computeCvPoissonRegression

Obtains critical values for the group and continuous sequential MaxSPRT test with Poisson regression data,
using a Wald type upper boundary, which is flat with respect to the likelihood ratio function,
and with a pre-specified upper limit on the sample size.
It is often not possible to select a critical value that corresponds to the exact alpha specified.
Instead, this function will select the least conservative critical value having an alpha below
the one specified, so the sequential analysis is conservative.

Routines for performing empirical calibration of observational
study estimates. By using a set of negative control hypotheses we can
estimate the empirical null distribution of a particular observational
study setup. This empirical null distribution can be used to compute a
calibrated p-value, which reflects the probability of observing an
estimated effect size when the null hypothesis is true taking both random
and systematic error into account. A similar approach can be used to
calibrate confidence intervals, using both negative and positive controls.
For more details, see Schuemie et al. (2013) <doi:10.1002/sim.5925> and
Schuemie et al. (2018) <doi:10.1073/pnas.1708282114>.

Martijn Schuemie

EmpiricalCalibration

Routines for Performing Empirical Calibration of Observational
Study Estimates

Marc Suchard

computeCvPoissonRegression function

<dl><dt>groupSizes</dt>
<dd>Vector containing the expected number of events under H0 for each test.</dd>
<dt>z</dt>
<dd>The control time divided by the time at risk.</dd>
<dt>minimumEvents</dt>
<dd>The minimum number of events needed before the null hypothesis can be rejected.</dd>
<dt>alpha</dt>
<dd>The significance level, or the type 1 error probability, which is the probability
of rejecting the null hypothesis when it is true.</dd>
<dt>sampleSize</dt>
<dd>Sample size for the Monte-Carlo simulations.</dd></dl>

Arguments

Compute critical values for Poisson regression data — computeCvPoissonRegression

<dl>

<dt>groupSizes</dt>
<dd>Vector containing the expected number of events under H0 for each test.</dd>


<dt>z</dt>
<dd>The control time divided by the time at risk.</dd>


<dt>minimumEvents</dt>
<dd>The minimum number of events needed before the null hypothesis can be rejected.</dd>


<dt>alpha</dt>
<dd>The significance level, or the type 1 error probability, which is the probability
of rejecting the null hypothesis when it is true.</dd>


<dt>sampleSize</dt>
<dd>Sample size for the Monte-Carlo simulations.</dd>

</dl>

computeCvPoissonRegression: Compute critical values for Poisson regression data

Description

Usage

Value

Arguments

Examples