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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24 views

Specifying Error() in R `aov` function

Consider a data where samples from different populations of 5 species are analyzed after 4 treatments at 3 time intervals. So the independent variables are ...
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6 views

GEE returned Mean estimate 0.5, confidence limit 0.5-0.5 and SE of ZERO for a categorical variable

Following were the notes NOTE: PROC GENMOD is modeling the probability that CompositeO='Yes'. NOTE: Algorithm converged. NOTE: Algorithm converged. NOTE: The empirical covariance matrix ...
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40 views

Reduce feature levels

I would like to know if someone knows of a way to group the number of levels of a feature that has 100's (even 1000's) of levels to a smaller number of levels - also, what number levels it should ...
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35 views

How to understand the results of generalized linear model in R? [on hold]

I am always confused about the results of generalized linear model when I use R package like MASS. For example, we can get the summary below using glm.nb: ...
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2answers
180 views

Questionable Beta Regression Results

The goal of this regression is to determine whether the amount of leaf disk that an insect consumed varied by what tree the leaf material came from. I'll acknowledge upfront that my coding is rarely ...
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13 views

How to perform GLM in SPSS for a data showing Gamma(2) distribution in XLSTAT? [on hold]

I have run the distribution fitting of a dependent variable in XLSTAT software which shows the variable follows Gamma(2) distribution. Now I want to know which one out of six continuous explanatory ...
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18 views

How to calculated test F with only output glm?

I have to calculate the value of the test F (no software needed ) . I read several notes, but I can not understand how I do . The idea is to take Null deviance and Residual Deviance and split in some ...
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45 views
+50

What r parameter is used in a negative binomial regression?

From my understanding of the negative binomial regression, we have $Y_i|X_i; \theta$ is distributed $Neg Binom (r_i, p_i)$, where $r_i$ is known and fixed (analogous to a fixed $\sigma^2$ when we ...
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19 views

GLM - compare the estimated model with the model with intercept-only

I have this glm output. How do the test to compare the estimated model with the model with intercept-only ? How can I comment on the result ?
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15 views

Identify differentially expressed genes across genotypes

I have 40 different genotypes of rice. For each genotype, I have two replicates under control treatment and two replicates under drought treatment. We sequenced those samples and get read counts of ...
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1answer
68 views

Is it possible to use ordered categorical independent variables in logistic regression?

I'm trying to model a logistic regression in R between two simple variables: Rating: An independent ordered categorical one, ranging from 1 to 99 (1, 2, 3, 4, 5, 99 in particular, 1 is the best) ...
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7 views

Poisson regression modelling using PROC GENMOD – impact of grouping on fit statistics

I am trying to model claim rates using poisson regression. Please find example SAS code below: c is the number of claims, n is the number of insured vehicles, car and age are categorical properties of ...
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16 views

Reconcile Different Statements of the IRWLS Algorithm

Different textbooks seem to have different definitions for the weight matrix W in the Iteratively Re-Weighted Least Squares (IRWLS) algorithm. They should be equivalent but I can't seem to piece it ...
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24 views

Comparing importance of features in different datasets in GLM

I want to compare the importance or 'predictive power' of the same feature in 2 different datasets. Specifically let $[\bf{y}_1,\bf{V}_1]$ be my output & design matrix of dataset 1 & $[\bf{y}...
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9 views

Log linear analysis with weights

I am trying to conduct a log linear analysis using deer count data from Heisey (1985) and used as an example in Resource selection by animals by Manly (2002). They use a program named GLIM (...
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1answer
35 views

Help Deriving Variance Function - Binomial GLM

I'm having difficulty replicating/deriving a result in GLM's for Binomial data. That is, if $Y \sim Bin(n, \mu)$ and we put the distribution of $Y/n$ into exponential family form (with a dispersion ...
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25 views

Understand output glm

I'm going crazy I can not solve the questions b and c. In addition I also write my solutions, even if they are not aware of their exactness. The set of data in the data frame care refers to 40 ...
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1answer
49 views

How to create a regression model if data points are structure as seen in the graph?

