MNL63

    Just-About-Right (JAR) Scales: Design, Usage, Benefits, and Risks

    Recipient of the 2013 Charles B. Dudley Award

    Rothman Lori, Parker Merry

    Pages: 120

    Published: 2009

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    This new ASTM manual is a comprehensive guide on the use of JAR scales in consumer testing, including their application, construction, analysis, and interpretation. It also identifies the risks associated with the use of JAR scales and ways to reduce those risks.

    JAR scales measure levels of a product's attribute relative to a respondent's theoretical ideal level. These scales have an anchored midpoint of "just-about-right" or "just right", and endpoints anchored to represent intensity levels of the attributes that are higher and lower than ideal.

    Manual 63 also includes numerous case studies for the analysis of JAR scale data and alternatives to JAR scales.

    This is a "must have" reference for professionals who use JAR scales when conducting consumer research.


    Table of Contents

    Structure and Use of Just-About-Right Scales
    Rothman L., Parker M.

    Appendix A: Graphical Data Display
    Conley C.

    Appendix B: Graphical Scaling
    Goldman A., Mazur J.

    Appendix C: Percent Difference from Norm and Percent Difference from Just Right
    Gaskin G., Keith J.

    Appendix D: The Mean
    Rothman L.

    Appendix E: Mean Direction and Mean Absolute Deviation
    Jones V.

    Appendix F: Mean versus Scale Mid-Point
    Pitts S.

    Appendix G: Methods for Determining Whether JAR Distributions are Similar Among Products (Chi-Square, Cochran-Mantel-Haenszel (CMH), Stuart-Maxwell, McNemar)
    Fritz C.

    Appendix H: A Proportional Odds/Hazards Approach to JAR Data
    Xiong R., Meullenet J.

    Appendix I: Student's t-Test—Analysis of Variance of Two Samples
    Parker M.

    Appendix J: Analysis of Variance (ANOVA)
    Parker M.

    Appendix K: Thurstonian Ideal Point Modeling
    Delwiche J.

    Appendix L: Penalty Analysis or Mean Drop Analysis
    Schraidt M.

    Appendix M: Using Grand Mean versus Mean of the Proportion of Respondents Who Scored the Product JAR
    Plaehn D., Stucky G., Lundahl D., Horne J.

    Appendix N: A Regression-Based Approach for Testing Significance of JAR Variable Penalties
    Plaehn D., Horne J.

    Appendix O: Bootstrapping Penalty Analysis
    Xiong R., Meullenet J.

    Appendix P: Opportunity Analysis
    Gualtieri T.

    Appendix Q: PRIMO Analysis
    Shvartsburg E.

    Appendix R: Chi-Square
    Templeton L.

    Appendix S: Biplots, Correspondence Analysis, and Principal Components Analysis
    Elizabeth H., Cindy F.

    Appendix T: Correlation
    Takkunen A.

    Appendix U: Regression
    Herskovic J.

    Appendix V: Preference Mapping from JAR Data Using Tree-Based Regressions
    Meullenet J., Xiong R.

    Appendix W: Application of JAR Data to Preference Mapping Using Dummy Variables
    Xiong R., Meullenet J.

    Appendix X: Collecting Intensity and Hedonic Information Separately
    Gaskin G., Keith J.

    Appendix Y: Designed Experiments
    Parker M., Carr B.

    Appendix Z: Ideal Scaling
    Goldman A., Mazur J.

    Bibliography


    Committee: E18

    Paper ID: MNL63-EB

    DOI: 10.1520/MNL63-EB

    ISBN-EB: 978-0-8031-6739-1

    ISBN-PRINT: 978-0-8031-7010-0


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    MNL63-EB

    MNL 63