We provide functions to perform an empirical small telescopes
    analysis. This package contains 2 functions, SmallTelescopes() and 
    EstimatePower(). Users only need to call SmallTelescopes() to conduct 
    the analysis. For more information on small telescopes analysis see
    Uri Simonsohn (2015) <doi:10.1177/0956797614567341>.

Aims at loading Facebook and Instagram advertising data from
    'Smartly.io' into R. 'Smartly.io' is an online advertising service that enables
    advertisers to display commercial ads on social media networks (see <http://www.smartly.io/> for more information).
    The package offers an interface to query the 'Smartly.io' API and loads data directly into R for further data processing and data analysis.

Implements popular methods for matching in time-varying
    observational studies. Matching is difficult in this scenario because
    participants can be treated at different times which may have an
    influence on the outcomes. The core methods include: "Balanced Risk
    Set Matching" from Li, Propert, and Rosenbaum (2011)
    <doi:10.1198/016214501753208573> and "Propensity Score Matching with
    Time-Dependent Covariates" from Lu (2005)
    <doi:10.1111/j.1541-0420.2005.00356.x>. Some functions use the
    'Gurobi' optimization back-end to improve the optimization problem
    speed; the 'gurobi' R package and associated software can be
    downloaded from <https://www.gurobi.com> after obtaining a license.

Calculate the matrices in
    Shiller (1991, <doi:10.1016/S1051-1377(05)80028-2>) that serve as the
    foundation for many repeat-sales price indexes.

Provides methods for model building and model evaluation of mixed effects models using 
    'Monolix' <https://monolix.lixoft.com>. 'Monolix' is a software tool for nonlinear mixed effects 
    modeling that must have been installed in order to use 'Rsmlx'. 
    Among other tasks, 'Rsmlx' provides a powerful tool for automatic PK model building, performs 
    statistical tests for model assessment, bootstrap simulation and likelihood profiling for 
    computing confidence intervals. 'Rsmlx' also proposes several automatic covariate search methods for 
    mixed effects models.