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RCT helps you focus on the statistics of the randomized control trials, rather than the heavy programming lifting. Any social scientist should use RCT when conducting Field Experiments.
RCT helps you in the whole process of designing and evaluating a RCT.
This version ensures that all functions remain compatible with upcoming dplyr 1.0.0 - balance_regression should continue to work well in both dplyr 0.89 and dplyr 1.0.0
This version ensures that all functions remain compatible with broom 0.70
This version introduces a new function (N_min) & corrects CRAN error due to lfe change.
This version now add a table of the treatments into summary_strata within treatment_Assign
This version replaces the regression engine for impact_eval from lfe (deprecated) to lm_robust. It has extremely similar functionality. The main difference is that now we only support 1 cluster variables and no more than 2 fixed effect variables.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.