for class "BACdecision"
plot(rule,interim=T)
## End(Not run)