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 ...

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4 views

GLM - X.intercept equal to NA [duplicate]

What does it mean X.Intercept equal to NA as a result of glm summary ? Thanks. Coefficients: (1 not defined because of singularities) ...
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5 views

Negative Binomial Anscombe Residuals

I need a help :) I'm working on a Generalised Linear Regression model, using the 'so called' NB2 model, in other words I'm using the Negative Binomial regression for count data. I would like to graph ...
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10 views

how can I block by location in r?

still new and learning how to use R, but I'd like to get some help with figuring out how to block my data by location. I found this, but I don't understand where to put my data into the code: ...
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36 views

How to Calculate π In R [on hold]

This GLM From My Data How To Calculate π With R. I Need R Code.
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1answer
29 views

Bootstrap glm and extract pvalue

I am running a glm model using bootstrap, I can extract the coefficient mean and the confidence intervals for all the factors in my model. But how can I get the pvalue from there? Model: ...
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14 views

How does one do a Post-hoc test for a Poisson glm in R?

My data consists of the following categories: Site - 3 sites - Boulder, Rubble and Cul-de-Sac Season - 4 types - warm1, warm2, cold1 and cold2 Behaviour - 6 behaviours scored - Basking, ...
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1answer
26 views

Selecting variables using SAS and R - all effects are significant even when shuffling the data

Dear all: I need to test which effects I should include in my model for genetic evaluation of cows. I was using the following code in R: ...
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1answer
17 views

Full effects from Poisson GLM

I am running a Poisson GLM with count data as response variable and both continuous and categorical variables as predictors. I made use of the following (dispersion is OK): ...
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0answers
31 views

glmer coefficients extraction

I would need to extract some coeffients after an analye performed with glmer in R. As I am not an expert I have tried to simulate data to see where I need to find those coefficients. But I am even ...
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0answers
9 views

Different results from quasipoisson models when using glm and winbugs

I used glm and winbugs to estimate quasipoisson models. I think the results should be very similar theoretically but they are not. Coefficients from winbugs are quite larger than those from glm. Does ...
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7 views

In R, using glm to model call counts in treated/not treated forests [on hold]

Ok, so I'm new to using R and trying to learn this on my own because my uni doesn't have a prof who uses R. I've tried googling for answers, and I feel like I'm sort of getting answers, but I'm still ...
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1answer
14 views

bayesglm (arm) versus MCMCpack

Both bayesglm() (in the arm R package) and various functions in the MCMCpack package are aimed at doing Bayesian estimation of generalized linear models, but I'm not sure they're actually computing ...
2
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1answer
32 views

Type of inference to use with log-linear Poisson glm on contingency table frequency counts

I was doing some log-linear models to test for interactions/associations in multiway contingency tables (based on the tutorial here, http://ww2.coastal.edu/kingw/statistics/R-tutorials/loglin.html). I ...
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9 views

Produce a GLM intercept that does not include reference levels for categorical variables?

I realize that a similar question to this has been asked, but it was not ultimately resolved. I have tried the suggestions posted to that question here, but have had no success. I am using the ...
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1answer
70 views

Logistic Regression Assumptions

I am preparing a presentation on logistic regression. I applied logit model to a data set and now want to check whether my model meets logistic regression assumptions. I don't exactly know how to do ...
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0answers
15 views

Measure of explained variance for Poisson GLM (log-link function)

I am looking for an appropriate measure of the "explained variance" of a Poisson GLM (using a log-link function). I have found a number of different resources (both on this site and elsewhere) that ...
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15 views

Creating a jpeg or TIFF for a loop of negative binomial GLMs in R [migrated]

I have made a loop to perform 4 negative binomial GLMs and now I want to graph them in a TIFF. What would be the best way to do this? ...
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6 views

Methodology for OCR Content Parsing

From a PDF book I have used built-in PDF OCR to retrieve text contents. But the PDF pages have 1-2 real book pages in one PDF page. I want to separate these pages. Example for txt page i: ...
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31 views

How do we generate the ROC curve for Linear Discriminant Analysis method

I know the method to generate the ROC curve for other methods such as naive Bayes where the tuning parameter is the threshold like also in logistic regression. If we want to generate the ROC curve ...
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22 views

How to account for overdispersion in a glm with negative binomial distribution?

I'm analysing count data with a generalised linear model in R. I started with a Poisson family distribution, but then realized that data was clearly overdispersed. I then took the option of applying a ...
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25 views

R gam() throws error: “Can't correct step size”

I am computing a GAM on a large set of data sets. Almost all of them work, just this one data set makes gam() throw an error. I paste a code that reproduces this error here: ...
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8 views

Coefficients flip sign in general linear model depending on what predictors are included: collinearity is NOT a problem [duplicate]

I have a general linear model with several predictors (~10). The sign (beta) of one of the predictors (Pred1) is negative when all predictors are included. It's STILL negative when the most correlated ...
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22 views

Adding real zeros to a dataset vs. presence-only modeling?

