Restricted Cubic Splines were performed to explore the shape of association form of "U, inverted U,
    L" shape and test linearity or non-linearity base on "Cox,Logistic,linear,quasipoisson" regression, and auto output Restricted Cubic Splines figures.
    rcssci package could automatically draw RCS graphics with Y-axis "OR,HR,RR,beta".
    The Restricted Cubic Splines method were based on 
    Suli Huang (2022) <doi:10.1016/j.ecoenv.2022.113183>,Amit Kaura (2019) <doi:10.1136/bmj.l6055>,
    and Harrell Jr (2015, ISBN:978-3-319-19424-0 (Print) 978-3-319-19425-7 (Online)).

Provides a means to style plots through cascading style sheets.
    This separates the aesthetics from the data crunching in plots and charts.

Assists in the whole process of designing and evaluating Randomized Control Trials.
    Robust treatment assignment by strata/blocks, that handles misfits; 
    Power calculations of the minimum detectable treatment effect or minimum populations;
    Balance tables of T-test of covariates; 
    Balance Regression: (treatment ~ all x variables) with F-test of null model; 
    Impact_evaluation: Impact evaluation regressions. This function
    gives you the option to include control_vars, fixed effect variables,
    cluster variables (for robust SE), multiple endogenous variables and
    multiple heterogeneous variables (to test treatment effect heterogeneity)
    summary_statistics: Function that creates a summary statistics table with statistics 
    rank observations in n groups: Creates a factor variable with n groups. Each group has 
    a min and max label attach to each category.
    Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>.

Provides various statistical methods for designing and analyzing two-stage randomized controlled 
	trials using the methods developed by Imai, Jiang, and Malani (2021) <doi:10.1080/01621459.2020.1775612> and 
	(2022+) <doi:10.48550/arXiv.2011.07677>.  The package enables the estimation of direct and spillover effects, 
	conduct hypotheses tests, and conduct sample size calculation for two-stage randomized controlled trials.