IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v12y2022i2p21582440221091253.html
   My bibliography  Save this article

Norm-Referenced Scoring on Real Data: A Comparative Study of GRiSTEN and STEN

Author

Listed:
  • Mehmet Guven Gunver

Abstract

STEN (Standard Ten) is the most frequently preferred score generating method among the norm reference scores (e.g., percentile rank, STANINE) However, it is usually misleading because of the skewness presented with the data. In this study, rather than STEN, GRiSTEN (Golden Ratio in Statistics) approach is proposed to generate relatively fair outcomes. The GRiSTEN method acknowledges the effects of skewness by accounting for the contribution of each data element to the center point based on its specific location in the data stack. Generating norms using the GRiSTEN approach enables us to mark “the most capable†or “the least capable†scores regarding the test without involving too many arithmetic operations. In order to verify the applicability of the psychometric tests based on System Sigma run by Mevasis IT Consultancy in Turkey, a watch test, which is designed to observe respondents’ estimation of velocity, is carried out with a pilot group consisting of 407 male respondents aged between 30 and 50. By using GRiSTEN approach, it is shown that consistent outputs can be obtained without changing, ignoring, or transforming any elements regardless of the number of elements, skewness, distribution, and values of the data array.

Suggested Citation

  • Mehmet Guven Gunver, 2022. "Norm-Referenced Scoring on Real Data: A Comparative Study of GRiSTEN and STEN," SAGE Open, , vol. 12(2), pages 21582440221, April.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221091253
    DOI: 10.1177/21582440221091253
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440221091253
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440221091253?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tsiang, S C, 1972. "The Rationale of the Mean-Standard Deviation Analysis, Skewness Preference, and the Demand for Money," American Economic Review, American Economic Association, vol. 62(3), pages 354-371, June.
    2. Lutz Bornmann, 2013. "The problem of percentile rank scores used with small reference sets," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(3), pages 650-650, March.
    3. Ivan A. Canay & Joseph P. Romano & Azeem M. Shaikh, 2017. "Randomization Tests Under an Approximate Symmetry Assumption," Econometrica, Econometric Society, vol. 85, pages 1013-1030, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1577-1608.
    2. Hagemann, Andreas, 2019. "Placebo inference on treatment effects when the number of clusters is small," Journal of Econometrics, Elsevier, vol. 213(1), pages 190-209.
    3. Guo, Xu & Lien, Donald & Wong, Wing-Keung, 2015. "Good Approximation of Exponential Utility Function for Optimal Futures Hedging," MPRA Paper 66841, University Library of Munich, Germany.
    4. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
    5. Jinyong Hahn & Ruoyao Shi, 2017. "Synthetic Control and Inference," Econometrics, MDPI, vol. 5(4), pages 1-12, November.
    6. Joost M. E. Pennings & Ale Smidts, 2003. "The Shape of Utility Functions and Organizational Behavior," Management Science, INFORMS, vol. 49(9), pages 1251-1263, September.
    7. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jul 2024.
    8. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    9. Giovanni Mastrobuoni & David A Rivers, 2019. "Optimising Criminal Behaviour and the Disutility of Prison," The Economic Journal, Royal Economic Society, vol. 129(619), pages 1364-1399.
    10. Soosung Hwang & Steve Satchell, 2005. "Valuing information using utility functions: how much should we pay for linear factor models?," The European Journal of Finance, Taylor & Francis Journals, vol. 11(1), pages 1-16.
    11. Hartog, Joop, 2009. "A Risk Augmented Mincer Earnings Equation? Taking Stock," IZA Discussion Papers 4439, Institute of Labor Economics (IZA).
    12. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    13. Pennings, Joost M. E., 2004. "A marketing-finance approach towards industrial channel contract relationships: a model and application," Journal of Business Research, Elsevier, vol. 57(6), pages 601-609, June.
    14. Emmanuel Jurczenko & Bertrand Maillet & Paul Merlin, 2008. "Efficient Frontier for Robust Higher-order Moment Portfolio Selection," Post-Print halshs-00336475, HAL.
    15. David S. Jones & V. Vance Roley, 1981. "Bliss Points in Mean-Variance Portfolio Models," NBER Technical Working Papers 0019, National Bureau of Economic Research, Inc.
    16. Benjamin M. Friedman, 1980. "The Effect of Shifting Wealth Ownership on the Term Structure of Interest Rates," NBER Working Papers 0239, National Bureau of Economic Research, Inc.
    17. Holt, Matthew T., 1989. "Risk, Rational Expectations, and Price Stabilization in the U.S. Corn Market," Staff Papers 200480, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    18. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    19. Raskin, Rob & Cochran, Mark J., 1986. "Interpretations And Transformations Of Scale For The Pratt-Arrow Absolute Risk Aversion Coefficient: Implications For Generalized Stochastic Dominance," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(2), pages 1-7, December.
    20. Mateane, Lebogang, 2020. "Risk preferences, global market conditions and foreign debt: Is there any role for the currency composition of FX reserves?," EconStor Preprints 227484, ZBW - Leibniz Information Centre for Economics.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221091253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.