# Questions tagged [quasi-likelihood]

In GLMs, quasi-likelihood estimation is a way to allow over- or under-dispersion by choosing an appropriate variance function.

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### Validity of AIC When Comparing Models with Varying Dispersion Parameters

I'm currently making a binomial model with a logit link, which is parameterised as a quasibinomial since I'm allowing it to calculate the dispersion parameter. I was wondering, since changes to the ...
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### How much dispersion is too much for quasipoisson regression?

Quasipoisson regression goes beyond standard poisson regression in taking into account overdispersion (whereby the dependent variable's variance is much greater than its mean). This is explained at ...
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1 vote
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### Calculate weight for GLM-quasi poisson model

I am running several models with the quasi-Poisson family. I am looking at data from vulture restaurants. Vulture count was modelled at each site as a function of either a linear or quadratic effect ...
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### How to derive standard errors of regressors in quasi-Poisson regression?

Suppose I want to relax a Poisson Regression to allow for overdispersion and apply a quasi-likelihood approach: $$E[y_i|x_i] = exp(x_i^T \beta)$$ $$Var[y_i|x_i] = \phi \cdot \mu_i$$ In other words, ...
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### Diagnostics and assumptions for Fractional Logistic Regression

I am investigating the effects of Variable X on Y'. Y' is a bounded, non-negative integer. So I have divided Y' by its upper bound to obtain a fraction Y which is in [0,1]. I am following a study ...
998 views

### The statistical model equivalent to this R formula

This is how my model is written in R: glm(formula = prop ~ A * B * C * D , family = quasibinomial, data = data, weights = w) This is a quasibinomial ...
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### Overdispersion Mixed generalized linear model

I am running a mixed generalized linear model to analyze insect capture in a baited trap. The experiment consisted of 3 separate cages, in each one one treatment (C+, C- or T) and 10 insects were ...
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### Given that quasibinomial/quasipoisson reg models overdispersion, why ever use normal bin/poiss regression if quasi is more flexible?

In reading about quasibinomial regression: The quasi-binomial distribution, while similar to the binomial distribution, has an extra parameter 𝜙 (limited to |𝜙|≤min{𝑝/𝑛,(1−𝑝)/𝑛} ) that attempts ...
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### Coefficients in quasibinomial regression and model prediction plots

I'm using two quasibinomial models. In the first model, the dependent variable is the proportion x of successes in experiment A. In the second model, the dependent variable is the proportion y of ...
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### Profile (quasi-)likelihood score tests

Suppose I have a log-likelihood or quasi-log-likelihood for my data in terms of the parameter vectors $\theta$ and $\psi$: $$L(\theta;\psi)=\frac{1}{T}\sum_{t=1}^T{\log{f(y_t|\theta;\psi)}}.$$ (I am ...
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### Can I use quasi-binomial regression on proportion data in this way?

prop.pass = proportion of students who passed the exam num = number of students who sat the exam ...
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### Poisson fixed effects model in pglm estimating time-invariant predictor

I am analyzing panel data on various municipalities (id_mun) over several years using the pglm package in R. My dataset contains a variable "treatment" which is continuous but is time-...
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### Quasibinomial GLMM with LASSO regularization in R

I am currently assessing drivers of deforestation using a GLM (generalised linear model) with LASSO regularization (using package glmnet in R). As the response variable is % of area deforested I have ...
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### Does binomial regression weight some observations more heavily than other?

I am performing a quasibinomial regression, where each subject has an unfixed number of trials. So one subject may have had 5 trials while another had 90. In R the regression equation follows: glm(...
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### Comparing the marginal effect of a GLM to the OLS estimates

My question is, whether there is any way to (somewhat) compare the marginal effect of a GLM estimate to an OLS estimate. As in, "since the OLS and GLM results are very similar, I will favour OLS ...
• 528
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### Comparing the marginal effects of glm output to polr output

I have a dependent variable that is technically ordinal, so I ran a ordered probit model (polr). However, an ordered probit model does not produce any residuals ...
• 528
1 vote
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### How flexible is Stata's ivpois? Could I use it for a (quasi) binomial distribution?

According to this post on statalist, Stata's ivpois (an instrumental variable approach) is pretty flexible, with very little assumptions. The problem mentioned in ...
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### How to do a Control Function (CF) / Two Stage Residual Inclusion (2SRI) with an ordinal dependent variable in the first stage and a glm in the second

I am trying to use a Control Function (CF) / Two Stage Residual Inclusion (2SRI) approach, because the modeled relationship that I am trying to estimate is non-linear (my dependent variable has a ...
• 528
1 vote
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### Getting the (Stata) margins from fractional regression (=glm with family quasibinomial) for an ordinal variable in R

I first found this really nice Stata video on fractional regression (the dependent variable is a proportion including 0 and 1). I am especially interested in how he applies the margin approach to ...
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