[R-sig-ME] Zero-inflated Poisson distribution

[Paul Metzner]

Hello!

I am analyzing eye-movement data with LMM and find it difficult to get my head around the regression counts. They are heavily zero-inflated, which, as far as I know, renders a simple Poisson GLMM improbable. Would the following (simplified) command do the zero-inflation justice?

m1 <- lmer(RBRC~COND+CPCU+COND:CPCU+DIR+COND:DIR+(1|SUBJECT)+(1|ITEM), cr, quasipoisson)
m2 <- lmer(RBRC~COND+CPCU+COND:CPCU+DIR+COND:DIR+(1|SUBJECT)+(1|ITEM), cr, poisson)

The outcome is dramatically different from a poisson LMM, with three effects hinging on the choice of distribution. I'm afraid m1 might be overestimating, since the numerical difference is miniscule. I uploaded histograms at http://amor.cms.hu-berlin.de/~metznerp/ghist_trc.pdf and http://amor.cms.hu-berlin.de/~metznerp/ghist_rbrc.pdf.

Best,
Paul

---
Paul Metzner

Humboldt-Universität zu Berlin
Philosophische Fakultät II
Institut für deutsche Sprache und Linguistik

Post: Unter den Linden 6 | 10099 Berlin | Deutschland
Besuch: Dorotheenstraße 24 | 10117 Berlin | Deutschland

+49-(0)30-2093-9726
paul.metzner at rz.hu-berlin.de
http://amor.rz.hu-berlin.de/~metznerp/