A parametric model fitting time to first event for overdispersed data: application to time to relapse in multiple sclerosis

DOI10.1007/S10985-011-9207-ZzbMath1322.62089OpenAlexW2082745236WikidataQ34074336 ScholiaQ34074336MaRDI QIDQ746130

Eric Henninger, Maria Pia Sormani, Paola Siri

Publication date: 15 October 2015

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10985-011-9207-z

zbMATH Keywords

negative binomial distributionrecurrent eventsmixed Poisson processestime to eventmultiple sclerosis relapses

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10)

Related Items (1)

Evidence synthesis for count distributions based on heterogeneous and incomplete aggregated data

Uses Software

• DEseq
• COUNT

Cites Work

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• On the extended Polya process and some of its interpretations
• Non-life insurance mathematics. An introduction with stochastic processes.
• Negative Binomial Regression
• Zur statistischen analyse des gemischten Poissonprozesses, gestützt auf Schadeneintrittszeitpunkte
• Applied Probability and Queues

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