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Multiple Group Time-Series Design

Author

Listed:
  • James Algina

    (University of Florida)

  • Stephen F. Olejnik

    (University of Florida)

Abstract

Configurations of means denying treatment effectiveness are presented for a multiple group time-series design. The configurations imply a sequence of null hypotheses. Failure to reject all of these hypotheses means the treatment effect is not supported. Rejection of any one of the hypotheses leads to tests of more detailed hypotheses. The rejection of these hypotheses can provide support for a treatment effect. Since both univariate and multivariate test criteria can be used to test the hypotheses, the procedure can be applied to data sets that have fewer subjects than occasions of measurement.

Suggested Citation

  • James Algina & Stephen F. Olejnik, 1982. "Multiple Group Time-Series Design," Evaluation Review, , vol. 6(2), pages 203-232, April.
    • Handle: RePEc:sae:evarev:v:6:y:1982:i:2:p:203-232
    DOI: 10.1177/0193841X8200600203
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    References listed on IDEAS

    as
    1. Henry Kaiser & Kern Dickman, 1962. "Sample and population score matrices and sample correlation matrices from an arbitrary population correlation matrix," Psychometrika, Springer;The Psychometric Society, vol. 27(2), pages 179-182, June.
    2. Kleinbaum, David G., 1973. "A generalization of the growth curve model which allows missing data," Journal of Multivariate Analysis, Elsevier, vol. 3(1), pages 117-124, March.
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