Unformatted text preview: Xi 1 + β2 Xi 2 + . . . + βp Xip ) = exp(xt β ).
The model is
Yi ∼ Poisson(λi ); λi = ηi θi = ηi exp(xt β ), i = 1, 2, . . . , n
log (λi ) = log (ηi ) + β1 Xi 1 + β2 Xi 2 + . . . + βp Xip
= offset + linear predictor UNM For a covariate Xj , factor is absent Xj = 0 and factor
present if Xj = 1.
The Rate ratio (RR)
RR = E (Yi |present)
η exp(β0 + β1 )
= exp(β1 )
E (Yi |absent)
ηi exp(β0 ) If a covariate is increased by one unit, exp(β1 ) is the effect
due to the increase.
In general, the RR for cov...
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This note was uploaded on 01/27/2014 for the course STAT 574 taught by Professor Gabrielhuerta during the Fall '13 term at New Mexico.
- Fall '13
- Poisson Distribution