The purpose of this study was to use a cross categorical scoring method for sociometric data focusing upon those individuals who have made the selections. A cross category selection was defined as choosing an individual on a sociometric instrument who was not within one's own classification. The classifications used for this study were sex, race, and perceived achievement level. A cross category score was obtained by summing the number of cross category selections. The conclusions below are the result of this study. Cross categorical scoring provides a useful method of scoring sociometric data. This method successfully focuses on those individuals who make sociometric choices rather than those who receive them. Each category utilized provides a unique contribution. The categories used in this study were sex, race, and achievement level. These are, however, only reflective of any number of variables which could be used. The categories must be chosen to reflect the needs of the particular study in which they are included. Multiple linear regression analysis can be used in order to provide the researcher with enough scope to handle numerous nominal and ordinal independent variables simultaneously. The sociometric criterion or question does make a difference in the results on cross categorical scores. Therefore, in a group that has more than one identifiable activity, a question pertaining to each activity should be included.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc331885 |
| Date | 12 1900 |
| Creators | Ernst, Nora Wilford |
| Contributors | Brookshire, William K., Haynes, Jack Read, Bonk, Edward C., McCallon, Earl L. |
| Publisher | North Texas State University |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | vi, 139 leaves, Text |
| Rights | Public, Ernst, Nora Wilford, Copyright, Copyright is held by the author, unless otherwise noted. All rights reserved. |
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