ℓ 1 $$ {\ell}_1 $$ -Penalized Multinomial Regression:估计、推理和预测,应用于不同痴呆亚型的风险因素识别。

IF 1.8 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Ye Tian, Henry Rusinek, Arjun V Masurkar, Yang Feng
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引用次数: 0

摘要

高维多叉回归模型在实践中非常有用,但与逻辑回归模型相比,它受到的研究关注较少,尤其是从统计推断的角度来看。在这项工作中,我们分析了基于对比度的 ℓ 1 $$ {\ell}_1 $$ -penalized 多叉回归模型的估计和预测误差,并将去尾法扩展到多叉情况,为每个系数和单个假设检验的 p $$ p $$ 值提供了有效的置信区间。我们还研究了模型规范错误和非同分布数据的情况,以证明我们的方法在违反某些假设时的稳健性。我们应用去杂方法来识别不同亚型痴呆症进展过程中的重要预测因素。大量模拟结果表明,与其他推理方法相比,去杂方法更具优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
1 $$ {\ell}_1 $$ -Penalized Multinomial Regression: Estimation, Inference, and Prediction, With an Application to Risk Factor Identification for Different Dementia Subtypes.

High-dimensional multinomial regression models are very useful in practice but have received less research attention than logistic regression models, especially from the perspective of statistical inference. In this work, we analyze the estimation and prediction error of the contrast-based 1 $$ {\ell}_1 $$ -penalized multinomial regression model and extend the debiasing method to the multinomial case, providing a valid confidence interval for each coefficient and p $$ p $$ value of the individual hypothesis test. We also examine cases of model misspecification and non-identically distributed data to demonstrate the robustness of our method when some assumptions are violated. We apply the debiasing method to identify important predictors in the progression into dementia of different subtypes. Results from extensive simulations show the superiority of the debiasing method compared to other inference methods.

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来源期刊
Statistics in Medicine
Statistics in Medicine 医学-公共卫生、环境卫生与职业卫生
CiteScore
3.40
自引率
10.00%
发文量
334
审稿时长
2-4 weeks
期刊介绍: The journal aims to influence practice in medicine and its associated sciences through the publication of papers on statistical and other quantitative methods. Papers will explain new methods and demonstrate their application, preferably through a substantive, real, motivating example or a comprehensive evaluation based on an illustrative example. Alternatively, papers will report on case-studies where creative use or technical generalizations of established methodology is directed towards a substantive application. Reviews of, and tutorials on, general topics relevant to the application of statistics to medicine will also be published. The main criteria for publication are appropriateness of the statistical methods to a particular medical problem and clarity of exposition. Papers with primarily mathematical content will be excluded. The journal aims to enhance communication between statisticians, clinicians and medical researchers.
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