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The Measurement of Speed in Motor Performance

Published online by Cambridge University Press:  01 January 2025

C. H. McCloy
C. H. McCloy*
Affiliation:
State University of Iowa
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Abstract

When the centroid method of factor analysis was applied to two sets of data on athletic performances, three significant factors emerged: strength, velocity, and dead weight. Scores on this speed factor were predicted by the multiple regression technique, the factor loadings on the speed factor being used as the criterion correlations, and these predicted scores were correlated with each of the other variables. When the original tables, augmented by the new speed variable, were refactored, the computed speed factor fell on the speed axis as a primary trait. It is thus shown that it is possible to isolate and measure a factor which appears in variables under consideration only as a compound.

Type
Original Paper
Information
Psychometrika , Volume 5 , Issue 3 , September 1940 , pp. 173 - 182
Copyright
Copyright © 1940 The Psychometric Society

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Footnotes

*

Much of the expense of the statistical computations connected with this study was financed by a grant from the Carnegie Foundation for the Advancement of Teaching.

References

* Coleman, James W. The differential measurement of the speed factor in large muscle activities. Research Quarterly, 1937, 3, 123-130.

† Harris, Jane E. The differential measurement of force and velocity for junior high school girls. Research Quarterly, 1937, 4, 114-121.

* The “Strength Index” is a total strength score made up of the sum of a number of strength test variables. See McCloy, C.H. Tests and Measurements in Health and Physical Education. New York: F. S. Crofts, 1939, Chapter 4.

† All of the other variables used have absolute values, regardless of the group studied. Thus a 10-year old boy and a 20-year old man, each of whom runs 100 yards in 12 seconds, achieve the same record. The scores for a speed factor, however, computed for each of the two age groups, would probably be different since they would be in terms of standard deviations from means of different experimental groups.

‡ We prefer T-scores to z-scores (or standard scores) because we find them to be much more meaningful to students, who frequently seem to have a high natural resistance against minus signs.

* It has been so used by one coach of track and field athletics, who found that all boys showing a large amount of this factor (T-scores 65 and up) made excellent track athletes when trained, regardless of their previous experience.