# 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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### How to interprete the outcome for quasi-binomial models

I am currently trying to understand the quasi-binomial model and have a rather basic question, which I seem not to be able to see an answer. The outcomes in binomial models are binary. So, 0 vs 1, car ...
1 vote
86 views

### Serious Coding Error in QIC function in geepack?

I believe the QIC function in geepack has a significant error. The function appears to incorrectly specify the independence model, which is needed to calculate QIC. The function will therefore often ...
20 views

### Can the offset variable be smaller than the outcome variable in a Poisson model?

I am modeling a number of bags of local crop harvested from a village in a given harvest over time. The village is divided into 48 communities and I have data on the total number of bags of crops from ...
43 views

### quasi-likelihood estimates of beta

working through Peter McCullagh's glm book and having a hard time with understanding quasi-likelihood. I'm working on this question below and I think I need to find the quasi-likelihood estimates and ...
25 views

### R package for spatial regression

I want to model counts of a beetle (B) as a function of three continuous dependent variables (PC1, PC2, RL), weighted by a fourth variable (W) using either poisson or quasipoisson regression with ...
67 views

### quasi likelihood for ungrouped binary data

I read in one of the textbooks that for ungrouped binary data the dispersion parameter should always be $\phi = 1$. Do you know why it is the case?
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### Find the optimal linear combination of the following estimating function / quasi-score

Consider a random variable $Y_1 \sim Bin(n,\theta)$ and $Y_2 \sim Bin(n,\theta^2)$ where $Y_1$ is independent from $Y_2$. Consider the residuals $R_1 = Y_1 - n\theta$ and $R_2 = Y_2 - n\theta^2$. Find ...
167 views

### Appropriate Regression Model for Proportions and Rate Data

I have a problem where my dependent variable is given as a click-through rate and thus bounded [0,1]. While I have the traffic for each sample (a combination of design factors) and could reconstruct a ...
1 vote
143 views

### Comparing performance of Quasi-binomial model and Beta-binomial model

I read some books in biostatistics about fitting binary date with Beta-Binomial regression model and Quasi-Binomial regression model. It proposes a setting: Setting: Assuming we have a sequence of ...
52 views

### Correct GLM or NLS to model exponential model with response variable with positive and negative values

I have been struggling to find the right way to model this dataset, this is a Data Frame with the dataset: ...
179 views

### How to Report the Results of a Quasi-Poisson Regression (APA)

What statistics (i.e. F-statistic, t-value, p-value, etc.) would be essential or desired when presenting a Quasi-Poisson regression. And if possible, how do you get these values in R if you have a ...
12 views

### how to interpret the summary of a glm poisson [duplicate]

I need a little help with the interpretation of my model's summary. First, here is the model : ...
1 vote
62 views

### How to calculate model weight for GLM-quasi poisson model

I am running several models with the quasi-Poisson family, I have calculated QAIC for each model but I wanted to know the weight of each individual model. I tried AICcmodavg but it did not work. Is ...
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### If my data is overdispersed when binomial but not when Poisson does that alone mean I should use Poisson GLM?

Top is Poisson, bottom is Binomial Source of variation is different people observed over a week long period. 118 people to be exact. want to make predictions about the proportion of days/week one ...
1 vote
48 views

### Avoiding data dredging with quasibinomial GLMs

Because my data is a bit overdispersed I am using quasibinomial GLM to analyse them however this means I cannot use AICs to compare my models. I am therefore using drop1 and update functions to do ...
1 vote
42 views

### Equivalence between prediction interval and hypothesis test on Poisson predicted values with 2/3 power transformation

I fitted a quasi-Poisson regression model to predict the value of a certain counting variable. Once the predicted value $\widehat{\mu_{0}}$ was obtained, I calculated the upper limit of its prediction ...
1 vote
52 views

### Overdispersion in logistic model

I'm relatively a newbie in R, and I've been trying to make a silly example of logistic regression to predict, according to Age and Sex whether someone dies of corona or not. I'm from Colombia, so my ...
555 views

### Interpreting coefficents on quasibinomial model

This might seem like a pretty basic question but I've scoured seemingly everywhere and can't get a definitive answer. I have a response parameter "rr" bound by 0-1 which is essentially the ...
344 views

### MASS::glmmPQL diagnostic

I am fitting models with MASS::glmmPQL of the form ...
2k views

### Quasi Poisson vs Negative Binomial [duplicate]

I read in several sources that the Quasi Poisson model and the Negative Binomial, should produce (on average) the same results. I tried a simple example and, although very close to each other, the ...
206 views

### Testing for endogeneity in a negative binomial model

I'm trying to fit a negative binomial model to my data because the dependent variable exhibits overdispersion. However, one of my reviewers is insisting that I also test for endogeneity. He or she is ...
328 views

### Interpreting interaction among 2 categorical IV in quasi-poisson regression

In my dataset, I'm looking at the impacts of developmental and immune phenotypes on morbidity- specifically, I want to determine if developmental phenotype has an effect on the difference in morbidity ...
32 views

### Can we mix conclusions from Poisson and Quasi-Poisson?

Currently I'm working with ecological studies, where my response is a count variable. I need to estimate several models, each one represents a city. Afterwards I aggregate them to obtain meta-analysis ...
1 vote
310 views

### Whats the difference between logistic regression and fractional response model? [duplicate]

Can anyone tell me the theory behind fractional response model, how it really works? I wonder if the logistic regression works only with binary variable {0,1}, why when conducting a GLM with ...
1 vote
181 views

### Strange output for pairwise comparisons on glm with quasi-binomial distribution

I'm new to CrossValidated - I've read up on how to ask questions properly but sorry if I do anything slightly wrong. My data is showing whether microplastics were present or absent in the gut of fish ...
1 vote
316 views

### "scale" in logistic regression

I am working on translating some R code into Python's statsmodels package, chiefly some logistic regression work that I've done, when I came across the following in ...
194 views

### Two intercepts for zero-truncated negative binomial model using VGAM

I am trying to understand the first and second intercept for the zero-truncated negative binomial regression model I estimated using VGAM. Below is my syntax: ...