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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How to model suspected piecewise-linear data with a lasso GLM

My data consist ~130 observations. Each observation has several thousand features (including many collinear or otherwise useless features) and a position along a single spatial dimension. Some sets of ...
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Assessment of Geospatial Analysis and Poisson GLM Modeling for Accident Frequency with Cluster-Based Features

I have a serious doubt about the quality of this approach: Firstly, a geospatial analysis was conducted using accident frequency and wind speed data to segment the map of a country into clusters using ...
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Should I use negative binomial GAM?

I'm trying to model a data of presence and absence of birds in nest boxes. I look whether it's zero-inflated and it gave me this: ...
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interactions between variables using Generalized Linear Mixed Model in SPSS

I want to study which factors have an effect on the hormone PTH. PTH is used as a dichotome variable and is our outcome variable, the dependent variable. We're using generalized linear mixed models in ...
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Is this glm approach in r appropriate for determining differences (if any) between 8 groups with binary data?

I have been given a dataset to analyze looking at some herbicide treatments for invasive trees in three states with 3 sites in state 1, 2 sites in state 2, and 1 site in state 3. We hope to answer ...
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Is logistic regression with random effects appropriate for my problem?

My problem is the following: I have 1/0 "conversion" outcomes. I have samples from three groups: people who speak russian, people who speak japanese, people who speak portuguese. i expect ...
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meaning of this GLM defintion

The answer key says "Different link functions have different shapes and can therefore fit to different nonlinear relationships between the predictors and the target variable." Shouldn't we ...
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Is there a justification for the Bernoulli deviance in the R stats package?

Using the standard glm(...) function in R for Bernoulli regression, it appears that the residual deviance has the same value as the binomial deviance where each ...
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Equivalent of `aov` with `split` argument for contrasts in GLM in R

In case of linear models (LM) it is possible to get ANOVA with planned contrasts by using a contrast matrix and aov. Is there any equivalent of the same for analysis of deviance in case of ...
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Generalized Linear Models - Order of Parameters Matter?

I've got two models, the first model is my original model: ...
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Why is serial correlation a problem in GLMs?

I have learned that serial correlation is a problem in linear regression as the idiosyncratic error terms are correlated which leads to the variance function of the coefficients to be misspecified and ...
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Derivation of Newton-Raphson Method for Maximum Likelihood Estimation of GLM Parameter [closed]

I am currently self-studying Generalized Linear Models after learning about linear regression in my undergraduate study. My undergraduate program is not statistics so I have some difficulties in ...
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Gamma GLM goodness-of-fit diagnostics and remedies for double glm

I’m looking for some help in diagnosing a gamma GLM. I am not sure whether the apparently poor fit is to do with the fact that my glm models dispersion rather than the mean, whether I am ...
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Use of weights in a binomial model, with the response no longer a proportion

I am studying the factors that influence mosquito feeding behavior. In the experiments, N mosquitoes are exposed to a host for a duration t. At the end of this exposure, we count how many mosquitoes (...
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Highly Skewed Binary Response Variable 10% One Category, 90% Other

I have a highly skewed binary response variable in my dataset. I am having issues finding a model that meets all assumptions for a binomial distribution GLM, and I believe this may be correlated to ...
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Understanding the results of the GLM in R

I have data on the abundance of beetles I have collected (I have also done this for biomass of beetles and proportion of abundance represented by a particular functional group of beetles, but only ...
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Count prediction with Poisson Regression

Is it essential to have the data grouped in a Poisson regression? An example: I want to know the determinants of traffic accidents in a country through data from two cities. My 3 explanatory variables ...
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Multivariate analysis for non-normal variables

Edit: I am trying to produce a model in R in order to analyze the relationship between several variables. I am looking at the relationship between behaviour and dispersal of a population. Each ...
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Family Choice for GLM with 0-1 Dependent Variable

I want to analyze the relationship between the dependent variable "Knowledge_index" (va numeric variable ranging between 0 and 1, both inclusive) and several independent variables (type “...
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How can I best formulate my glmm if i want to test within individuals and within context for these individuals?

I am a beginner in using glmm, I have a question about which structure to test "within individual and within context". I have collected vocal data on 12 different individuals (animals) in a &...
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How do I check proportional odds assumption for cumulative link mixed models?

I am using ordinal R-package to fit a cumulative link mixed model to an ordered, categorical outcome (5 levels) using logit function as the link function. The model is a random intercepts only model. ...
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Distribution model for Multiple-choice Data?

I am running an experiment where I am testing the effects of three interventions (A,B,C) and measuring participants' performance via a multiple choice test with 5 questions. To perform hypothesis ...
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Split plot design - help with choosing the analysis

I have a split-plot design experiment with three levels (slope, then treatment within slope, then cages within each treatment), with the main response being a count of seedlings. South South ...
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Confidence interval for a variable which is function of the coefficients of a linear regression, $\frac{\hat{\beta}_1}{\hat{\beta}_2}$

Consider the following linear regression $$Y = \beta_1X_1 + \beta_2X_2 + \epsilon$$ Can I compute a confidence interval for the estimate of the quantity ? $$\frac{\beta_1}{\beta_2}$$ ...
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Fitting a complex GLM in R with probit link

I am trying to fit a probit model for binomial data as follows. \begin{equation} \tag{1} \%\textrm{alive} = \phi \ [ \textrm{a} - \textrm{b}t\ ] \end{equation} Where $\%alive$ is the dependent ...
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What is the advantage of running generalized mixed effect linear regression model with bayesian with non-informative prior vs frequentist approach?