This is a graph of revenues for different products with the Y-axis showing normalized revenues (mean of 3 and SD of 1) and X-axis is weeks. I need do a regression analysis of sorts on this data and am ...
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8 views

Delta-x glm (delta gamma and others)

Can anyone recommend a good book about delta-x glm (delta gamma and others). I know there is an r function for it and the basic principle of it but I would like to understand it better before ...
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24 views

Negative Variance Inflation Factor (VIF)?

I'm working on a Poisson regression model (with SAS), and my predictors are not only quantitatives (I have a lot of categorical variables). With SAS, it's possible to determine easily VIF of each ...
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1answer
25 views

Partitioning effects from a Poisson GLM

I'm using a Poisson GLM to model the effects of advertising (number of ads bought) on the number of sales (numConvs). If possible I'd like to use the model to get ...
0
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0answers
14 views

Weights vs Correlation Linear Regression

I am working with Spark 1.5 and I want to predict something. Before in R, I would use the p-values from glm and the importance from randomForest to get an idea of feature selection. So, in Spark (...
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19 views

Confidence interval sum fitted probabilities GLM

Let CI$_i:=logit^{-1}(\hat{\mathcal S}_i \pm 1.96*$ SE$(\hat{\mathcal S}_i))$ denote the $n$ Wald confidence intervals of the fitted probabilities $\{\hat{p}_i\}_{i=1,\dots,n}, \hat{p}_i:=\hat{p}_i(x|\...
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31 views

Can I flip the null and alternative hypotheses for logit regression in R?

I would like to accept the hypothesis that a variable is insignificant in determining the dependent variable of a logistic regression, but in R the glm summary which contains the p-values for each ...
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15 views

Nested GLMMs: which are my random factors?

I am analyzing the number of seed capsules between different genotypes (A,B and C) I have 4 replicates for each genotype and in each of these replicates, I have 8 plants. Here is an example of the ...
2
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1answer
65 views

GLM missing data

I've come across the problem of missing data when doing GLMs. I'm using GLMs to make predictions in R. My dependent variable is continuous and my independent variables are factors. The question arises,...
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7 views

How to test if the difference between two logit-function-fits is significant or not?

I am considering a binomial experiment where each trial can only have two possible outputs (0,1). I vary the value of a predictor (experiment parameter) and repeat the experiment several times for ...
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1answer
48 views

Is there a way to flip the hypotheses of the significance of variables in a logit regression model?

I am using the GLM Summary in R to determine the significance of the variables in the logistic regression model. I am trying to figure out if there is a way to flip the null and alternative hypotheses ...
2
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1answer
23 views

Should I be using season as a random or fixed effect?

I am a marine turtle researcher attempting to understand the effect of a harmful algal bloom on our turtle capture rates and the body condition (BC=mass/length^3) of captured turtles. Field ...
2
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0answers
30 views

Will the signs of coef (Estimate) of lm and glm always be the same?

Will the signs of coef (Estimate) of lm and glm always be the same? ^ According to below toy example, it seems yes. Can you provide a case where they might be different? (If it matters in my real ...
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15 views

Multivariate GLM or MANOVA or other alternative for 2x2 repeated measure experiment?

I am trying to get my head around the right choice of experimental design and analysis for a collaborative software I have created and would like to evaluate. The software allows groups to conduct a ...
1
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1answer
98 views

Reproducing SPSS GLM in R, changed coefficients

I'm trying to reproduce a generalized linear model in R. The original SPSS model has distribution Gamma, link Log, with a continuous dependent variable and all independent variables categorical. In R ...
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13 views

Relationship between two (zero-inflated) count variables

TLDR: How can I model the relationship between two count variables that are both dependent on the same third, unobserved, continuous variable. Detail I am interested modelling the effect of an ...
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1answer
20 views

Extracting Standard Errors for a combination of factorial predictors in binomial GLM

