Summary ellipses superimposed on a scatter plot contain all bi-variate summary
            statistics for regression analysis. Furthermore, the outer ellipse flags potential
            outliers. Multiple groups can be compared in terms of centers and spreads as illustrated
            in the examples.

Provides a general purpose simulation-based power analysis 
   API for routine and customized simulation experimental designs. 
   The package focuses exclusively on Monte Carlo simulation experiment variants of 
   (expected) prospective power analyses, 
   criterion analyses, compromise analyses, sensitivity analyses, and 
   a priori/post-hoc analyses. The default simulation experiment functions defined within the package 
   provide stochastic variants of the power analysis subroutines in 
   G*Power 3.1 (Faul, Erdfelder, Buchner, and Lang, 2009) <doi:10.3758/brm.41.4.1149>,
   along with various other parametric and non-parametric power analysis 
   applications (e.g., mediation analyses) and support for Bayesian power analysis 
   by way of Bayes factors or posterior probability evaluations. 
   Additional functions for building 
   empirical power curves, reanalyzing simulation information, and 
   for increasing the precision of the resulting power 
   estimates are also included, each of which utilize similar API structures.

We propose a novel two-step procedure to combine epidemiological
    data obtained from diverse sources with the aim to quantify risk factors
    affecting the probability that an individual develops certain disease such as
    cancer. See  Hui Huang, Xiaomei Ma, Rasmus Waagepetersen, Theodore R. Holford,
    Rong Wang, Harvey Risch, Lloyd Mueller & Yongtao Guan (2014) A New Estimation Approach
    for Combining Epidemiological Data From Multiple Sources, Journal of the American Statistical
    Association, 109:505, 11-23,  <doi:10.1080/01621459.2013.870904>.

Predicts the occurrence times (in day-of-year) of spring phenological events. Three methods, including the accumulated degree days (ADD) method, the accumulated days transferred to a standardized temperature (ADTS) method, and the accumulated developmental progress (ADP) method, were used. See Shi et al. (2017a) <doi:10.1016/j.agrformet.2017.04.001> and Shi et al. (2017b) <doi:10.1093/aesa/sax063> for details.