Description Usage Arguments Details References See Also Examples
This function creates an object of class Test
which can be added to
an object of class AnalysisModel
.
1 |
id |
defines the ID of the Test object. |
method |
defines the method of the Test object. |
samples |
defines a list of samples defined in the data model to be used within the selected Test object method. |
par |
defines the parameter(s) of the selected Test object method. |
Objects of class Test
are used in objects of class
AnalysisModel
to define the statistical test to produce. Several
objects of class Test
can be added to an object of class
AnalysisModel
.
method
argument defines the statistical test method. Several methods
are already implemented in the Mediana package (listed below, along with the
required parameters to define in the par
parameter):
TTest
: perform a two-sample t-test between the two samples defined in
the samples
argument. Optional parameter: larger
(Larger value
is expected in the second sample (TRUE
or FALSE
)). Two samples
must be defined.
TTestNI
: perform a non-inferiority two-sample
t-test between the two samples defined in the samples
argument.
Required parameter: margin
. Optional parameter: larger
(Larger
value is expected in the second sample (TRUE
or FALSE
)).Two
samples must be defined.
WilcoxTest
: perform a
Wilcoxon-Mann-Whitney test between the two samples defined in the
samples
argument. Optional parameter: larger
(Larger value is
expected in the second sample (TRUE
or FALSE
)).Two samples
must be defined.
PropTest
: perform a two-sample test for
proportions between the two samples defined in the samples
argument.
Optional parameter: yates
(Yates' continuity correction TRUE
or FALSE
) and larger
(Larger value is expected in the second
sample (TRUE
or FALSE
)). Two samples must be defined.
PropTestNI
: perform a non-inferiority two-sample test for proportions
between the two samples defined in the samples
argument. Required
parameter: margin
. Optional parameter: yates
(Yates'
continuity correction TRUE
or FALSE
) and larger
(Larger
value is expected in the second sample (TRUE
or FALSE
)). Two
samples must be defined.
FisherTest
: perform a Fisher exact
test between the two samples defined in the samples
argument.
Optional parameter: larger
(Larger value is expected in the second
sample (TRUE
or FALSE
)). Two samples must be defined.
GLMPoissonTest
: perform a Poisson regression test between the two
samples defined in the samples
argument. Optional parameter:
larger
(Larger value is expected in the second sample (TRUE
or
FALSE
)). Two samples must be defined.
GLMNegBinomTest
:
perform a Negative-binomial regression test between the two samples defined
in the samples
argument. Optional parameter: larger
(Larger
value is expected in the second sample (TRUE
or FALSE
)).Two
samples must be defined.
LogrankTest
: perform a Log-rank test
between the two samples defined in the samples
argument. Optional
parameter: larger
(Larger value is expected in the second sample
(TRUE
or FALSE
)). Two samples must be defined.
OrdinalLogisticRegTest
: perform an Ordinal logistic regression test
between the two samples defined in the samples
argument. Optional
parameter: larger
(Larger value is expected in the second sample
(TRUE
or FALSE
)). Two samples must be defined.
It is to be noted that the statistical tests implemented are one-sided and
thus the sample order in the samples argument is important. In particular,
the Mediana package assumes by default that a numerically larger value of
the endpoint is expected in Sample 2 compared to Sample 1. Suppose, for
example, that a higher treatment response indicates a beneficial effect
(e.g., higher improvement rate). In this case Sample 1 should include
control patients whereas Sample 2 should include patients allocated to the
experimental treatment arm. The sample order needs to be reversed if a
beneficial treatment effect is associated with a lower value of the endpoint
(e.g., lower blood pressure), or alternatively (from version 1.0.6), the
optional parameters larger
must be set to FALSE
to indicate
that a larger value is expected on the first Sample.
http://gpaux.github.io/Mediana/
See Also AnalysisModel
.
1 2 3 4 5 | # Analysis model
analysis.model = AnalysisModel() +
Test(id = "Placebo vs treatment",
samples = samples("Placebo", "Treatment"),
method = "TTest")
|
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