Scores {adoptr} | R Documentation |
In adoptr
scores are used to assess the performance of a design.
This can be done either conditionally on the observed stage-one outcome
or unconditionally.
Consequently, score objects are either of class ConditionalScore
or
UnconditionalScore
.
## S4 method for signature 'Score' show(object) expected(s, data_distribution, prior, ...) ## S4 method for signature 'ConditionalScore' expected(s, data_distribution, prior, ...) evaluate(s, design, ...) ## S4 method for signature 'IntegralScore,TwoStageDesign' evaluate(s, design, optimization = FALSE, subdivisions = 10000L, ...)
object |
object to show |
s |
|
data_distribution |
|
prior |
a |
... |
further optional arguments |
design |
object |
optimization |
logical, if |
subdivisions |
maximal number of subdivisions when evaluating an integral score using adaptive quadrature (optimization = FALSE) |
All scores can be evaluated on a design using the evaluate
method.
Note that evaluate
requires a third argument x1
for
conditional scores (observed stage-one outcome).
Any ConditionalScore
can be converted to a UnconditionalScore
by forming its expected value using expected
.
The returned unconditional score is of class IntegralScore
.
ConditionalPower
, ConditionalSampleSize
,
composite
design <- TwoStageDesign( n1 = 25, c1f = 0, c1e = 2.5, n2 = 50, c2 = 1.96, order = 7L ) prior <- PointMassPrior(.3, 1) # conditional cp <- ConditionalPower(Normal(), prior) expected(cp, Normal(), prior) evaluate(cp, design, x1 = .5) # unconditional power <- Power(Normal(), prior) evaluate(power, design) evaluate(power, design, optimization = TRUE) # use non-adaptive quadrature