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| ^.*\.Rproj$ | ||
| ^\.Rproj\.user$ | ||
| vignette\surrosurv.Rnw | ||
| vignette\surrosurv.bbl | ||
| vignette\surrosurv.log | ||
| vignette\surrosurv.syntex.gz | ||
| ^\.travis\.yml$ | ||
| ^.*\.Rproj$ | ||
| ^\.Rproj\.user$ | ||
| vignette\surrosurv.Rnw | ||
| vignette\surrosurv.bbl | ||
| vignette\surrosurv.log | ||
| vignette\surrosurv.syntex.gz | ||
| ^\.travis\.yml$ |
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| ^.*\.Rproj$ | ||
| ^\.Rproj\.user$ | ||
| vignette\surrosurv.Rnw | ||
| vignette\surrosurv.bbl | ||
| vignette\surrosurv.log | ||
| ^.*\.Rproj$ | ||
| ^\.Rproj\.user$ | ||
| vignette\surrosurv.Rnw | ||
| vignette\surrosurv.bbl | ||
| vignette\surrosurv.log | ||
| vignette\surrosurv.syntex.gz |
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| Package: surrosurv | ||
| Type: Package | ||
| Title: Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data | ||
| Meta-Analyses | ||
| Version: 1.1.16 | ||
| Date: 2017-05-06 | ||
| Authors@R: c( | ||
| person("Federico", "Rotolo", email="[email protected]", | ||
| role=c("aut", "cre")), | ||
| person("Xavier", "Paoletti", role="ctr"), | ||
| person("Marc", "Buyse", role="ctr"), | ||
| person("Tomasz", "Burzykowski", role="ctr"), | ||
| person("Stefan", "Michiels", role="ctr")) | ||
| Author: Federico Rotolo [aut, cre], | ||
| Xavier Paoletti [ctr], Marc Buyse [ctr], Tomasz Burzykowski [ctr], Stefan Michiels [ctr] | ||
| Maintainer: Federico Rotolo <[email protected]> | ||
| Description: Provides functions for the evaluation of | ||
| surrogate endpoints when both the surrogate and the true endpoint are failure | ||
| time variables. The approaches implemented are: (1) the two-step approach | ||
| (Burzykowski et al, 2001) <DOI:10.1111/1467-9876.00244> with a copula model (Clayton, Plackett, Hougaard) at | ||
| the first step and either a linear regression of log-hazard ratios at the second | ||
| step (either adjusted or not for measurement error); (2) mixed proportional | ||
| hazard models estimated via mixed Poisson GLM. | ||
| Depends: R (>= 2.10), stats, optimx, grDevices | ||
| Imports: | ||
| copula, | ||
| eha, | ||
| lme4, | ||
| MASS, | ||
| Matrix, | ||
| msm, | ||
| mvmeta, | ||
| optextras, | ||
| parallel, | ||
| parfm, | ||
| survival, | ||
| SurvCorr | ||
| License: GPL-2 | ||
| VignetteBuilder: R.rsp | ||
| Suggests: R.rsp | ||
| Package: surrosurv | ||
| Type: Package | ||
| Title: Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data | ||
| Meta-Analyses | ||
| Version: 1.1.16 | ||
| Date: 2017-05-06 | ||
| Authors@R: c( | ||
| person("Federico", "Rotolo", email="[email protected]", | ||
| role=c("aut", "cre")), | ||
| person("Xavier", "Paoletti", role="ctr"), | ||
| person("Marc", "Buyse", role="ctr"), | ||
| person("Tomasz", "Burzykowski", role="ctr"), | ||
| person("Stefan", "Michiels", role="ctr")) | ||
| Author: Federico Rotolo [aut, cre], | ||
| Xavier Paoletti [ctr], Marc Buyse [ctr], Tomasz Burzykowski [ctr], Stefan Michiels [ctr] | ||
| Maintainer: Federico Rotolo <[email protected]> | ||
| Description: Provides functions for the evaluation of | ||
| surrogate endpoints when both the surrogate and the true endpoint are failure | ||
| time variables. The approaches implemented are: (1) the two-step approach | ||
| (Burzykowski et al, 2001) <DOI:10.1111/1467-9876.00244> with a copula model (Clayton, Plackett, Hougaard) at | ||
| the first step and either a linear regression of log-hazard ratios at the second | ||
| step (either adjusted or not for measurement error); (2) mixed proportional | ||
| hazard models estimated via mixed Poisson GLM. | ||
| Depends: R (>= 2.10), stats, optimx, grDevices | ||
| Imports: | ||
| copula, | ||
| eha, | ||
| lme4, | ||
| MASS, | ||
| Matrix, | ||
| msm, | ||
| mvmeta, | ||
| optextras, | ||
| parallel, | ||
| parfm, | ||
| survival, | ||
| SurvCorr | ||
| License: GPL-2 | ||
| VignetteBuilder: R.rsp | ||
| Suggests: R.rsp | ||
| Encoding: UTF-8 |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,53 +1,53 @@ | ||
