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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Poisson regression residual analysis

In a three factor poisson (log-linear) model $(A*B*C)$, when the highest interaction term $(A:B:C)$ is dropped, the response/raw residuals are exactly the same for different levels of two of the ...
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19 views

Generalise multiple linear models in R

I have 3 variables of my cellular recordings and made 9 linear regressions for their connection to fourth variable (a~x1...9, a~y1...9 and a~z1...9). All variables are random, not controlled. Each ...
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7 views

Obtaining AICc weights after glm.nb

I am performing negative binomial regression using glm.nb() function from MASS package and calculating AICc using package "AICcmodavg". I need also to obtain the (AICc) weights using aictab() function ...
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1answer
10 views

Fixing degenerate p-values from doing logistic regression with R glm.fit [on hold]

I'm using glm.fit to look at DNA methylation data- each site in the data set is covered by reads labeled either C or T, where Cs indicate methylation. Thus the reads are being generated by a binomial ...
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11 views

analyzing binary mortality data collected at different remeasurement intervals. Bonus for R implementation

I am replicating an analysis that models tree mortality data. Data are structured such that forest sites are revisted at some random interval, which is recorded. It is then determined if a tree lived ...
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1answer
38 views

negative binomial modelling for child pedestrian accidents

I am currently try to model child pedestrian casualties for each ward in England and to create a model that will predict how many casualties per area based on social and economic qualities of the area ...
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11 views

How to find gamma coefficients?

I am trying to replicate this paper "Gleditsch, Kristian Skrede and Michael D. Ward. 2006. "Diffusion and the International Context of Democratization", International Organization 50: 911-933" and I ...
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2answers
25 views

How to get Cox & Snell, Nagelkerke R-Square in R logistic regression output?

I'm new to R (used to work with SPSS), and looking for a function that will output the Cox & Snell and Nagelkerke R-Square measures of logistic regression. In SPSS they are displayed as part of ...
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1answer
48 views

Why doesn't standardization work in the linear regression?

I have a matrix containing the attributes of the item and their corresponding rating. All of the attributes are in the range of (0,1) and the rating is in [1,5]. I transform the range of rating to ...
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1answer
17 views

Rao's Score/Lagrange Multiplier Test most powerful when $\theta$ close to $\theta_0$?

I was reading over the documentation for the Rao's Score/Lagrange Multiplier Test on wikipedia and ran across this: Rao's score test is a statistical test of a simple null hypothesis that a ...
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1answer
17 views

picking out outliers from a GLM in R

I recently fitted a beta distributed GLM using R (and the betareg package). as you can see the model is a reasonably decent fit, however there are a few outliers. i would like to run the model again ...
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2answers
48 views

Consequence of choosing wrong functional of covariates in GLM/GAM

I'm modelling the mood of teenagers in a really big school. Response is 'good mood' and 'bad mood'. One of the variables that is used to explain the students mood is "Area of residence". Explanatory ...
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7 views

single group pre/post test

I have a single group pre/post test design. I am estimating a GLM with baseline covariate, along with a vector of other covariates. The goal is to assess change in the outcome. I found a significant ...
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24 views

Nonlinear regression vs. GLMs for estimating ED50

Are binomial GLMs better than nonlinear regression for model-fitting, and predicting ED50s and other effective dose point intercepts? In toxicology it is typical to run an experiment with a ...
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28 views

Why does my glm predict absence, not presence?

In order to explain the distribution of a species (LO), I have run a glm (family=binary, link=logit) in R 3.1.2. I have presence absence data for my species, and a number of dataset describing the ...
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14 views

GLM required sample size

I'm doing 2 different types of generalized linear models. A Poisson GLM for claim counts and a Gamma GLM for claim amounts. I've read a lot of literature about GLMs but I still haven't found a ...
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26 views

How to report the results of a GLM from R output

I am currently writing up my 4th year dissertation in Ecology having completed fieldwork and analysis on the effects of various environmental variables on Butterfly abundance. I have conductuded a ...
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1answer
66 views

Robustness of GLM to link function

When I first learned about GLMs I was taught that the link function wasn't that important so long as the domain and codomain match up. For instance, in a logistic regression we certainly need $g: ...
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4 views

Glm planned comparison fail to compare identical samples

I am dealing with several treatments, binary dependent variable and lots of zeros. When running a glm with pairwise comparison the model fail to compare two different treatments that have actually ...
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2answers
792 views

Is there a GLM bible?

Is there consensus in the field of statistics that one book is the absolute best source and completely covering every aspect of GLM - detailing everything from estimation to inference?
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50 views

Will PCA also produce multicollinearity? [closed]

It's well known that PCA will generate orthogonal basis. But in practice, I found that even after PCA, I can still face the problem of multicollinearity. Is it due to the numerical limit or I did ...
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29 views

Covariance matrix of multivariate multiple regression coefficients

I would like to perform a regression analysis on a dataset comprising one independent variable (X) and two dependent variables (Y1 and Y2) which may be affected by correlated errors. R's stats::lm ...
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6 views

Plotting Negative Binomial curves in GGplot

I am trying to plot this data with a negative binomial curve and I keep coming up with this warning label. Now, I know what the theta is, but I can not figure out where in the code to specify it. ...
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11 views

How to get correlation of each predictor to response

I am wondering how can I get the correlation from one predictor to a repsonse when I am looking at a given data set with many predictors. For example, the output of GLM in R would be exactly what I ...
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13 views

Using predict() to plot glm (and glmm) with continuous and categorical explanatory variables

I want to visualize the output from my glm by plotting the predicted values, and found an example in the Mixed Effects Models book by Zuur (pg 216-219). The description of this code from the book is: ...
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17 views

How do you create an ARIMA model with year wise regressors?

