Chen, N., Carlin, B.P., and Hobbs, B.P. (2018), ``Web-based statistical tools for the analysis and design of clinical trials that incorporate historical controls." Computational Statistics and Data Analysis., 127, 50--68.
In this case we do not provide code, but instead a link to the online by constructed by Dr. Nan Chen, with component code chunks contributed by Dr. Brian Hobbs.
In this case we do not provide code, but instead a link to the online by constructed by Dr. Nan Chen, with component code chunks contributed by Dr. Brian Hobbs.
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Paper and Supplementary Content:
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Lewis, C.J., Sarkar, S., Zhu, J., and Carlin, B.P. (2018). ``Borrowing from historical control data in cancer drug development: A cautionary tale and practical guidelines." To appear Statistics in Biopharmaceutical Research.
OpenBUGS code below fits the "full model" in the paper. This code written by Ms. Connor Jo Lewis in 2017.
OpenBUGS code below fits the "full model" in the paper. This code written by Ms. Connor Jo Lewis in 2017.
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Manuscript:
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OpenBUGS code:
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Data (BUGS format):
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Hong, H., Fu, H., and Carlin, B.P. (2018), ``Power and commensurate priors for synthesizing aggregate and individual patient-level data in network meta-analysis," J. Roy. Statist. Soc., Ser. C (Applied Statistics), 67, 1047--1069.
The supplemental material file contains the JAGS code written by Dr. Hwanhee Hong in 2015-16 to fit the integrative (individual-level plus aggregate-level) data models in the paper.
The supplemental material file contains the JAGS code written by Dr. Hwanhee Hong in 2015-16 to fit the integrative (individual-level plus aggregate-level) data models in the paper.
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Manuscript and Supplementary Materials:
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JAGS code (see Supplementary Materials for full explanation):
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Schnell, P.M., Tang, Q., Muller, P., and Carlin, B.P. (2017), ``Subgroup inference for multiple treatments and multiple endpoints in an Alzheimer's disease treatment trial," Annals of Applied Statistics, 11, 949--966.
Zip file contains the code and data to compute quantile-based simultaneous credible bands from posterior samples, as well as run the simulation study described in the manuscript. The NIMBLE R package is also required. These programs were written by Dr. Patrick Schnell in 2016.
Zip file contains the code and data to compute quantile-based simultaneous credible bands from posterior samples, as well as run the simulation study described in the manuscript. The NIMBLE R package is also required. These programs were written by Dr. Patrick Schnell in 2016.
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Manuscript:
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Code:
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Schnell, P.M., Tang, Q., Offen, W.W., and Carlin, B.P. (2016), ``A Bayesian credible subgroups approach to identifying patient subgroups with positive treatment effects," (with supplementary material ). Biometrics, 72, 1026--1036.
Zip file contains the R code to reproduce both the Alzheimer's disease example analysis and the simulation study in the paper. These programs were written by Dr. Patrick Schnell during 2015-16.
Zip file contains the R code to reproduce both the Alzheimer's disease example analysis and the simulation study in the paper. These programs were written by Dr. Patrick Schnell during 2015-16.
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Manuscript:
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Code:
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Supplementary materials:
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Zhao, H., Hodges, J.S., Ma, H., Jiang, Q., and and Carlin, B.P. (2016), ``Hierarchical Bayesian approaches for detecting inconsistency in network meta-analysis." Statistics in Medicine, 35, 3524--3536.
Zip file contains the BUGS program (winbug_ABRE.odc) that creates the "AB random effect models" results in Table 3 of the paper. These programs were written by Dr. Hong Zhao during 2015.
Zip file contains the BUGS program (winbug_ABRE.odc) that creates the "AB random effect models" results in Table 3 of the paper. These programs were written by Dr. Hong Zhao during 2015.
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Manuscript:
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Code:
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Hong, H., Chu, H., Zhang, J., and Carlin, B.P. (2016), ``A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons" (with discussion and rejoinder), Research Synthesis Methods, 7, 6--33.
Zip file contains the WinBUGS code and data necessary to fit all the arm-based (AB) and contrast-based (CB) network meta analysis (NMA) models in the paper. Code written by Dr. Hwanhee Hong in 2014-15.
Zip file contains the WinBUGS code and data necessary to fit all the arm-based (AB) and contrast-based (CB) network meta analysis (NMA) models in the paper. Code written by Dr. Hwanhee Hong in 2014-15.
