A Method of Grouping Projects for Comparisons

A Method of Grouping Projects for Comparisons Most methods currently available for grouping an agency fundedprojects are well suited for continuous data (e.g., Dalenius and Hodges Cum √ frule) but not for grouping a few projects based on their means. This is because these projectmeans form a set of discrete observations. So, applying Dalenius and Hodges Cum √ frule to such discrete observations generally does not help in forming as homogeneousgroups as one would desire. Seeking more homogeneous groups in practice is necessary becauseoften an administrator needs as accurate comparisons among projects as possible (e.g.,evaluation of project performances) to make correct decisions about continuation or administrationof agency funded projects. Therefore, in this paper an iterative procedure is given togroup projects in such a situation. To apply this procedure, the only requirement is that the variableused for stratification is not a categorical or a nominal variable. The iterative procedure isillustrated by three examples. As should be expected, the procedure yields a different and morehomogeneous set of strata than the one obtained by the Cum √ f rule. For administration ofprojects, to form as homogeneous a group of projects as possible is important and , therefore,it is advisable to use this procedure to achieve more homogeneous strata for the data at hand. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

A Method of Grouping Projects for Comparisons

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1023/A:1023319322594
Publisher site
See Article on Publisher Site

Abstract

Most methods currently available for grouping an agency fundedprojects are well suited for continuous data (e.g., Dalenius and Hodges Cum √ frule) but not for grouping a few projects based on their means. This is because these projectmeans form a set of discrete observations. So, applying Dalenius and Hodges Cum √ frule to such discrete observations generally does not help in forming as homogeneousgroups as one would desire. Seeking more homogeneous groups in practice is necessary becauseoften an administrator needs as accurate comparisons among projects as possible (e.g.,evaluation of project performances) to make correct decisions about continuation or administrationof agency funded projects. Therefore, in this paper an iterative procedure is given togroup projects in such a situation. To apply this procedure, the only requirement is that the variableused for stratification is not a categorical or a nominal variable. The iterative procedure isillustrated by three examples. As should be expected, the procedure yields a different and morehomogeneous set of strata than the one obtained by the Cum √ f rule. For administration ofprojects, to form as homogeneous a group of projects as possible is important and , therefore,it is advisable to use this procedure to achieve more homogeneous strata for the data at hand.

Journal

Quality & QuantitySpringer Journals

Published: Oct 17, 2004

References

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