Search is a binary segmentation procedure used to develop a predictive model for a dependent variable. It searches among a set of predictor variables for the predictors that most increase the researcher’s ability to account for the variance or distribution of a dependent variable. The question “What dichotomous split on which single predictor variable will give us a maximum improvement in our ability to predict values of the dependent variable?” asked iteratively, is the basis for the Search algorithm.
Search can perform the following functions:
- Maximize differences in group means, group regression lines, distributions (maximum-likelihood chi-square criterion), or ranking (Kendall’s tau-b).
- Rank the predictors to give them preference in the partitioning.
- Sacrifice explanatory power for symmetry.
- Start after a specified partial tree structure has been generated.
The University of Michigan version of Search is a set of C and FORTRAN routines that can be launched from R, SAS, SPSS or Stata or run independently using data from many sources. It is available for computers running the Linux, Mac OS X and Microsoft Windows operating systems. For the independent Search implementation see the Srcware references in Documentation.
Search is also available as part of MicrOsiris, a full-featured data management and analysis software package for Microsoft Windows from Van Eck Computer Consulting at URL:
Search is freeware. The University of Michigan retains the copyright for Search and authorizes its use free of charge. See the Search License Agreement for details.
Search was developed by James N. Morgan, Peter W. Solenberger, Neal A. Van Eck, and Pauline R. Nagara.
Resources
Please report problems or send comments via e-mail to IVEware Support: isr-iveware@umich.edu. For more detailed help, please complete and submit this Help Request.
© The Regents of the University of Michigan, 2024. All rights reserved. Permission is granted to use, copy and redistribute this software for any purpose, so long as no fee is charged and so long as the copyright notice above, this grant of permission, and the disclaimer below appear in all copies made; and so long as the name of the University of Michigan is not used in any advertising or publicity pertaining to the use or distribution of this software without specific, written prior authorization. Permission to modify or otherwise create derivative works of this software is not granted. This software is provided as is, without representation as to its fitness for any purpose, and without warranty of any kind, either express or implied, including without limitation the implied warranties of merchantability and fitness for a particular purpose. The regents of the University of Michigan shall not be liable for any damages, including special, indirect, incidental, or consequential damages, with respect to any claim arising out of or in connection with the use of the software, even if it has been or is hereafter advised of the possibility of such damages.