| reveal.data {NU.Learning} | R Documentation |
Create a data.frame for use in Prediction of a LTD/LRC effect-size Distribution
Description
reveal.data() forms a data.frame by sorting and appending the LTD or LRC exposure effect-size measures from ltdagg() or lrcagg() – as well as a Cluster membership-number variable – to a copy of the data.frame specified in NUsetup(). In the fourth and final REVEAL Phase of NU.Learning, a stretch-goal is to predict variation in LTD/LRC effect-size distributions using the known (baseline) X-covariate characteristics of experimental units. For example, the data.frame output by reveal.data() is suitable for input to party::ctree() as well as to a number of other "less Visual" prediction methods available in R.
Usage
reveal.data(x, clus.var="Clus", effe.var="eSiz")Arguments
x |
An output object resulting from a call to ltdagg() or lrcagg(). |
clus.var |
Quoted NAME for the Cluster-Number variable. |
effe.var |
Quoted NAME for the LTD/LRC effect-size variable. |
Value
The desired data.frame:
outdf |
A data.frame containing clus.var, effe.var plus (X, trex & Y) variables. |
Author(s)
Bob Obenchain <wizbob@att.net>
References
Obenchain RL. (2023) NU.Learning_in_R.pdf http://localcontrolstatistics.org