st: Package "clstop_lbt" available on SSC

[Dirk Enzmann <dirk.enzmann@uni-hamburg.de>]

Thanks to Kit Baum, the new package "clstop_lbt" is available on SSC.

"clstop_lbt" adds the rule "lbt" to the post-estimation command -cluster 
stop- to determine the number of kmeans clusters using Steinley & 
Brusco's (2011) lower bound technique (LBT). It is used via -cluster 
stop, rule(lbt)-.

"clstop_lbt" creates the normalized index LBT that measures the 
closeness of the observed value of the within-cluster sums of squares 
(SSE) to the the minimum value of SSE in terms of total sums of squares 
(SST) according to LBT = (SSE - SSE_min)/SST. The method to determine 
the lower bound of SSE (i.e. SSE_min) is given in Steinley & Brusco 
(2011, p. 289). If the number of variables is equal or less than the 
number of clusters k, LBT is equal to the ratio SSE/SST (in this case, 
the LBT cannot be used).

"clstop_lbt" can also be used to determine whether there is more than 
one cluster. In this case the ratio SSE(2)/SST of a two cluster solution 
should be less than the lower bound ratio (LBR) obtainable when there is 
only one cluster - assuming a (multivariate) normal distribution, the 
LBR(normal) is 1-2/pi = .3634, assuming a univariate distribution the 
LBR(univariate) is .25.

A simulation study by Steinley & Brusco (2011) shows that the LBT index 
outperforms the accuracy and precision of the CH (Calinski/Harabasz) 
index. However, the LBT requires that the number of variables exceed the 
number of clusters. In cases of equal or less variables than the number 
of clusters Steinley & Brusco recommend to use the CH index (which is 
the default when using -cluster stop-).

Reference:

Steinley, D. & Brusco, M. J. (2011). Choosing the number of clusters in 
K-means clustering. Psychological Methods, 16, 285-297. [ 
http://psycnet.apa.org/journals/met/16/3/285/ ]

Dirk

========================================
Dr. Dirk Enzmann
Institute of Criminal Sciences
Dept. of Criminology
Rothenbaumchaussee 33
D-20148 Hamburg
Germany

phone: +49-(0)40-42838.7498 (office)
       +49-(0)40-42838.4591 (Mrs Billon)
fax:   +49-(0)40-42838.2344
email: dirk.enzmann@uni-hamburg.de
http://www2.jura.uni-hamburg.de/instkrim/kriminologie/Mitarbeiter/Enzmann/Enzmann.html
========================================
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