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Logistic Regression Based on Individual-Level Predictors and Aggregate-Level Responses

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  • Zheng Xu

    (Department of Mathematics and Statistics, Wright State University, Dayton, OH 45435, USA)

Abstract

We propose estimation methods to conduct logistic regression based on individual-level predictors and aggregate-level responses. We derive the likelihood of logistic models in this situation and proposed estimators with different optimization methods. Simulation studies have been conducted to evaluate and compare the performance of the different estimators. A real data-based study has been conducted to illustrate the use of our estimators and compare the different estimators.

Suggested Citation

  • Zheng Xu, 2023. "Logistic Regression Based on Individual-Level Predictors and Aggregate-Level Responses," Mathematics, MDPI, vol. 11(3), pages 1-12, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:746-:d:1054879
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    References listed on IDEAS

    as
    1. Hong, Yili, 2013. "On computing the distribution function for the Poisson binomial distribution," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 41-51.
    2. Palm, F. C. & Nijman, T. E., 1982. "Linear regression using both temporally aggregated and temporally disaggregated data," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 333-343, August.
    3. Hsiao, Cheng, 1979. "Linear regression using both temporally aggregated and temporally disaggregated data," Journal of Econometrics, Elsevier, vol. 10(2), pages 243-252, June.
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