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Penalized generalized estimating equations approach to longitudinal data with multinomial responses

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Abstract

In high-dimensional longitudinal data with multinomial response, the number of covariates is always much larger than the number of subjects and when modelling such data, variable selection is always an important issue. In this study, we developed the penalized generalized estimating equation for multinomial responses for identifying important variables and estimation of their regression coefficients simultaneously. An iterative algorithm is used to solve the penalized estimating equation by combining the Fisher-scoring algorithm and minorization-maximization algorithm. We used a penalty term to regularize the slope part only because category-specific intercept terms should be included in the multinomial model. We conducted a simulation study to investigate the performance of the proposed method and demonstrated its performance using real dataset.

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Data availability

An example dataset is available at http://statgen.snu.ac.kr/software/PGEE_M/.

Code availability

An implementation of PGEE_M is available at http://statgen.snu.ac.kr/software/PGEE_M/.

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Acknowledgements

The authors like to thank Apio Catherine for English editing.

Funding

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant number: HI16C2037), and the Bio & Medical Technology Development Program of the National Research Foundation of Korea (NRF) (Grant number: 2013M3A9C4078158).

Author information

Authors and Affiliations

  1. Department of Statistics, Seoul National University, Seoul, 08826, Republic of Korea

    Md. Kamruzzaman & Taesung Park

  2. Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, 120-750, Republic of Korea

    Oran Kwon

  3. Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Republic of Korea

    Taesung Park

Authors
  1. Md. Kamruzzaman
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  2. Oran Kwon
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  3. Taesung Park
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Contributions

TP developed the idea and the method, MK performed all analysis. MK and TP draft the manuscript. TP revised the manuscript. OK provided the real data.

Corresponding author

Correspondence to Taesung Park.

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Conflict of interest

The authors declare no competing interests.

Ethics approval

The protocol was approved by the Institutional Review Board of Ewha Womans University (No 61–12). It is also registered in the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP, No. KCT0001241).

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Kamruzzaman, M., Kwon, O. & Park, T. Penalized generalized estimating equations approach to longitudinal data with multinomial responses. J. Korean Stat. Soc. 50, 844–859 (2021). https://doi.org/10.1007/s42952-021-00134-4

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  • DOI: https://doi.org/10.1007/s42952-021-00134-4

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