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Manuscript, discussion, and rejoinder:
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Code:
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Murray, T.A., Hobbs, B.P., Sargent, D.J. and Carlin, B.P. (2016). ``Flexible Bayesian survival modeling with semiparametric time-dependent and shape-restricted covariate effects," Bayesian Analysis, 11, 381--402.
Zip file contains the R-JAGS code to replicate each of the three simulation investigations found in Sections 4.1, 4.2, and 4.3 of the paper. These programs were written by Dr. Tom Murray during 2014 and 2015 .
Zip file contains the R-JAGS code to replicate each of the three simulation investigations found in Sections 4.1, 4.2, and 4.3 of the paper. These programs were written by Dr. Tom Murray during 2014 and 2015 .
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Manuscript:
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Code:
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Murray, T.A., Hobbs, B.P., and Carlin, B.P. (2015), ``Combining nonexchangeable functional or survival data sources in oncology using generalized mixture commensurate priors," Annals of Applied Statistics, 9, 1549--1570.
Zip file contains the R program (GMCSim.R) that replicates the simulation investigation found in Section 3.2 of the paper. These programs were written by Dr. Tom Murray during 2014; revised in 2015.
Zip file contains the R program (GMCSim.R) that replicates the simulation investigation found in Section 3.2 of the paper. These programs were written by Dr. Tom Murray during 2014; revised in 2015.
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Manuscript:
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Code:
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Murray, T.A., Hobbs, B.P., Lystig, T.C., and Carlin, B.P. (2014). ``Semiparametric Bayesian commensurate survival model for post-market medical device surveillance with non-exchangeable historical data," Biometrics, 70, 185--191.
Zip file contains the BUGS and R code to fit the models in this paper above and produce the paper's analyses of the dialysis patient heart stent data in Figure 1 and Table 2. These programs were written by Dr. Tom Murray during 2013.
Zip file contains the BUGS and R code to fit the models in this paper above and produce the paper's analyses of the dialysis patient heart stent data in Figure 1 and Table 2. These programs were written by Dr. Tom Murray during 2013.
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Manuscript and Web Supplement:
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Code:
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Quick, H., Banerjee, S., and Carlin, B.P. (2013), ``Modeling temporal gradients in regionally aggregated California asthma hospitalization data," Annals of Applied Statistics, 7, 154--176.
Zip file containing the BUGS and R code to fit the models in this paper above. These programs were written by Dr. Harrison Quick during 2012.
Zip file containing the BUGS and R code to fit the models in this paper above. These programs were written by Dr. Harrison Quick during 2012.
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Paper and Web Supplement:
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Code:
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Guo, X. and Carlin, B.P. (2004), ``Separate and joint modeling of longitudinal and event time data using standard computer packages,'' The American Statistician, 58, 16--24.
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WinBUGS 1.4 program written by Ms. Xu Guo, 3/1/03, to fit "Model XI", the chosen joint (longitudinal plus survival) model in the paper. Full posterior inferential results are obtained via MCMC sampling.
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WinBUGS 1.4 program written by Ms. Xu Guo, 6/26/03, to fit "Model XII", a slightly more general joint model that allows the hazard function to vary with time. Full posterior inferential results are obtained via MCMC sampling. WARNING: This code ignores the time-varying aspect of the survival portion of the model, and must thus be considered approximate!
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WinBUGS 1.4 program written by Mr. Jeremiah Menk for a class project (joint with Ms. Emily Zabor and Ms. Anne Eaton), Spring 2010, to fit "Model XII" with the correct time-varying aspect using the "zeros trick" in WinBUGS.
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WinBUGS 1.4 program written by Dr. Michael Sweeting, 7/12/10, also used to correctly fit "Model XII" with the time-varying aspect, this time using the "ones trick" in WinBUGS; results are broadly similar to those obtained using the Menk code!
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SAS Proc SORT, MIXED, LIFEREG, and NLMIXED code written by Dr. Oliver Schabenberger, 3/21/03, to fit Model XI above. Estimation of random effects is now via empirical Bayes, with associated standard errors obtained by the delta method.
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SAS Proc SORT, MIXED, LIFEREG, and NLMIXED code written by Dr. Oliver Schabenberger, 6/27/03, to fit Model XII above. Estimation of random effects is again via empirical Bayes, with associated standard errors obtained by the delta method.
WARNING: This code also ignores the time-varying aspect of the model, and so is in principle similar to the original Model XII WinBUGS code above. |
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