Regression Analysis of Count Data¶
Cameron, A. C., & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Poisson Event-Process Model
- That overdispersion is the Poisson model failing informatively — its equidispersion fingerprint (variance equals mean) is exactly what makes the failure legible.
This sourceExplains that a Poisson model has equal mean and variance, so variance exceeding the mean is a visible overdispersion diagnostic of model mismatch.
- That overdispersion is the Poisson model failing informatively — its equidispersion fingerprint (variance equals mean) is exactly what makes the failure legible.
- Poisson Rate Model
- Real streams are frequently overdispersed — events cluster, arrivals correlate, the rate itself drifts — so their variance exceeds their mean, and a strict Poisson model then reports intervals that are too narrow and significances that are too strong, manufacturing false confidence.
This sourceDefines overdispersion as variance exceeding the mean and explains that ignoring it in Poisson inference can understate uncertainty and overstate significance.
- Real streams are frequently overdispersed — events cluster, arrivals correlate, the rate itself drifts — so their variance exceeds their mean, and a strict Poisson model then reports intervals that are too narrow and significances that are too strong, manufacturing false confidence.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Not recorded. Neither this nor any other of the 2 citations of this work carries a recorded support check.
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Registry ID ref:193f33982024 · see in the full table