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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Effect size in linear mixed models

Thank you for reading this question. I know there have been a few discussions regarding this topic, but I couldn't get a satisfactory answer. So here is my question, with some details in the ...
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Does Poisson regression give a good fit?

I am using a hurricane dataset (specifically the NDAM and Gender_MF columns): ...
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What is the difference between Generalized Linear Models(GLM), Fixed-effect models (FE), and Random-effect models (RE)?

I am new to statistics and I am looking for a general answer. Can someone explain (very simply) what is the relationship between Fixed-effect & Random-effect models with Generalized Linear Models? ...
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Questions regarding generalised linear models and analysis of deviance

I query concerns Question 2 of this past exam paper. I am fairly new to the subject of generalised linear models, so I would appreciate some help in constructing a 'model answer' to a question such ...
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Do you specify priors according to the link function's transformed space?

Suppose I'm developing a model where the response variable is weight measured in pounds and is Gamma distributed. I would like to specify a prior on my intercept coefficient using other information ...
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Fitting distribution to log response ratios [on hold]

I am trying to analyze variables on repeated measures with a randomized block design, and used log response ratios to do so: $$ln\left(\frac{Y_{control}}{Y_{treatment}}\right)$$ I would like to model ...
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Fitting a distribution for log normal ratios [duplicate]

I am trying to analyze variables on repeated measures with a randomized block design, and used log response ratios ( $\ln(\text{Ycontrol}/\text{Ytreatment})$ ) to do so. I would like to model the ...
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I have a confusion between using 4 different general linear models and 1 singular ones. I have provided with the codes and outputs

I want to check the effect on mass of crickets, I have a fixed linear effect (AltitudeAge), fixed quadratic effect (AltitudeAge^2), random effects (Nymph IDs, population and the incubators they are ...
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Appropriate GLMM distribution for ratings data that are bounded and discrete

I am using a linear mixed model to explain variation in an object's ratings. These ratings are bounded between 0 and 10, and take only discrete values (example histogram of the raw data below). Note ...
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Poisson regression: Is a skewed Likert-scale dataset a valid candidate for this approach?

Goal My goal is to correctly model the effect of three independent variables (job autonomy, trait plasticity, and job complexity) on a dependent variable (job stress). Problem Having run a ...
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Likelihood Formulation of a Time Dynamic Bradley Terry Model with Random Effects

Let us assume a mixed logit model with a binary dependent variable $y_{i, t } $ that is explained by a fixed effect matrix X and a simple random intercept for each individual $i$ $y_{i,t}^* = x_{i,t}'...
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Placing constraints on free parameters across groups in lm or glm functions [on hold]

It's possible to place certain combinations of constraints on free parameters (intercepts, slopes, residual variances) across groups within the context of lm(), <...
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Is there a difference between a GLM with gaussian family and a standard linear model?

I am trying to model some data and I'm going around in circles trying to figure out what family I should be using when writing the generalised linear model. Here is some example data: ...
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count data model with capped response variable

I'm trying to predict the total number of Olympic medals won by a country in the summer Olympics games. I have data from 2000 to 2012 relating to the country gdp, population, number of athletes sent, ...
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Multi variables analysis [closed]

probably this question was answered already but I'm so bad that I can't find it. I ran a basic correlation between the many items of a questionnaire I had (>75) and some of them seem to be correlated....
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R: Modelling estimates for the factors and 'sub-factors' of a predictor variable within a GLM

To take a simple example, let's say the model contains a dichotomous predictor variable with the factors {Group X, Group Y}, where all observations can be categorized into one of the two groups. ...
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Continuation ratio model issue: non-numeric argument to binary operator [closed]

I am trying to build a continuation ratio model for my dataset which has mainly categorical predictors. I used glmnetcr package. This is my code: ...
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Effect of Hydration Status on Cognitive Function - which statistical tests do I use?

I'm carrying out a study on the above. My data is normal and my independent variable has two levels (hypohydrated and euhydrated) and unequal groups (14 vs. 8). I have 5 dependent variables - CF 1, 2, ...
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Interpretation of fractional regression (GLM quasibinomial with logit link) coefficients

I am writing a research paper commenting theresults of the following regression, which is a GLM quasibionomial regression with a logit link (the outcome variable capfactor ranges between 0 and 1). <...
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Parameter Estimation in Generalized Linear Mixed Models

Let us assume a generalized linear mixed model with a binary dependent variable $y_{i, t } $ that is explained by a fixed effect matrix X and a simple random intercept for each individual $i$ $y_{i,t}...
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Question regarding notation for F-distribution

Apologies for the basic question; I don't have a very deep or broad background in statistics. I am reading this paper on phase transitions in the existence of maximum likelihood estimators for ...
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Parameter not estimating due to singular information matrix and mutually exclusive categories in R

I have some data that has two categorical variables that are somewhat correlated (there is a row and a column of zeros where the levels are mutually exclusive), similar to the tabulation below. ...
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SPSS generalized linear mixed model: estimated marginal means 95% CI [closed]

When I use the estimated marginal means the 95% confidence interval is also reported. What is this 95% CI based on? I assumed it is based on the SD of the model and not only on the SD of the reported ...
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Change in X and Change in Y in Pearson Correlation

Suppose I have my x variable calculated as Hormone2-Hormone1 where Hormone2 is at a later time point and Hormone1 is earlier - this is true for all subjects and the time points are equally spaced for ...
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Comparing proportions of two samples in time

I am trying to compare if the proportion of one bird subspecies in a roosting area is different now from over 20 years ago. My dataset looks like following: -In 1996 birds were counted at a ...
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Trying to slightly alter logistic GLM - Link function seems unstable [closed]

So the data I have is whether a subject has performed a test correctly, or incorrectly. They have to match choose which of a pair of stimuli matches one they have memorized, and this gets harder and ...
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Error in y * weights : non-numeric argument to binary operator [closed]

I am trying to build a continuation ratio model on a large dataset that has many categorical variables using glmnetcr package. I'm trying to fit this model: ...
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Gaussian GLM with Log Link (Distribution of Response)

If I have a Gaussian distribution with a log link, what is this model saying about the distribution of the response variable. E.g. Is the distribution of the response in this model Y|X ~ Normal( Exp(...
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R: how to get effective degrees of freedom?

