UPSaccum: Prepare for Accumulation of (Outcome,Treatment) Results in...

Description Usage Arguments Details Value Author(s) References See Also

Description

Specify key result accumulation parameters: Treatment t-Factor, Outcome Y-variable, faclev setting, scedasticity assumption, and name of the UPSgraph() data accumulation object.

Usage

1
UPSaccum(envir, dframe, trtm, yvar, faclev = 3, scedas = "homo")

Arguments

envir

name of the working local control classic environment.

dframe

Name of data.frame containing the X, t & Y variables.

trtm

Name of treatment factor variable.

yvar

Name of outcome Y variable.

faclev

Maximum number of different numerical values an outcome variable can assume without automatically being converted into a "factor" variable; faclev=1 causes a binary indicator to be treated as a continuous variable determining an average or proportion.

scedas

Scedasticity assumption: "homo" or "hete"

Details

The second phase in an Unsupervised Propensity Scoring analysis is to prepare to accumulate results over a wide range of values for "Number of Clusters." As the number of such clusters increases, individual clusters will tend to become smaller and smaller and, thus, more and more compact in covariate X-space.

Value

Author(s)

Bob Obenchain <[email protected]>

References

Obenchain RL. (2004) Unsupervised Propensity Scoring: NN and IV Plots. Proceedings of the American Statistical Association (on CD) 8 pages.

Obenchain RL. (2011) USPSinR.pdf USPS R-package vignette, 40 pages.

See Also

UPSnnltd, UPSivadj and UPShclus.


LocalControl documentation built on May 2, 2019, 7:29 a.m.