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    Author(s): Stanley J. Zarnoch
    Date: 2009
    Source: Res. Note SRS-17. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 20 p.
    Publication Series: Research Note (RN)
    Station: Southern Research Station
    PDF: View PDF  (4.06 MB)

    Description

    Five hypotheses are identified for testing differences between simple linear regression lines. The distinctions between these hypotheses are based on a priori assumptions and illustrated with full and reduced models. The contrast approach is presented as an easy and complete method for testing for overall differences between the regressions and for making pairwise comparisons. Use of the Bonferroni adjustment to ensure a desired experimentwise type I error rate is emphasized. SAS software is used to illustrate application of these concepts to an artificial simulated dataset. The SAS code is provided for each of the five hypotheses and for the contrasts for the general test and all possible specific tests.

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    Citation

    Zarnoch, Stanley J. 2009. Testing hypotheses for differences between linear regression lines. Res. Note SRS-17. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 20 p.

    Keywords

    Contrasts, dummy variables, F-test, intercept, SAS, slope, test of conditional error

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