The past is one of the best predictors of the present and future behavior of individuals or organizations. Few would argue with this principle, yet it is largely ignored in the human factors literature. Most data analysis assumes independence of successive observations, and most theories deal with simultaneous values of several variables. This paper illustrates the dynamics of the two major subjects of human factors studies: organizations and individuals. Several representative human factors variables are shown to exhibit dynamism. Implications of a dynamic viewpoint are that static `heories may be incomplete, traditional data analysis methods are inappropriate for some types of human factors data, experimental designs for dynamic variables will have few subjects and many observations per subject, and dynamic analysis will be useful in human factors.
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References
1.
Abraham, B.Intervention analysis and multiple time series. Biometrika, 1980, 67, 73–78.
2.
Box, G. E. P., and Jenkins, G. M.Time series analysis, forecasting, and control.San Francisco: Holden-Day, 1970.
3.
Box, G. E. P., and Newbold, P.Some comments on a paper by Coen, Gomme, and Kendall. Journal of the Royal Statistical Society Series A, 1970, 134, 229–240.
4.
Box, G. E. P., and Tiao, G. C.Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical Association, 1975, 70, 70–79.
5.
Bracewell, R.The Fourier transform and its applications. New York: McGraw-Hill, 1965.
6.
Carter, R. C., Kennedy, R. S., and Bittner, A. C., Jr.Grammatical reasoning: A stable performance yardstick. Human Factors, 1981, 23, 587–591.
7.
Carter, R. C., and Sbisa, H. E.Human performance tests for repeated measurements: Alternate forms of eight tests by computer (Report NBDL-82R003). New Orleans, LA: Naval Biodynamics Laboratory, January, 1982. (NTIS No. AD A115021)
8.
Cook, P. D., Dintzer, L., and Mark, M. M.The causal analysis of concomitant time series. In L. Bickman (Ed.), Applied Social Psychology Annual (Vol. 1), Beverly Hills: Sage, 1980.
9.
DeRusso, P. M., Roy, R. J., and Close, C. M.State variables for engineers.New York: Wiley, 1965.
10.
Ekstrom, R. B., French, J. W., Harman, H. H., and Dermen, D.Manual for kit of factor-referenced cognitive tests.Princeton, NJ: Educational Testing Service, 1976.
11.
Glass, G. V., Willson, V. L., and Gottman, J. M.Design and analysis of time-series experiments. Boulder, CO: Colorado Associated University Press, 1975.
12.
Goldberg, L.Recruiters, advertising, and navy enlistments (CRC 409). Alexandria, VA: Center for Naval Analyses, October, 1979. (NTIS No. ADA086201)
13.
Higgins, J. J.A robust model for estimating and testing for means in single subject experiments. Human Factors, 1978, 20, 717–724.
14.
Hollingsworth, S.Functional periodicity.New York: Teachers College of Columbia University, 1914.
15.
Hosking, J. R. M.The multivariate portmanteau statistic. Journal of the American Statistical Association, 1980, 75, 602–608.
16.
Kazdin, A. E.Single-case research designs: Methods for clinical and applied settings.New York: Oxford University Press, 1982.
17.
Kenny, D. A.Correlation and causality.New York: Wiley, 1979.
18.
Komaki, J., Heinzmann, A. J., and Lawson, L.Effect of training and feedback: Component analysis of a behavioral safety program. Journal of Applied Psychology, 1980, 65, 261–270.
19.
Klein, R., and Armitage, R.Rhythms in human performance: 1 1/2-hour oscillations in cognitive style, Science,1979, 204, 1326–1328.
20.
Krause, M.Repeated measures on a choice reaction time test. In Proceedings of the 26th Annual Meeting of the Human Factors Society, Santa Monica, CA: Human Factors Society, 1982. (NTIS No. ADA121904)
21.
Ljung, G. M., and Box, G. E. P.On a measure of lack of fit in time series models. Biometrika.1978, 65, 297–303.
22.
Marmarelis, P. Z., and Marmarelis, V. Z.Analysis of physiological systems.New York: Plenum, 1978.
23.
Nelson, C. R.Applied time series analysis.San Francisco: Holden-Day, 1973.
24.
Scheffé, H. A.The analysis of variance.New York: Wiley, 1959.
25.
Tiao, G. C., and Box, G. E. P.Modeling multiple time series with applications. Journal of the American Statistical Association, 1981, 76, 802–816.
26.
Tiao, G. C., Box, G. E. P., Grupe, M. R., Hudak, G. B., Bell, W. R., and Chang, I.The Wisconsin Multiple Time Series (WMTS-1) Program: A preliminary guide.Madison, WI: University of Wisconsin, Department of Statistics, 1979.
