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.)

Filter by
Sorted by
Tagged with
0 votes
0 answers
16 views

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 ...
Neuromancer's user avatar
0 votes
0 answers
6 views

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 ...
aelyus's user avatar
  • 1
2 votes
1 answer
165 views

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: ...
Hari Tsivlin's user avatar
0 votes
1 answer
28 views

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 ...
Delphine's user avatar
0 votes
0 answers
12 views

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 ...
E10's user avatar
  • 71
0 votes
1 answer
44 views

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 ...
Estimate the estimators's user avatar
0 votes
0 answers
19 views

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 ...
Shawn Kim's user avatar
1 vote
0 answers
11 views

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 ...
Straine's user avatar
  • 11
0 votes
0 answers
7 views

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 ...
Crops's user avatar
  • 477
1 vote
2 answers
169 views

Generalized Linear Models - Order of Parameters Matter?

I've got two models, the first model is my original model: ...
Michael Emerson's user avatar
1 vote
0 answers
45 views

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 ...
Geoff's user avatar
  • 521
2 votes
0 answers
46 views

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 ...
stats_newbie's user avatar
0 votes
0 answers
19 views

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 ...
Fiona's user avatar
  • 1
0 votes
0 answers
16 views

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 (...
alpagarou's user avatar
0 votes
0 answers
37 views

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 ...
Jack Carrasco's user avatar
2 votes
1 answer
27 views

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 ...
Paul Thrift's user avatar
0 votes
0 answers
23 views

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 ...
Amc's user avatar
  • 1
0 votes
0 answers
32 views

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 ...
MyraCampbell's user avatar
1 vote
0 answers
32 views

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 “...
user22506037's user avatar
0 votes
0 answers
24 views

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 &...
AN93's user avatar
  • 1
0 votes
1 answer
40 views

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. ...
medium-dimensional's user avatar
0 votes
0 answers
28 views

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 ...
A Tyshka's user avatar
  • 101
0 votes
0 answers
23 views

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 ...
Maia's user avatar
  • 1
0 votes
0 answers
91 views

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 ? $$\frac{\beta_1}{\beta_2}$$ ...
Julien's user avatar
  • 150
0 votes
0 answers
21 views

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 ...
Crops's user avatar
  • 477
2 votes
0 answers
16 views

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 ...
user395714's user avatar
0 votes
0 answers
12 views

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'(\...
29703461's user avatar
2 votes
0 answers
38 views

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^...
Spätzle's user avatar
  • 3,028
0 votes
0 answers
30 views

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 ...
David Wang's user avatar
0 votes
0 answers
22 views

How to check assumptions of a binomal GLM with categorical predictors

I have a data set that looks like this (subset below): ...
mels's user avatar
  • 23
0 votes
0 answers
15 views

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 ...
Tan's user avatar
  • 1
0 votes
0 answers
16 views

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 ...
jrubins's user avatar
  • 13
1 vote
0 answers
39 views

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 ...
medium-dimensional's user avatar
0 votes
0 answers
8 views

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 ...
D.Hodgkiss's user avatar
0 votes
0 answers
17 views

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 ...
Carlos Benítez Collins's user avatar
0 votes
0 answers
18 views

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 ...
jpsmith's user avatar
  • 307
0 votes
0 answers
24 views

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 ...
Sternengezuecht's user avatar
2 votes
1 answer
19 views

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 ...
tjebo's user avatar
  • 135
2 votes
1 answer
39 views

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. ...
Simone's user avatar
  • 244
0 votes
1 answer
20 views

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 ...
Jens's user avatar
  • 1,564
1 vote
0 answers
22 views

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 ...
vibe's user avatar
  • 281
2 votes
3 answers
99 views

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 ...
user395024's user avatar
0 votes
0 answers
29 views

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 ...
user avatar
0 votes
0 answers
4 views

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 (...
raptorfeather's user avatar
0 votes
0 answers
27 views

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&...
Lorenzo's user avatar
  • 11
0 votes
0 answers
18 views

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-...
JuanJMV's user avatar
0 votes
0 answers
20 views

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 ...
Ye Jin Bang's user avatar
0 votes
1 answer
34 views

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 ...
Tessa's user avatar
  • 1
1 vote
0 answers
47 views

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 ...
Robert-Jan Pierik's user avatar
0 votes
0 answers
15 views

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 ...
dne3344's user avatar

1
2 3 4 5
90