Version 0.2.7
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Bugfixes:
* LogisticNormal now works again - "prec" was not found before.
Version 0.2.6
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Bugfixes:
* Replaced BayesLogit dependency by JAGS code, since BayesLogit was taken off CRAN.
* Speed up one example to pass CRAN check.
Version 0.2.5
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New features:
* matching of doses with the dose grid now includes a tolerance of 1e-10, in order
to make it more user-friendly (thanks to YJ Choi and Giuseppe for investigating)
Bugfixes:
* documentation:
- minor fix for alpha1 description in LogisticLogNormal-class
* minor fix on scale_colour_manual import from ggplot2 reported by R-Core
Version 0.2.4
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New features:
* In case of multiple nextBest plots these are now also returned as original plots
in the list singlePlots, to allow for further customization, before jointly plotting them.
* ProbitLogNormal: Now also this model allows for a reference dose and a log transformation
of the (standardized) dose. This can be specified with options refDose and useLogDose.
* DualEndpoint: Same additional options as for ProbitLogNormal are now available for the
DualEndpoint models. As a consequence, the parameter "refDose" for class
DualEndpointBeta needed to be renamed to "refDoseBeta", and the parameter "refDose" for
class DualEndpointEmax renamed to "refDoseEmax".
Bugfixes:
* documentation: in the DualEndpoint description fixed the \left problem in the
formula
Version 0.2.3
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New features:
* New increment class "IncrementMin" has been added which allows to combine multiple
increment rules with the MIN operation
Version 0.2.1
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New features:
* Option targetThresh for NextBestDualEndpoint allows to tune from which target probability
onwards it will be used to derive the next best dose (before this was fixed to 0.05)
* Added ProbitLogNormal model
* In the NextBestDualEndpoint class, the additional option "scale" now allows to also
specify absolute biomarker target ranges. In the corresponding method evaluation,
the safety samples are now no longer included in the evaluation of the biomarker
target probability, such that now the description is consistent with the computations.
* NextBestNCRM and NextBestDualEndpoint now return the matrix of target and overdosing
probabilities as additional list element "probs" in the result of "nextBest" applied.
* Note that in the StoppingTargetBiomarker evaluation, the toxicity is no longer
a part of the biomarker target probability.
Bugfixes:
* Added back the example vignette, so that it can be opened with crmPackExample()
* Clarified that for the DualEndpointRW model samples from the prior cannot be
obtained due to impropriety of the RW prior (added to model class description).
* For DualEndpointRW models, it is now possible to have non-equidistant grid points,
and obtain sensible results. (But still needs to be thouroughly tested though.)
* For DualEndpointBeta model, it is now possible to have negative E0 and Emax parameters.
* Cohort size of 0 for placebo is now possible - e.g. to only start with patients and
then later move to larger cohorts also including placebo subjects.
* When simulating with firstSeparate=TRUE and placebo, now the first (sentinel) cohort
includes one active and one placebo patients, and the next patients use the cohort
size for the active and placebo arms, respectively.
* Barplots work now also when there was only one observed value in all simulations
* NextBestDualEndpoint now only takes into account active doses when optimizing the biomarker
outcome for the next best dose among admissible doses, thus avoiding early stopping
at the placebo dose level.
* If DataMixture objects are used, mcmc now correctly sets fromPrior to FALSE if
the shared data object contains any data.
Version 0.2.0
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* Added arguments probmin and probmax to MinimalInformative in order to control
the probability threshold at the minimum and maximum dose for the minimally
informative prior
* Values of 95% CI and the corresponding ratio of the upper to the lower limit of this CI
are displayed in results when using 'nextBest'
* The six- number summary tables including the values of the lowest, 25th percentile,
50th percentile or the median, the mean, the 75th precentile and the highest of the
final (at stopping) estimates of the
1) dose levels corresponds to the target probability of DLE used at the end of a trial, TDEOT
2) ratios of the upper to the lower 95% credibility intervals (CI) of TDEOT
3) dose levels corresponds to the target probability of DLE used during a trial
4) dose levels corresponds to the maximum gain value, Gstar
5) ratios of the upper to the lower 95% CI of the final estimates of Gstar
6) optimal doses, either the TDEOT (for DLE response only) or the minimum of TDEOT and Gstar
(for DLE and efficacy response)
7) ratios of the optimal dose
across all simulations will also be displayed when using 'summary' for simulations.
Version 0.1.8
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* The value of the 95% CI of the final estimates
will be displayed in results when using 'stopTrial'
* Bugfixes for dual endpoint designs:
- Improved graphical display in plots for nextBest dose
- Improved methodology to compute Gstar
- Warnings are removed when using nextBest in simulations
- Stopping rules can now also be freely combined using the and/or operators
with the dual endpoint design stopping rules not using MCMC samples.