| import(eha, lme4, msm, mvmeta, optextras, optimx, parallel, stats, survival) | ||
| importFrom(copula, | ||
| tau, claytonCopula, gumbelCopula, plackettCopula) | ||
| importFrom(graphics, | ||
| curve, mtext, points, polygon, text) | ||
| importFrom(grDevices, | ||
| palette) | ||
| importFrom(MASS, | ||
| mvrnorm) | ||
| importFrom(Matrix, | ||
| nearPD) | ||
| importFrom(msm, | ||
| deltamethod, rtnorm) | ||
| importFrom(SurvCorr, | ||
| survcorr) | ||
| importFrom(parfm, | ||
| parfm) | ||
| importFrom(graphics, | ||
| abline, axis, axTicks, par, plot, segments) | ||
| importFrom(grDevices, | ||
| n2mfrow, rgb) | ||
| importFrom(utils, | ||
| head) | ||
| export(convals, | ||
| convergence, | ||
| loocv, | ||
| plotsson, | ||
| poissonize, | ||
| simData.mx, | ||
| simData.cc, | ||
| simData.re, | ||
| ste, | ||
| surrosurv) | ||
| S3method(print, conv) | ||
| S3method(loocv, data.frame) | ||
| S3method(confint, surrosurv) | ||
| S3method(loocv, surrosurv) | ||
| S3method(predict, surrosurv) | ||
| S3method(print, surrosurv) | ||
| S3method(plot, surrosurv) | ||
| S3method(print, steSurrosurv) | ||
| S3method(print, predictSurrosurv) | ||
| S3method(plot, predictSurrosurv) | ||
| S3method(print, loocvSurrosurv) | ||
| S3method(plot, loocvSurrosurv) | ||
| import(eha, lme4, msm, mvmeta, optextras, optimx, parallel, stats, survival) | ||
| importFrom(copula, | ||
| tau, claytonCopula, gumbelCopula, plackettCopula) | ||
| importFrom(graphics, | ||
| curve, mtext, points, polygon, text) | ||
| importFrom(grDevices, | ||
| palette) | ||
| importFrom(MASS, | ||
| mvrnorm) | ||
| importFrom(Matrix, | ||
| nearPD) | ||
| importFrom(msm, | ||
| deltamethod, rtnorm) | ||
| importFrom(SurvCorr, | ||
| survcorr) | ||
| importFrom(parfm, | ||
| parfm) | ||
| importFrom(graphics, | ||
| abline, axis, axTicks, par, plot, segments) | ||
| importFrom(grDevices, | ||
| n2mfrow, rgb) | ||
| importFrom(utils, | ||
| head) | ||
| export(convals, | ||
| convergence, | ||
| loocv, | ||
| plotsson, | ||
| poissonize, | ||
| simData.mx, | ||
| simData.cc, | ||
| simData.re, | ||
| ste, | ||
| surrosurv) | ||
|
|
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| S3method(print, conv) | ||
|
|
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| S3method(loocv, data.frame) | ||
|
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| S3method(confint, surrosurv) | ||
| S3method(loocv, surrosurv) | ||
| S3method(predict, surrosurv) | ||
| S3method(print, surrosurv) | ||
| S3method(plot, surrosurv) | ||
|
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| S3method(print, steSurrosurv) | ||
|
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| S3method(print, predictSurrosurv) | ||
| S3method(plot, predictSurrosurv) | ||
|
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| S3method(print, loocvSurrosurv) | ||
| S3method(plot, loocvSurrosurv) | ||
|
|
||
| S3method(print, ciSurrosurv) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,60 +1,60 @@ | ||
| Changes in version 1.1.15 (2017-04-25) | ||
| - fixed minor issue in prediction function for adjusted copula models | ||
| Changes in version 1.1.14 (2017-04-06) | ||
| - fixed issue in prediction intervals for mixed Poisson models | ||
| Changes in version 1.1.13 (2017-03-28) | ||
| - fixed issue in prediction intervals for adjusted copula models | ||
| Changes in version 1.1.12 (2017-03-02) | ||
| - loocv() now also returns the values of kTau and R2 | ||
| estimated in each (N-1) fold | ||
| Changes in version 1.1.10 (2017-02-27) | ||
| - fixed issues with loocv when few trials (added controls) | ||
| - added data 'gastadj' | ||
| - added twoStage parameter to surrosurv for Shih and Louis (1995) approach | ||
| to copula estimation | ||
| Changes in version 1.1.4 (2016-12-06) | ||
| - added paper manuscript as vignette('surrosurv') | ||
| Changes in version 1.1 (2016-11-09) | ||
| - Poisson models can be fitted each separately | ||
| ################################################################################ | ||
