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Robust Negative Binomial Regression/Evidence
Method evidence record

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.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Robust Negative Binomial Regression
Taxonomic method record · 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
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Related methods

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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.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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