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On Regression Standardization for Moments

Author

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  • CLIFFORD C. CLOGG

    (Pennsylvania State University)

  • SCOTT R. ELIASON

    (Pennsylvania State University)

Abstract

Polynomial regression models can be used to standardize means of endogenous variables for moments of exogenous variables. In other words, standardized means obtained from polynomial models adjust for group differences in location and shape parameters that characterize distributions of exogenous variables. The suggested approach is a natural extension of the conventional method of regression standardization for means (or first moments) of exogenous variables, and it is a more direct analogue to standardization methods used in demography. We also give simple methods that can be used to test the significance of various components of a difference between two means.

Suggested Citation

  • Clifford C. Clogg & Scott R. Eliason, 1986. "On Regression Standardization for Moments," Sociological Methods & Research, , vol. 14(4), pages 423-446, May.
  • Handle: RePEc:sae:somere:v:14:y:1986:i:4:p:423-446
    DOI: 10.1177/0049124186014004004
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    References listed on IDEAS

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    1. Evelyn Kitagawa, 1964. "Standardized comparisons in population research," Demography, Springer;Population Association of America (PAA), vol. 1(1), pages 296-315, March.
    2. Clifford Clogg, 1978. "Adjustment of rates using multiplicative models," Demography, Springer;Population Association of America (PAA), vol. 15(4), pages 523-539, November.
    3. Malkiel, Burton G & Malkiel, Judith A, 1973. "Male-Female Pay Differentials in Professional Employment," American Economic Review, American Economic Association, vol. 63(4), pages 693-705, September.
    4. F. L. Jones & Jonathan Kelley, 1984. "Decomposing Differences between Groups," Sociological Methods & Research, , vol. 12(3), pages 323-343, February.
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    1. Lonnie Stevans & Charles Register & David Sessions, 1992. "Simulating bias in the estimator of labor market discrimination," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 27(2), pages 157-168, September.

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