| Changes in version 0.1.1 (2016-09-28) | ||
| - fixed examples for poissonize() | ||
| Changes in version 0.1.0 (First Complete version, 2016-09-27) | ||
| - new function loocv() (with print() and plot() functions) | ||
| to compute leave-one-out cross-validation | ||
| ################################################################################ | ||
| Changes in version 0.0.15 (2016-09-23) | ||
| - new function ste() to compute the surrogate threshold effect | ||
| - plot.sussosurv() can now show prediction intervals and the STE | ||
| Changes in version 0.0.11 (2016-08-12) | ||
| - predict and plot for class sussosurv | ||
| Changes in version 0.0.10 (2016-08-01) | ||
| - kkt2 convergence criteria corrected from positive determinant | ||
| to positive min eigenvalue | ||
| Changes in version 0.0.9 (2016-07-28) | ||
| - bugfix in Poisson method, which did not return results | ||
| because of mispelled model name | ||
| Changes in version 0.0.7 (2016-07-25) | ||
| - the Kendall's tau for copulas is now initialized | ||
| using the SurvCorr package (much faster) | ||
| Changes in version 0.0.6 (2016-07-22) | ||
| - added the function convals(), giving the values of the max abs gradient | ||
| and the min eigenvalue of the variance-covariance matrix of the random treatment effects | ||
| - the function convergence() uses explicit computation provided by covals(), | ||
| Changes in version 1.1.15 (2017-04-25) | ||
| - fixed minor issue in prediction function for adjusted copula models | ||
|
|
||
| Changes in version 1.1.14 (2017-04-06) | ||
| - fixed issue in prediction intervals for mixed Poisson models | ||
|
|
||
| Changes in version 1.1.13 (2017-03-28) | ||
| - fixed issue in prediction intervals for adjusted copula models | ||
|
|
||
| Changes in version 1.1.12 (2017-03-02) | ||
| - loocv() now also returns the values of kTau and R2 | ||
| estimated in each (N-1) fold | ||
|
|
||
| Changes in version 1.1.10 (2017-02-27) | ||
| - fixed issues with loocv when few trials (added controls) | ||
| - added data 'gastadj' | ||
| - added twoStage parameter to surrosurv for Shih and Louis (1995) approach | ||
| to copula estimation | ||
|
|
||
| Changes in version 1.1.4 (2016-12-06) | ||
| - added paper manuscript as vignette('surrosurv') | ||
|
|
||
| Changes in version 1.1 (2016-11-09) | ||
| - Poisson models can be fitted each separately | ||
|
|
||
| ################################################################################ | ||
|
|
||
| Changes in version 0.1.1 (2016-09-28) | ||
| - fixed examples for poissonize() | ||
|
|
||
| Changes in version 0.1.0 (First Complete version, 2016-09-27) | ||
| - new function loocv() (with print() and plot() functions) | ||
| to compute leave-one-out cross-validation | ||
|
|
||
| ################################################################################ | ||
|
|
||
| Changes in version 0.0.15 (2016-09-23) | ||
| - new function ste() to compute the surrogate threshold effect | ||
| - plot.sussosurv() can now show prediction intervals and the STE | ||
|
|
||
| Changes in version 0.0.11 (2016-08-12) | ||
| - predict and plot for class sussosurv | ||
|
|
||
| Changes in version 0.0.10 (2016-08-01) | ||
| - kkt2 convergence criteria corrected from positive determinant | ||
| to positive min eigenvalue | ||
|
|
||
| Changes in version 0.0.9 (2016-07-28) | ||
| - bugfix in Poisson method, which did not return results | ||
| because of mispelled model name | ||
|
|
||
| Changes in version 0.0.7 (2016-07-25) | ||
| - the Kendall's tau for copulas is now initialized | ||
| using the SurvCorr package (much faster) | ||
|
|
||
| Changes in version 0.0.6 (2016-07-22) | ||
| - added the function convals(), giving the values of the max abs gradient | ||
| and the min eigenvalue of the variance-covariance matrix of the random treatment effects | ||
| - the function convergence() uses explicit computation provided by covals(), | ||
| instead of using the function optimx in the package optimx |
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