I am trying to understand how discontinuations in products have an effect on sales volume. I have a sales variable and information on product discontinuation sales volume by month and year. For ...
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1answer
40 views

R's algorithm for finding glm estimates

Is there a way of seeing the algorithm behind the glm function in R? I'm not really interested in the source code, but the step by step algorithm for finding estimates for binomial family and how it ...
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31 views

simple explanation of offset term for logistic regression

In simple words, how we can force any logistic regrssion coefficent be 1. Is there any steps/algorithm that used behind offset term? Thanks.
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2 views

What component of the result should I look at when doing a LLM model fit?

I am running mixed effects models with poisson and negative binomial fits. To asses which of the models are better, what components of the models should I look at? Some popular methods I follow: a) ...
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12 views

Logit Probability Curve Application

I have a data set whose binomial response variable is an event (1 event happens within 5 days, 0 event didn't happen within 5 days) and a predictor variable which is a count value between 1 - 10. If ...
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1answer
18 views

How to prioritize variables in GLM in R?

I am relatively new to R and GLMs. I have a simple GLM y ~ a+b. a is the dominant variable and I would like the coefficients to basically give more weight to a and then use b to explain the ...
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1answer
42 views

Making sense of Binominal GLM model

I have binominal data: For each of $x_i = 1,\ldots,49999$, I have the number of successes $s_i$, out of $n_i$ experiments. It so happens that $n_i = 50000-i$. Here is a plot of $s_i$: And here is a ...
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24 views

How to plot a categorical variable from a GLM

How do you correctly plot results from a GLM used to test a categorical variable? Here is a reproducible example in R: ...
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15 views

multicomparison treatment against 2 controls

i'm new in "r" and in statistics. I have some data that i would like to analize. Just to give you a background of my experiment: 1) i have 4 treatments (ifferent concentration of drugs) 2) i have 2 ...
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18 views

Reference level in GLM regression

In GLM regression I have always been told to set the reference level of categorical/ordinal/dummy variables to the level with the most exposure (level with most data), because this somehow makes the ...
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1answer
18 views

How to use principal component to fit linear regression for pairwise relation in R

I have been struggling with this problem for several months. I would really appreciate if someone could help me solve this. I am working on a pairwise relationship as shown in the data below (...
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13 views

Which Statistical model should I Choose to fit the Data?

I am struggling with this problem for quite a few days.So far, I have used simple Box-Plot method to pick out the outliers for each location and Diseases. And how can I get outliers after fitting any ...
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21 views

Count regression for a response that have a strict upper bound

I wonder what is the optimal way to conduct count regression when the response variable has a strict upper bound. For example, I would like to relate some predictors to how many lung lobes are ...
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1answer
41 views

Linear hypothesis test on a simple GLM in MATLAB: linhyptest on glmfit?

I have a very simple GLM in MATLAB $$y=\beta_0+\beta_1x_1+\beta_2x_2+\epsilon,$$ which I fit with glmfit. Now I wish to test if $\beta_1=\beta_2$ with linear ...
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1answer
50 views

How to choose between logit, probit or linear probability model?

To decide whether to use logit, probit or a linear probability model I compared the marginal effects of the logit/probit models to the coefficients of the variables in the linear probability model. ...
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18 views

Comparing percentages of a measurement in different conditions

I am performing behavioral analysis on two groups of mice, specifically looking at their gait. The machine that we use to analyze gait provides a percentage metric regarding a kind of step pattern ...
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20 views

How to deal with 2 response variable model?

given, for example, a glm model: fitglm <- glm (formula = cbind(Successes, Failures) ~ other variables, family = binomial) How would you interpret the ...
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19 views

GLM model specification in distribution and link function for fractional (percentage) response data

I have some aggregated data. Indep. Dep. N 1.3 78% 23 1.2 67% 20 Note that both the independent and dependent variables are aggregated by ...
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8 views

R: Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : contrasts can be applied only to factors with 2 or more levels [migrated]

I am running a regression with one categorical predictor (Group), one categorical covariate (Sex), and two continuous covariates ...
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1answer
69 views

Logistic regression doesn't fit this Infection risk analysis. Wrong model?

I am looking at a logistic regression model for predicting hospital acquired infection likelihood (HAI) from predictors of whether germs are found on the x number of patients (Patient), x number of ...
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1answer
32 views

Can there be overdispersion in a logistic regression model where each observation represents a single Bernoulli trial?

A friend and I are having a dis-agreement about over-dispersion in binomial/logistic regression glm modelling. We have structured our data so that each observation represents 1 Bernoulli trial (so the ...
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35 views

Dependent variable is count data, which method to use?

Which method should I use to analyse the relationship between count variable (absent days) and other 4 variables? Should I standardise Size variable? Please recommend some further literature/ ...
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0answers
11 views

Find the underlying model of data using different predictor variables

I have energy consumption data for a duration of one-month. The frequency of data is half-hourly. The features of dataset are temperature - temperature value at particular time instant humidity - ...
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18 views

Understanding Tukey post-hoc Tests for factor variables in GLMs

I performed a GLM, which contained one factor variable (Site), one continuous variable (Days_til_clutch_comp), and an interaction of two factor variables (Host * Egg_type). The levels of Site are: ACT ...
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1answer
125 views

What is the best way to determine which proteins are significantly bound on a testing chip?

I've got a question about the data from a biological experiment. Three times the same 1024 different proteins are spotted on one testing chip. Target of the experiment is to see whether certain ...