Computer programs

R code implementing the simulation studies and HVTN 505 application in Gilbert, Blette, Shepherd, and Hudgens's manuscript ``Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial"

• R code

Gilbert PB, Zhang L, Rudnicki E, Huang Y. R code for implementing the statistical methods described in "Assessing Pharmacokinetic Marker Correlates of Outcome, with Application to Antibody Prevention Efficacy Trials" (2019, Stat Med).

• R code including all HIV-1 infected cases
• R code including excluding +++ first positive HIV-1 infected cases
• Case control data set analyzed by the R code
• Parent (full cohort) data set analyzed by the R code
• Results of data analysis (Table 1 in Gilbert et al. 2019)

R code implementing the Rotnitzky and Robins (1995, Biometrika) Augmented Inverse probability Weighted estimator of a mean and mean difference with application to analyzing peptide microarray outcomes in HVTN 106.

• R code for a data analysis

Price BL, Gilbert PB, van der Laan MJ. R code for implementing the Application for dengue vaccine efficacy trials (on dummy data sets) in "Estimation of the Optimal Surrogate Based on a Randomized Trial" (2018, Biometrics).

• R code

Gilbert PB, Janes HE, Huang Y. Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials. Statistics in Medicine (2016).

• R source package (compiled under R version 3.2.2 on Windows) for computing power to detect a continuous, trichotomous, or dichotomous biomarker as a correlate of risk of outcome in the active arm of a controlled clinical trial, accounting for measurement error and the level of treatment efficacy. Once the package is installed, type the following commands to read the documentation on the package and functions:

Juraska M, Gilbert PB. Mark-Specific Hazard Ratio Model with Missing Multivariate Marks. Lifetime Data Analysis (2016).

• Code implementing the methods for a mark-specific hazard ratio for a bivariate mark V
• Code implementing the diagnostic test of T independent of V for V univariate
• Code implementing the diagnostic test of T independent of V for V bivariate
• Example code for illustrating application of the methods to a data set (identical structure as the Step data set analyzed in Juraska and Gilbert (2015), with altered values to satisfy data sharing legal requirements)
• Example data set used for the illustration

Fu R, Gilbert PB. Joint Modeling of Longitudinal and Survival Data with the Cox Model and Two-Phase Sampling. Lifetime Data Analysis (2016).

• Code implementing the methods
• Example code for illustrating application of the methods to a data set
• Example data set used for the illustration

Sun Y, Gilbert PB. Estimation of stratified mark-specific proportional hazards models with missing marks. Scandinavian Journal of Statistics, Theory and Applications (2012) and Gilbert PB, Sun Y. Testing for vaccine efficacy against a spectrum of pathogen sequences in stratified mark-specific proportional hazards models with missing marks, with application to the RV144 HIV vaccine efficacy trial. Journal of the Royal Statistical Society, Series C (2014)

• Instructions and case study for how to run the R code implementing the methods
• The code for downloading

Gilbert PB, Shepherd BE, Hudgens MG. Sensitivity analysis of per-protocol time-to-event treatment efficacy in randomized clinical trials. Journal of the American Statistical Association. 2013;108(503):789-800.

• Instructions and case study for how to run the R code implementing the methods (Bryan Shepherd's website)

Finite-Sample Corrected GEE of Population Average Treatment Effects in Stepped Wedge Cluster Randomized Trials [Method of Scott, deCamp, Juraska, Fay, Gilbert, 2014, Statistical Methods in Medical Research

• R code implementing the methods in the article Scott et al. 2014

Gilbert, Yu, and Rotnitzky (2014, Statistics in Medicine), ``Optimal Auxiliary-Covariate Based Sampling Design for Semiparametric Efficient Estimation of a Mean or Mean Difference, with Application to Clinical Trials"

• R code implementing Results 1-4 for determining the optimal 2-phase sampling design and for carrying out the corresponding optimal analysis via the Rotnitzky and Robins (1995, Biometrika) method

R Code Implementing Gilbert, Rossini, and Shankarappa (2005, Biometrics)

• Two-Sample Tests for Comparing Genetic Sequence Diversity Between Populations

Compute Simultaneous Confidence Bands for a Log Hazard Ratio over Time [Method of Gilbert, Wei, Kosorok, Clemens (2002, Biometrics)]

• Example R code for computing simultaneous confidence bands about a log hazard ratio over time
• R program for calling the program (confidenceband.loghazratio.r) that computes the confidence bands and for plotting the point estimates and confidence bands
• R program for computing the confidence bands

Sensitivity Analysis for Assessing the Causal Effect of Vaccine on Viral Load [Method of Gilbert, Bosch, and Hudgens (2003, Biometrics)]

• Example R code for assessing the causal effect of vaccination on viral load
• R code that implements the estimation and testing procedures
• R code that plots the ACE estimators and p-values of the testing procedures

Sample Size for Studying Vaccine Effects on Infection in Repeated Low Dose Challenge Studies [Method of Hudgens and Gilbert (2009, Biometrics)]

• Sample Size Calculator for Non-Human Primate Repeated Low Dose Challenge Studies

The two-sample problem for failure rates depending on a continuous mark: an application to vaccine efficacy [Method of Gilbert, McKeague, and Sun (2008, Biostatistics)]: R package cmprskContin available at CRAN

• Comprehensive R Archive Network Homepage

Semiparametric efficient estimation for a two-sample treatment effect in a randomized clinical trial, for a quantitative endpoint, a dichotomous endpoint, or a right-censored time-to-event endpoint [For a quantitative endpoint, the method is described in Gilbert et al. (2009, Vaccine)]: R package speff2trial available at CRAN

• Comprehensive R Archive Network Homepage

Evaluating covariability of amino acid site doubles and triples, and comparing covariability between two groups of amino acid sequences [Method of Gilbert, Novitsky, and Essex, AIDS Research and Human Retroviruses, 2005; 21: 1016-1030]

• R and C code for performing the M and M* covariability methods of Gilbert et al. 2005