Facilities for Simulating from ODE-Based Models (RxODE)
Facilities for running simulations from ordinary differential equation (ODE) models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the ‘R Administration and Installation’ manual. Also the code is mostly released under GPL. The VODE and LSODA are in the public domain. The information is available in the inst/COPYRIGHTS.

Stanford ‘ATLAS’ Search Engine API (atlas)
Stanford ‘ATLAS’ (Advanced Temporal Search Engine) is a powerful tool that allows constructing cohorts of patients extremely quickly and efficiently. This package is designed to interface directly with an instance of ‘ATLAS’ search engine and facilitates API queries and data dumps. Prerequisite is a good knowledge of the temporal language to be able to efficiently construct a query. More information available at <https://…/start>.

In-place Operators for R (inplace)
It provides in-place operators for R that are equivalent to ‘+=’, ‘-=’, ‘*=’, ‘/=’ in C++. Those can be applied on integer|double vectors|matrices. You have also access to sweep operations (in-place).

Simulation Extrapolation Inverse Probability Weighted Generalized Estimating Equations (swgee)
Simulation extrapolation and inverse probability weighted generalized estimating equations method for longitudinal data with missing observations and measurement error in covariates. References: Yi, G. Y. (2008) <doi:10.1093/biostatistics/kxm054>; Cook, J. R. and Stefanski, L. A. (1994) <doi:10.1080/01621459.1994.10476871>; Little, R. J. A. and Rubin, D. B. (2002, ISBN:978-0-471-18386-0).

A User-Oriented Statistical Toolkit for Analytical Variance Estimation (gustave)
Provides a toolkit for analytical variance estimation in survey sampling. Apart from the implementation of standard variance estimators, its main feature is to help the sampling expert produce easy-to-use variance estimation ‘wrappers’, where systematic operations (linearization, domain estimation) are handled in a consistent and transparent way for the end user.