方法证据记录

Robust Negative Binomial Regression

Robust Negative Binomial Regression models overdispersed count outcomes using the negative binomial distribution while protecting coefficient inference against misspecification of the variance function. It pairs maximum-likelihood estimation of the mean and dispersion parameters with sandwich (Huber-White) standard errors, yielding valid tests even when the assumed variance structure is only approximately correct.

Sources recorded, not reviewed

源记录

引文逐字复制自方法源记录。这些引文不代表任何层级的验证。

分类方法记录 · regression-model / statistics

Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. · ISBN 978-0521198158
Zeileis, A., Kleiber, C., & Jackman, S. (2008). Regression Models for Count Data in R. Journal of Statistical Software, 27(8), 1–25. · DOI 10.18637/jss.v027.i08

打开完整方法

精选声明

声明已持久化到证据分类账中，每个声明都有自己的评估。

尚无精选声明

当分类账中没有声明时，此视图不会自行创建声明评估。

相关方法

从方法图中生成，显示为机器建议的关系 — 不推断任何证据声明。

Taxonomic bucketGeneralized Linear Modelmachine-suggested · Relational suggestion, not evidence.Same method familyNegative Binomial Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyPoisson Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Poisson Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketZero-inflated modelmachine-suggested · Relational suggestion, not evidence.