Version 0.1.6
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* New model class "LogisticLogNormalMixture" has been added, for use with the
new data class "DataMixture".
* New stopping rule "StoppingHighestDose" has been added.
* The "examine" method no longer stops when two consecutive cohorts start with
the same dose. This is important e.g. for the two-parts study designs, where
part 1 can end with the same dose as part 2 starts.
* The contents of the "datanames" slot of new models are no longer restricted to
a specific set, which was previously enforced by the validation function of
the GeneralModel and AllModels classes.
* Sampling from the prior can now be enabled/disabled by the user for the
mcmc function, which is necessary for models where it might not be from the
prior even though nObs == 0.
* Bugfix: The results from the MinimalInformative function were not reproducible
beforehand. Now a seed parameter can be supplied, which ensures
reproducibility.
* Bugfix: Compatibility of help file links with new ggplot2 package version.
Version 0.1.5
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* Bugfix: In newer versions of grid the plotting of simulation objects did no
longer work. This was fixed.
Version 0.1.2
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* Bugfix: The MinimalInformative function previously produced too uninformative
prior quantiles, which were not fulfilling the requirements in the function's
documentation. With this bugfix, the correct (as per the Neuenschwander et al
(2008) publication) prior quantiles are specified and then approximated with
logistic (log) normal priors.
Version 0.1.1
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* Bugfix: Previously, it could happen with NextBestNCRM rule, that higher doses
lead to decreasing probability of overdosing, only because for some doses
there was numerically probability 1 of having a DLT. With this bugfix, it was
clarified in the rules documentation and fixed in the rule method, that the
right limit of the overdose interval vector will be inclusive.
Version 0.1.0
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* Added examine function to generate a table of hypothetical trial courses
for model-based and rule-based DLT-endpoint designs
* Made results from mcmc() (works with the usual set.seed in earlier user code)
and simulate() (as previously already promised) reproducible. See help file
for mcmc for more details. Additional improvements to reduce confusing warning
messages / notes from mcmc() and higher-level functions.
* Made simulate with parallel=TRUE work on r.roche.com (Linux server),
using the same parallelization method as for laptops (Windows)
* Passing an empty (zero length) vector as the doselimit parameter of the
nextBest function is now considered as requesting a dose recommendation
without a strict dose limit, and a corresponding warning is printed.
* Introduced GeneralModel class, from which then the class Model for single
agent dose escalation derives. Another branch will be the ComboLogistic model
for multiple agent combinations (in a future version). Similarly introduced
GeneralData class, from which the class Data for single agent derives,
separately from that will be the subclass DataCombo (in a future version).
Version 0.0.23
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* Fixed bug in mcmc function which led to error
"all data elements must have as many rows as the sample size was" and slightly
changed JAGS way of handling burnin / thinning (which should not have a user
impact).
* Reduced number of MCMC samples for dual-endpoint example in vignette to be
able to plot the vignette
Version 0.0.22
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* simulate function has been fixed (specification of arguments)
* Dual-endpoint model-based design has been added.
* 3+3 design simulation is now possible, see ?ThreePlusThreeDesign
* Welcome message on attaching crmPack, i.e. when library("crmPack") is
run
* crmPackUpgrade() function for easy upgrade of crmPack to the latest version
* Rule-based designs now can be specified with the class RuleDesign, while the
model-based designs stay with the class Design. An even more special class is
the DualDesign class, for dual-endpoint model-based designs. Corresponding
classes GeneralSimulations, Simulations and DualSimulations capture the output
of the trial simulations for rule-based, model-based and dual-endpoint
designs.
* The class Simulations-summary has been renamed to SimulationsSummary,
similarly for the classes GeneralSimulationsSummary and
DualSimulationsSummary.
* All Stopping and CohortSize rules that are based on intervals
(IncrementsRelative, IncrementsRelativeDLT, CohortSizeRange, CohortSizeDLT)
now use a different intervals definition. Now the "intervals" slots only contain
the left bounds of the intervals. Before, the last element needed to be
infinity. See the vignette for examples.
* StoppingMaxPatients class has been removed, as it was redundant with the class
StoppingMinPatients. Please just use the StoppingMinPatients class instead.
* Initialization methods have been replaced by dedicated initialization
functions. Please now use these Class(...) functions instead of new("Class",
...) calls to obtain the correct objects. This change is also reflected in the
vignette.
* The extract function for extracting parameter samples from Samples objects has
been removed (due to a name conflict with ggmcmc dependency packages). Please
now use instead the "get" method for Samples objects (see the vignette for an
example) to obtain data in the ggmcmc format.
* crmPack now needs the package httr (it's now in the "Imports" field). Packages
Rcpp and RcppArmadillo have been moved from "Depends" to "Suggests" packages.
Currently we are not using them at all.
* showLegend argument for model fit plotting functions, in order to show the
legend or not.
Version 0.0.21
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no NEWS until this version