Quasi-likelihood is a function similar to but not likelihood, and it was introduced by Wedderburn (1974) and mainly used in generalized linear models.

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GEE in SPSS: the case of ever-decreasing QICc values

I've been using GEEs in SPSS 22 to analyze my dissertation data and have discovered an interesting problem: when trying to figure out which subset of model factors have the lowest QICc, and therefore ...
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145 views

GLM analogue of weighted least squares

The short version: I can fit a model using Weighted Least Squares, given a diagonal matrix of weights $W$, by solving $(X^TWX)\hat{\beta}=X^TWy$ for $\hat{\beta}$. Is there a GLM analogue? if so, ...
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147 views

How to handle underdispersion in GLMM (binomial outcome variable)

I'm working on the following model in R: ...
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57 views

Estimating the asymptotic distribution of a quasi maximum likelihood estimator

We consider the following GARCH(1, 1) model: $y_t = h_t \epsilon_t$ where $(\epsilon_t)_{t \in \{1, \dots, n\}}$ are i.i.d. random variables with mean 0 and standard deviation 1. $h_t = \omega + ...
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Difference between quasi-likelihood estimating equations, IEE and GEE?

What is the difference between quasi-likelihood estimating equations, and GEE? From a note Quasi-score function is for independent, over-dispersed data (Poisson or binomial), while GEE1 is for ...
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295 views

GEE, quasi-likelihood and what it generalizes

Wikipedia formulates Generalized Estimating Equations (GEE) as Given a mean model, $\mu_{ij}$, and variance structure, $V_{i}$, the estimating equation is formed via: $$ U(\beta) = ...
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182 views

Models for Generalized Estimating Equation?

From Wikipedia, Generalized Estimating Equation (GEE) is a method to estimate the parameters of a generalized linear model (with an exponential family distribution for the response). By reading other ...
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Weird behavior of Poisson, negative binomial, and quasipoisson GLM

I have some overdispersed count data (mean=8.6, var=263.5) that I am hoping to model using either a negative binomial (NB) or quasipoisson GLM. A rootogram suggests that the Poisson distribution is a ...
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Definition of dispersion parameter for quasipoisson family

I try to model quasi-poisson family in bugs language, to handle overdispersion. According to Introduction to WinBUGS for ecologists, this is done by: $log(\lambda_i) = f(x_i) + \epsilon_i$ $N_i \sim ...
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GLM quasi family with log transformation?

I am working on my thesis analysis, and I have some error data that's right-skewed. I log-transformed it and ran glm on it (gaussian, identity in R) weighted by sample size, and my data is still ...
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219 views

Using GLM with germination percentages

I have germination data in percentages (with a few zeros) and wish to fit a GLM on them to explore how different seed origins and levels of treatment affect them. My results are not exactly 'counts', ...
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Fitting a complex model of variance-vs-mean for quasi likelihood models? (in R)

I wish to deal with over dispersion of a Poisson model. Negative binomial (glm.nb), and quasi likelihood models (family=quasi in glm) do not offer a flexible enough structure of the variance-vs-mean ...