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The Connecticut Crackdown on Speeding
Time-Series Data in Quasi-Experimental Analysis
Published online by Cambridge University Press: 01 July 2024
Extract
Social research frequently encounters the task of evaluating change produced in nonrandomly selected groups by events which are beyond the researcher's control. The social scientist must verify that there has in fact been a change, and that the indicated event is its cause. Illustrations are manifold: a state terminates capital punishment, and proponents of this type of punishment predict an increase in the murder rate; a school is integrated, and supporters of the reform expect to find an increase in the positive self-evaluation of Negro pupils; a natural disaster occurs in a community, and altruistic behavior is expected to increase. Because in these situations the investigator has no control over the assignment of individuals or groups to “experimental” and “control” situations, the logic of the classical experiment must be reexamined in a search for optimal interpretative procedures.
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- Copyright © 1968 by the Law and Society Association
Footnotes
Authors' Note: The preparation of this paper has been supported in part by the National Science Foundation (Grant GS 1309x), the U. S. Office of Education (Project C-998, Contract 3-20-001), the U. S. Bureau of Public Roads (CPR 11-5981), the National Institutes of Health, the U. S. Public Health Service (RG-5359), and the Automotive Safety Foundation (as an aspect of Experimental Case Studies of Traffic Accidents conducted at Northwestern University). A brief version of it appears as H. L. Ross & D. T. Campbell, The Connecticut Speed Crackdown: A Study of the Effects of Legal Change, in Perspectives on the Social Order: Readings in Sociology 30-35 (2d ed. H. L. Ross ed. 1968).
References
1. E.g., D. T. Campbell & J. S. Stanley, Experimental and Quasi-Experimental Designs for Research on Teaching, in Handbook of Research on Teaching 171-246 (N. L. Gage ed. 1963) reprinted as Experimental and Quasi-Experimental Designs for Research (1963); D. T. Campbell, From Description to Experimentation: Interpreting Trends as Quasi-Experiments, in Problems in Measuring Change (C. W. Harris ed. 1963); D. T. Campbell & K. N. Clayton, Avoiding Regression Effects in Panel Studies of Communication Impact, in Studies in Public Communication 99-118 (Dept. of Sociology. University of Chicago, No. 3, 1961) reprinted in Bobbs-Merrill Reprints in Sociology as S-353. For an application of this type of analysis to legal impact, see R. Lempert, Strategies of Research Design in the Legal Impact Study, 1 L. & Soc'y Rev. 111 (1966).
2. Cited in C. Selltiz, M. Jahoda, M. Deutsch, & S. W. Cook, Research Methods in Social Relations 323 (1959).
3. J. Sween & D. T. Campbell, A Study of the Effect of Proximally Autocorelated Error on Tests of Significance for the Interrupted Time Series Quasi-Experimental Design 31-32, Figs. 11 & 12 (mimeographed Research Report, Dept. of Psychology, Northwestern University, 1965). These figures also will appear in D. T. Campbell, Reforms as Experiments, Am. Psychologist (to be submitted).
4. Instability has not been singled out as a specific threat to validity in previous discussions of quasi-experimental design, although the discussion of tests of significance in such situations has implied it. Tests of significance obviously do not provide “proof” relevant to the many other sources of invalidity, but they are relevant to this one plausible rival hypothesis even where randomization has not been used.
5. This issue is extremely complex. In ordinary correlation, the regression is technically toward the mean of the second variable, not to the mean of the selection variable, if these means differ. In time-series, the regression is toward the general trend-line, which may of course be upward or downward or unchanging. A more expanded analysis of the regression problem in correlation across persons is contained in Campbell & Clavton (1961) and in Campbell & Stanley (1963), both supra note 1.
6. S. C. Dodd, A Controlled Experiment on Rural Hygiene in Syria (1934).
7. D. T. Campbell, Quasi-Experimental Design in 5 Int'l Encyc. Soc. Sci. 259 (Sills ed. 1968).
8. J. Sween & D. T. Campbell, supra note 3. The tests thus biased include tests of slope and intercept provided by H. M. Walker & J. Lev, Statistical Inference 390-95, 399-400 (1953). Note that this invalidates the discussion of tests of significance in Campbell, From Description to Experimentation, supra note 1, at 220-30. The “Clayton test” presented there was found in the Monte Carlo simulation by Sween & Campbell to have additional errors leading it to be too optimistic.
9. A. M. Mood, Introduction to the Theory of Statistics 297-98 (1950).
10. G. V. Glass, Analysis of Data on the Connecticut Speeding Crackdown as a Time-Series Quasi-Experiment, 3 L. & Soc‘y Rev. 55-76 (1968); T. O. Maguire & G. V. Glass, A Program for the Analysis of Certain Time-Series Quasi-Experiments, 27 Educational and Psychological Measurement 743-50 (1967); G. V. Glass, G. C. Tiao, & T. O. Maguire, Analysis of Data on the 1900 Revision of German Divorce Laws as a Time-Series Quasi-Experiment, 3 L. & Soc‘y Rev. (1969) (in press).
11. G. E. P. Box & G. C. Tiao, A Change in Level of a Non-stationary Time Series, 52 Biometrika 181-92 (1965); G. E. P. Box, Bayesian Approaches to Some Bothersome Problems in Data Analysis in Improving Experimental Design and Statistical Analysis (J. C. Stanley ed. 1967).
12. The classic reference is E. H. Sutherland, White Collar Crime (1959). See also H. L. Ross, Traffic Law Violation: A Folk Crime, 8 Social Problems 231-41 (1961).
13. E. G. Boring, The Nature and History of Experimental Control, 67 Am. J. Psychology 573-89 (1954).
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