Suppose I run a binomial GLM (in R) with response variable [0,1] and 2 predictor variables that are both categorical. Let's call them a and ...
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38 views

Why the coefficient of regressors in robust multiple regression is beyond 1 even though I have normalized the data

Could you please help me with my confusion: I have used the robust multiple regression model(both X and y have been normalized by using zscore) and want to get the beta(standard coefficient of the two ...
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1answer
40 views

Poisson Regression Likelihood estimation

Let $Y_1,\dots,Y_n$ independent random variables with $Y_i\sim > Poisson(\lambda_i)$. For the likelihood model $$log(\lambda_i)=\sum_{j=0}^p\beta_jx_ij$$ with $x_i=(x_{i0},\dots,x_{ip})$ where $...
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1answer
26 views

Calculating relative importance of predictors in a poisson glm model

This is the model I'm working with, some variables are int, some are num and some are factors. ...
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1answer
28 views

How to choose a link function in Generalized Linear Model in R

I would like to know how to choose a link function in generalized linear models in R. Roughly, I have learned that family=binomial or ...
1
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1answer
74 views

What is the difference between logistic regression and Fractional response regression?

As far as I know, the difference between logistic model and fractional response model (frm) is that the dependent variable (Y) in which frm is [0,1], but logistic is {0, 1}. Further, frm uses the ...
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9 views

Predicting probabilities in quasibinomial GLM

I have a very specific problem, as I've done a somewhat complicated analysis for my Master's thesis (deadline in two weeks!). First, I've done Latent Class Analysis with Gibbs sampling (paper I've ...
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29 views

Classification model created in R, how to run it in Excel [closed]

USE CASE Use R to fit/train a binary classification model, then interpret the model for the purpose of manual calculating classifications in Excel, not R. MODEL COEFFICIENTS ...
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1answer
25 views

Removing intercept from GLM for multiple factorial predictors only works for first factor in model

I am running a binomial logistic regression with a logit link function in R. My response is factorial [0/1] and I have two multilevel factorial predictors - let's call them a and b where a has 4 ...
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23 views

include random effect in model

I am having problem deciding wheter to define a variable as a random effect to include in our logistic regression model. Any help on this subject would be most appreciated. In this model, we are ...
0
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1answer
29 views

3 Interaction terms in generalized linear model

I have 4 continuous variables as my predictors (say, cognitive ability and three components of self-esteem) and the 3 two-way interactions between cognition and each self-esteem component. I am using ...
3
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1answer
81 views

Positive skewness: what to do when transformations don't help?

I would like to perform General Linear Model with one response variable and two predictor variables (1 numeric, 1 categorical). The response variable is positively skewed and transformations don't ...
2
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1answer
77 views

GLM Categorical Variable Level grouping / simplification

I am trying to find information regarding a technique which is commonly used in the insurance pricing industry. This relates to a GLM model where a categorical variable is used in the model. The ...
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17 views

Logistic regression with temporal autocorrelated data

My objective is to simulate daily temporal series of wet/dry sequence of 2 years (730 days). I'm using a logistic regression with one continuous covariate, $x_{i}$, which is the rain amount of the day ...
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1answer
24 views

Is there a limit proportion of 0 and 1 to fit binary data using glm (link “logit”)

In relation with my other question here where I observe a strange behavior of the residuals after fitting binary data using glm/glmer, I now wonder: Are there boundaries on the proportion of 0 (or 1) ...
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1answer
24 views

What is the ideal distribution for a GLM for comparing survey data with election results?

I'm relatively new to statistical methods. I'm hoping to learn what kind of distribution I should use for some data I have. My dependent variable is the results a candidate received by county. My ...
3
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1answer
38 views

Logistic regression link defined in terms of $\pi_i$ and not $\mu_i$

I am confused about the terminology used when discussing the logistic GLM. When dealing with any glm, we have that for the response $Y_i$: $$ E(Y_i) = \mu_i $$ and $$ g(\mu_i)= x_i^T \beta = \eta_i $...