UPSgraph {USPS} | R Documentation |
Plot summary of results from multiple calls to UPSnnltd() and/or UPSivadj() after an initial setup call to UPSaccum(). The UPSgraph() plot displays any sensitivity of the LTD and LOA Distributions to choice of Number of Clusters in X-space.
UPSgraph(nncol = "red", nwcol = "green3", ivcol = "blue", ...)
nncol |
optional; string specifying color for display of the Mean of the LTD distribution when weighted by cluster size from any calls to UPSnnltd(). |
nwcol |
optional; string specifying color for display of the Mean of the LTD distribution when weighted inversely proportional to variance from any calls to UPSnnltd(). |
ivcol |
optional; string specifying color for display of the Difference in LOA predictions, at PS = 100% minus that at PS = 0%, from any calls to UPSivadj(). |
... |
Optional parameter(s) passed on to plot(). |
The third phase of Unsupervised Propensity Scoring is a graphical Sensitivity Analysis that depicts how the Overall Means of the LTD and LOA distributions change with the number of clusters.
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Bob Obenchain <wizbob@att.net>
Kaufman L, Rousseeuw PJ. (1990) Finding Groups in Data. An Introduction to Cluster Analysis. New York: John Wiley and Sons.
Obenchain RL. (2004) Unsupervised Propensity Scoring: NN and IV Plots. Proceedings of the American Statistical Association (on CD) 8 pages.
Obenchain RL. (2009) USPSinR.pdf ../R_HOME/library/USPS 40 pages.
Rubin DB. (1980) Bias reduction using Mahalanobis metric matching. Biometrics 36: 293-298.
UPSnnltd
, UPSivadj
and UPSaccum
.
data(lindner) UPSxvars <- c("stent", "height", "female", "diabetic", "acutemi", "ejecfrac", "ves1proc") UPSharch <- UPShclus(lindner, UPSxvars) UPSaccum(UPSharch, lindner, abcix, lifepres, faclev=1, scedas="homo", accobj="ABClife") lif001nn <- UPSnnltd(1) lif020nn <- UPSnnltd(20) lif070nn <- UPSnnltd(70) lif120nn <- UPSnnltd(120) UPSgraph() ABClife