I have a fisheries dataset for which I have calculated the number of fishing sets in each grid cell (100 km x 100 km) for each month of every year. Fishermen in this fishery are legally required to ...
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2answers
49 views

Proportion data - beta distribution v. GLM with binomial distribution and logit link

I have a fisheries dataset for which I have calculated value for each grid cell on a map. The value is the proportion of the total fishing sets in that cell for each month/year. So, I have values ...
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0answers
18 views

covariance matrix of residuals from a fitted model to decorrelate residuals

I fit a geeglm model with clustered data and now I would like to decorrelate the residuals of the model in order to run model diagnostics. I read that if I can obtain the covariance matrix of the ...
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0answers
27 views

Adding in L2 predictor in GLiMM fails even though ICC is high

I'm using SPSS GLiMM to run a repeated measures logistic regression model. Research Qn I'm interested to know if a MP is more likely to make a particular response (e.g., apology, challenge, denial) ...
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1answer
33 views

Exploring dependencies between variables in log-linear models

Hi there I'm using R to perform some multivariate data analysis on health data. I'm currently using the glm() function with ...
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1answer
11 views

Problem fitting a geeglm regression

I am fitting a model using geeglm in geepack and ran into a problem. I have a dataset pertaining to oil consumption and fit the below model. ...
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43 views

Poisson GLM,Hessian matrix = the observed Hessian matrix

Assume a simple Poisson model with 2 unknown parameters (the intercept and the slope) Show that the expectation of the Hessian matrix = the observed Hessian matrix or equivalently the observed ...
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1answer
26 views

Expressing beta estimate in terms of odds ratio for a continuous variable

I am making a table from results of an analysis using generalised linear model which involves detecting association of a categorical predictor variable over multiple outcome variables. Of those ...
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0answers
19 views

R implementation of Zeger's parameter-driven (latent process) approach to time series regression with count data

For time series regressions with count data, Poisson-response with log link (i.e. GLM) is widely used. However, such models often suffer from serial correlation. One approach to handle was introduced ...
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8 views

Proc GLM with a list of binary dummy variables [migrated]

I am running a regression. My outcome (dependent) is a continuous variable. I have two types of independent variables. One represents day of week. The second type of independent variable is a binary ...
3
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0answers
26 views

Paired test using GLM with Gamma distribution

I know, that a paired T-test can be formulated in the framework of a linear model for gaussian distributions. I have two vectors of paired mesurements (rates under certain conditions) that follow a ...
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17 views

Post hoc for GLM that looks at interactions (in R)

I’d like some help with analysing some count data. I am very new to R (and statistical analysis for that matter!) and have done my best to work it out on my own … but seemed to have got stuck! I am ...
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18 views

Post hoc test for GLM using quasi poisson on count data in R? glht?

I'm currently working with count data with lots of zeros (the number of invertebrates within 6 types of hedge plots). I decided to use glm and quasipoisson which showed there is significant ...
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49 views

Set of confidence intervals for linear combinations of linear regression coefficients

If $$ y_i = b_0 + b_1 x_i + e_i $$ are linear regressions with $ e_i $ independent and identically distributed $N(0,v^2)$, how do I obtain a set of confidence intervals $ a_0 b_0 + a_1 b_1 $ such ...
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25 views

How to measure goodness of fit in a simple quadratic Gaussian GLM?

I hope this question will be specific enough, I went through many of the other questions about GLM but now I am even more confused because my sample size is small and it seems that R square (or pseudo ...
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12 views

Variance Decomposition in Generalized Linear Models

I'm using a generalized linear model (with a Negative Binomial distribution for observed variables) to model my data. I was wondering whether using the partial coefficient of determination is ...
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0answers
19 views

correlation between factors in a glm

My model looks like this: mdl<-glm(yld ~ rain + stage + rain*stage) A hypothetical data for the above model is: ...
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0answers
31 views

Relative variable importance for glm & glm.nb - Percentage of deviance explained

I'm currently trying to calculate variable importance for multiple GLMs. I've got both continous and count data response variables. The first I modeled with gaussian GLM, the second with negative ...
8
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185 views

Advanced regression modeling examples

I'm looking for an advanced linear regression case study illustrating the steps required to model complex, multiple non-linear relationships using GLM or OLS. It is surprisingly difficult to find ...
2
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1answer
171 views

Logistic Regression with regression splines in R

I have been developing a logistic regression model based on retrospective data from a national trauma database of head injury in the UK. The key outcome is 30 day mortality (denoted as "Survive" ...
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24 views

How to make beta coefficients comparable?

My study design delivers both, count data and continous outcomes (e.g., numbers of taxa vs. an diversity index). As these variables are used as response variables, I have to use negative binomial glm ...
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0answers
13 views

modeling a proportion with seasonality removed

I have a time series of proportions that typically fall in the 0.01-0.05 range. I had intended to use GLM to model these proportions, but I ran into trouble when I needed to first remove a strong ...
6
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2answers
307 views

Why is GLM different than an LM with transformed variable

As explained in this course handout (page 1), a linear model can be written in the form: $$ y = \beta_1 x_{1} + \cdots + \beta_p x_{2} + \varepsilon_i$$ , where $y$ is the response variable and ...
2
votes
1answer
45 views

Probit or Logit in Generalized Linear Model [duplicate]

I'm trying to apply GLMs on a dataset in which dependent variable Y is dichotomous. I applied either logit and probit models, and probit fitted better than logit model. How do I justify the choice of ...
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46 views

How to determine if GLM quadratic term should be set up orthogonal or non-orthogonal

I am setting up a GLM in R where I have only one predictor variable and its quadratic form. I understand that in R I have 2 options. ...
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1answer
35 views

Why does the null deviance in glm.nb differ between models of the same response variable?

I'm struggeling to understand the topic of deviance. Let's have two models as follows: ...
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18 views

Negative binomial instead of ordinal logistic?

I have data with one metric and a discrete outcome that I'm trying to estimate the probability of. The outcome is a count, but it's a safe assumption that the increments aren't i.i.d. I thought an ...
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0answers
46 views

“weight” input in glm.nb function in R. How exactly does the weight affect the likelihood?

I would like to understand how the weight argument of glm.nb is affecting the likelihood function. I understand that glm.nb find the MLE in an alternating iteration process where for a given theta the ...