# Questions tagged [generalized-linear-model]

A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "general linear model" which extends the ordinary linear model to general covariance structure and multivariate response.)

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### Negative Binomial Regression

I had a question regarding negative binomial regression. My data uses COVID-19 deaths (y-intercept), and COVID-19 positive tests in California. I would like to try and use the regression formula to ...
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### Model comparison for nested regression models that are not symbolically nested

Say I have two nested models and I want to compare them, but they are parameterized differently so that no simple constraint (i.e., setting coefficients to 0) on the larger model corresponds exactly ...
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### nlme How to extract and understand the coefficients of the variance function

I am using nlme to fit heteroskedastic residual variance as a function of covariates. I am not sure how to extract and understand the values produced by ...
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### Help interpreting GLM interaction effect (Poisson with offset)

I've modelled a count variable using a Poisson glm and an offset variable. I'm looking at the effect of sampled year on the number of times people who are 'old' ( > age x) perform a behaviour ...
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### Adding interaction to regression: main effect AND interaction non-significant

I've used two models on my dataset: Model 1: clinical score ~ X + Z: both X and Z are significant. Model 2: clinical score ~ X + Z + X*Z: X is not significant anymore, and neither is the interaction, ...
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### LOOCV test error is different by mannually "for() loop" or cv.glm() [closed]

It's about Question 7 in Chapter 5 of book "An Introduction to Statistical Learning with Applications in R". Below is part of the question's text: In Sections 5.3.2 and 5.3.3, we saw that ...
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### Lagged Dependent Variable in Bayesian Linear Regression

I'm constructing a Bayesian General Linear model to try to model the number of customers a business has. Essentially Market Mix Modelling. I believe the number of customers to be explained by the ...
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### GLMM for not so gaussian data

I am having an issue with GLMM and hope you could advice me. So basically I have data from microscopy experiment of three independent groups (variable: subfolder) nested within 4 experimental ...
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### Linear models to compare SNP categories between patients

I have 8 patients (GROUP: 3 healthy, 5 disease). For each patient, I determined single nucleotide polymorphisms (SNPs) and annotated the effect of the SNPs (EFFECT_CATEGORY). Each SNP (~3000 per ...
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### Testing the difference between two Root Mean Square Error values for statistical significance [duplicate]

I would like to compare the predictive power of 2 models. The models are meant to model count data and respective probabilities. I am using two metrics as means of comparison: Root Mean Square Error ...
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### why does LASSO regression return unstandardized coefficients [closed]

I have more general questions that does not refer to a coding issue. Why does LASSO regression require standardization of the predictors but return unstandardized coefficients (glmnet function - https:...
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### How to approach GLMs using data with beta distribution in R?

I'm trying to run some models on bee presence with five predictor variables. A snippet of the data is attached, but essentially I measured floral abundance and richness, calculated floral evenness and ...
1 vote
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### What are the degress of freedom in the summary output for GLMs in R?

I am currently self-studying GLMs with the book "Generalized Additive Models An Introduction with R" and I am a bit confused regarding the degrees of freedom in the summary output for GLMs ...
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### Questions regarding the definition of the deviance in the context of GLMs

I've been self-studying GLMs and I have some questions regarding the deviance in the context of GLMs. In Generalized Additive Models An Introduction with R, the author defines the deviance of a model ...
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### Modeling trend in binary variable over time

I have a dataset with repeated measures per subject, with 100 subjects. My outcome of interest is a binary variable assessed on an hourly basis, of if the subject met a threshold value through a test. ...
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### Comparing performance of probabilistic regression models - how to adapt Brier score?

Suppose I have two predictions models, Model 1 and Model 2. I have a dataset containing observations, features and actual outcomes. For each observation, the “outcomes” (i.e. predictions) that the ...
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### Relating animal sightings with land cover - poisson, negative binomial, zero inflated and then LOST

I have a number of sightings of animals in a location (an island). The sightings are opportunistic (corpses people stumble upon) and happen in different land covers. I am supposed to investigate if ...
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### log ratio transformation on data and GLM testing on 4-way olfactometry results

I recently completed an experiment looking at 40 individual aphids movement over 20 minutes inside a 4-arm olfactometer with 3 controls (no scent, uninfected aphids, agar) and aphids infected with the ...
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### Which is the correct regression model for predicting the association of climate with Julian days nested within decades?

Below is a reproducible example: ...
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### How to derive GEE from GLM?

I am now reading the lecture note from: https://dept.stat.lsa.umich.edu/~kshedden/Courses/Regression_Notes/gee.pdf Why do we have $V_{i}^{-1}(y_{i}-\mu_{i})$? I cannot link the last equation on page ...
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### GLM Multiple Comparisons

I am performing several Generalized Linear Models in my analysis and I am wondering which method to use for adjusting p-values due to multiple comparisons. I have 4 outcomes (judgement of intensity ...
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### How to report ANOVA results when comparing to negative binomial models?

I want to report the results of an ANOVA test used to compare two negative binomial models in R: anova(model1, model2, test = "Chi") I receive the ...
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### Multiple regression with two continuous predictor variables with R

I'm trying to find a suitable multiple model (with two continuous predictor variables) for my data and I'm not sure if a linear model with lm() would be sufficient ...
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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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### Difference between regression methods

When to use logistic regression and when to use beta regression in statistical modeling for given data? How do know the difference between them? And when can I fit just a linear regression and not ...
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### Finding the best way for combining features non-linearly within a linear regression

Problem Statement I have a set of two features, $X_1$ and $X_2$ that I combine to try and predict a target variable in a regression of the form: $Y_0 = \frac{X_1 - X_2}{X_1 + X_2}$. You can think of ...
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