I'm building a sparse additive model and using the Generalized Cross Validation score for a linear smoother $\hat f(x) = L(x) \underline Y$ $$GCV(\lambda) = \frac 1n \sum_{i=1}^n \left( \frac{Y_i - \...
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Generalized linear model (GLM) for panel data?

I have a panel data and what I need is to use generalized linear model (GLM), but I am confused; that is, I cannot find any related article in which they have used GLM for panel data. Can you share ...
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GLM: Empirical cloglog transformation for exploratory data analysis

Prior to fitting a GLM to an ordered categorical response $Y$ (6 levels), I would like to check the linearity assumption between the one (and only) continuous covariate $x$ in my linear predictor and ...
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Polynomial Regression with grouped independent observations

I am trying to model how porosity changes across burn up levels of a fuel pellet. I have 300 observations at varying levels of burn up. The way my data is collected makes burn up appear as a ...
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Cross validation for glm gives AUC 1, but predictor values overlap between groups

I want to apply cross validation for a glm and get a classifier evaluation. Two variables in my dataset have identical values, but prediction for them is different and that results in perfect ...
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GLM Categorical IV Predictor vs Group by Analysis

I am modeling a continuous dependent variable with a couple of covariates (known a priori) and a variable of interest. I ran into an issue of interpretation which I'd like to clear up. When I ...
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Moderation Analysis with Ordinal Dependent Variable

My knowledge of statistics is unfortunately rather limited, at a basic undergraduate level. Part of my current project involves conducting a moderation analysis between one independent, one moderator, ...
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Seeking to understand using the Firth correction in Generalized Estimating Equations to deal with quasi-complete separation

In order to deal with complete separation in my data someone suggested that I run penalized GEE (PGEE) by adding a Firth-type penalty term in R. Although I have read many papers on the Firth ...
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Quasi/Complete separation due to huge and infinite values

(R statistics) My question is regarding this warning. My data contains patients and healthy subjects. Exponential decay is my outcome measure. I have a example dataset here I managed to run ...
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Can Park & Casella's Bayesian LASSO be applied to generalized linear models?

In Park & Casella's Bayesian LASSO model the LASSO is estimated through a scale mixture of normals: ...
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Specification and Interpretation of Repeated Measures Binomial model in BRMS

I have two questions regarding specifying and interpreting Repeated Measures Binomial Models in BRMS We have a set of data in the following format: ...
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Which model with multiple samples by subject and one response by subject? glme?

I have a few variables (continuous or ordinal) and multiple samples from the same subjects (n=10 for now). The number of samples by subject varies from 1 to 50. Samples are not repeated measure s in ...
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What kind of regression to use with heavily skewed data?

I have data with an explanatory variable $X$ (I think I can treat this as continuous, as scores 1-100 on a certain test) and a response variable $Y$ (continuous variable, never lower than 0). Both ...
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Which model to choose - lmer vs. glmer

I am trying to model y, a continuous variable that only takes positive values with fixed and random effects. This is my first approach, using lmer(): ...
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How to deal with binary predictors in a logistic regression model?

I'm building a logistic regression model in R using glm(y ~ x1 + x2 + x3 + x4, data = train.set, family = binomial(link = 'logit')). Among 4 predictors ...
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Predicting vector of counts

I was wondering if there are any models that are similar to Poisson regression, but instead of having 1 count as the target, there is a vector of counts as the target. For example: Typical Poisson ...
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Why does independence matter in Statistics & Why does a MLM change Fixed Effect Coefficients?

I've been trying to get a better grasp of statistics lately, and have been wondering why exactly independent observations matter when building a model? This is a broad question, but I'm curious about ...
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analysis of cumulative count data

I am comparing the number flowering in normal plants and 3 mutants. I have 60 normal plants and 60 of each mutant plants. The flowering were measured at 6 consecutive weeks and the data is like the ...
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Role of different exponential families in generalized linear models

I've gone through a variety of introductions to generalized linear models (GLM), and there's always a point in the discussion that confuses me. The story often begins saying that $P(y|x)$ belongs to a ...
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Comparing Gaussian and Poisson GLM when applied to count data; “Chi-Squared Error”

I have a fixed set of predictors ($[x_1,x_2,...,x_p]$), which I'm using to fit a GLM for univariate responses ($y_1$, $y_2$,...) of various types. E.g. I fit a GLM for $y_1 \sim [x_1,x_2,\dots,x_p]$, ...
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Definition of exponential family with dispersion parameter

I was recently reading a discussion of generalized linear models that considered the response to come from an exponential family with a dispersion parameter so $$ f(y|\theta,\phi) = \exp\left(\frac{y\...
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Variable selection for mixed models

Longtime lurker here. I have a question about determining informative variables in generalized linear mixed models (GLMMs). My background is ecology, and I primarily examine habitat selection under ...