I am curious as to whether the bayesian approach with non-informative prior (flat prior) is more suitable for generalized mixed effects linear model than frequentist approach and what the reasons may ...
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Generalized Linear Model optional weights

In Introduction to General and Generalized Linear Models by H. Madsen & P. Thyregod, the ML estimator for $\beta$ is defined in eq. 4.42 (p.106) as $$W(\beta) = \text{diag}\bigg\{\frac{w_i}{g'(\...
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Distribution of Penalized Regression Coefficients

For both linear and logistic regression we know that the coefficient vector $\hat\beta$ holds an asymptotic normal distribution, therefore the the distribution of the linear predictor $\hat\theta_i=x^...
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Correlation of GLM coefficent when Y is correlated

First to motivate the problem, let me start with a solved example. Say I have some fixed design matrix $X$ and random vectors $Y_1, Y_2, \dots, Y_N$ which have a normal distribution. I can get the ...
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How to check assumptions of a binomal GLM with categorical predictors

I have a data set that looks like this (subset below): ...
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GLMM not working if I specify the distribution as gamma

Following is the histogram and Q-Q plot of deceleration data retrieved from driving simulator experiment. As the data is not normally distributed, I am using generalized linear mixed model to analyze ...
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discovering latent values, with extremely high cardinality categorical features

I think i know what I need to do here, but I want a gut check, and i might need some direction on specific packages and processing to use. My goal is to discover the latent value of products that ...
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Are cumulative link models multinomial generalized nonlinear models?

I am trying to understand the following statement (Christensen and Brockhoff, 2013): Cumulative link mixed models is a member of a class of models sometimes referred to as multivariate generalized ...
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How to test for significant differences among percent increases between two unbalanced samples from each of 10 treatments?

I am trying to figure out how best to analyse fruit weight data from an experiment involving samples of both open-pollinated and unpollinated fruit from each of 10 different pollination treatments. I ...
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How to deal with overdispersion with glmmTMB for generalized linear models

I'll try to make it as brief as possible. I'm trying to fit a glm to echolocation clicks count data using the glmmTMB function. I started with a Poisson glm and ...
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Poisson regression with random effect using pre-post data

I have data on outcomes collected across several clinics. The outcome is an integer indicating days until treatment initiation. Outcome data were collected at baseline and follow up, and are collected ...
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Interpretation of OR in logistic mixed model

I am new to mixed models and am unsure about the interpretation of the OR results. I have a significant main effect of OR = 1.08, 95% CI [1.01, 1.16], p = 0.025. How can I interpret this? The variable ...
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Interaction and correlation between two variables?

I fitted a generalised linear model to my medical retrospective data, in which there is a continuous variable x a binary variable y If y is TRUE, x will have high values. Because whatever causes y to ...
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Overdispersed and zero-inflated count data

I have a dataset with social media posts and like to predict the number of likes a post receives. So I fit a Generalised Linear Model (GLM). I am relatively new to GLMs but find them super cool. ...
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How to interpret the average rate of NB-GLM when offset is involved?

My question is on how to interpret the coefficients of a negative-binomial GLM that included an offset. My dataset is a clinical trial where patients got one of two treatments (A or B) and stayed in ...
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Comparing the PCA modes from two different covariances

Suppose I have a set of $n$ vectors $x_i$ arranged as columns of a matrix $X$ and I want to perform PCA to reduce the number of dimensions needed to explain some set of observations. I have developed ...
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Interaction terms of one variable with many variables

Suppose that I'd like to analyze the relationship between Y and A, and A moderated by B, and A moderated by C, and A moderated by D, .... and A moderated by J. I'd then formulate my regression as ...
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Definition of priors for GLM

I am building a generalized linear model using the logit function in R using JAGS. Whenever I saw code people only define priors for the parameters of the model, but never for parameters of the ...
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Gamma GLMM in R with unusual data format

I have been trying to find how hummingbirds' behaviors and sex correlate to the interval between their vocalizations. The intervals have a non-normal distribution. Each observation is not independent (...
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What is the best method to analyze multiple and matched linear numeric response?

I have a survey with ten questions, and participants should answer each one reporting how frequent is his/her symptom on a scale from 0 to 10. These question are repeated twice considering "Now&...
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Quadratic relationship binary variable and a factor [duplicate]

I have a set of data collected during over a year. We have created a variable called “bimonthly” (1=January-February; 2=March-April; 3=May-June; 4=July-August; 5=September-October and 6=November-...
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overall (allfit) and incremental cumulative association (cumfit) - R Package 'dlnm'

I am conducting research on the impact of between radiation dose and incidence of cancer in radiation epidemiology. To further explore this topic, I would like to utilize distributed lag non-linear ...
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GLM with log link vs linear regression with logarithmic transformation parameter estimation

I am trying to calculate the parameter estimates of GLM with log link and normal distribution and the linear regression with logarithmic transformation. For the first I get the total derivative of the ...
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Interpreting results of GLM with gamma regression in R

I am fairly new to R and multiple regression analyses so I could use some help interpreting my results. For my research I am trying to find predictors for the amount of blood loss during surgery. For ...
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Questions on calculating probabilities from user choice data for GLM training when two objects are equivalent

I’ve designed a GLM to predict user preference when presented with a choice between two buttons. However, there is some disagreement about how I’m providing collected user data to the model, and I ...
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