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 ...

learn more… | top users | synonyms (1)

-1
votes
0answers
27 views

Am I using the correct model, if so what do I need to fix?

I am seeking to model the number of high tunnels on farms with 13 other factors. Factors include: lattitude, percent of the population with food access, percent of vegetable acres per county, ...
1
vote
0answers
32 views

Help with complex model formula in lmer (lme4) for R

Most examples about lmer formula description in R target rather simple study designs. However, sometimes one is confronted with more complex designs and there is no ...
2
votes
2answers
69 views

Sine link with binary regression

I have used the SIN link to estimate probabilities, mostly with Program MARK. However, I am not sure how the SIN link works. I know the SIN link enables parameter ...
0
votes
0answers
16 views

How to deal with categorical features.

Recently I am playing in the famous Big-Data website Kaggle. There is a Display Advertising Challenge. In this competition, you are giving a training file which include huge records. the records is ...
3
votes
1answer
40 views

Numerical stability of IWLS for Gamma models with log-link

The combination of a $\Gamma$-distribution with the log-link function in a generalized linear model can be a useful model. However, in my experience the iterative weighted least squares (IWLS) ...
-3
votes
1answer
36 views

code for ordered probit model

I have a data set with 7 predictor variables and one dependent variable. The dependent variable has 4 categories so it's not binomial. I need to fit a probit model. I need codes for probit model in ...
0
votes
0answers
11 views

package in R for BMA of a logistic model?

I am trying to perform analysis similar to Gerlach et al. (2002). it involves predicting the posterior probability of a particular binary outcome using the previous 5 observations. I was just ...
0
votes
0answers
10 views

rebuild model based on what columns a record has

I've built a model in R using glm, and in the new dataset that I need to predict, there exist some new levels for the columns that are non-numeric. I know there are so many approaches to deal with ...
2
votes
0answers
29 views

What GLM family and link function for “proportion of time”?

A simple question to which I don't seem to find the answer anywhere. I have a response variable duration of time spent doing A of individuals tested for ...
-1
votes
0answers
33 views

In the glm function for logistic regression, where is the likelihood function stored? Is it in family? [migrated]

I am currently trying to run a logistic regression on my own, using the functions optim, nlm, etc. However, I am somehow getting ...
1
vote
2answers
48 views

Best Fit for Exponential Data

I'm trying to better understand some of the theory behind fitting models that have a nonlinear link between the response and the predictors. ...
1
vote
0answers
11 views

How to structure data for SPSS (percentages for log-linear analysis)?

I am a bit desperate because I am writing my Msc thesis and I am not sure how to organize my data for an SPSS usage. My research examines the performance of mobile banner campaigns and how the 3 ...
1
vote
1answer
50 views
+50

Testing the variance part of a Generalized Linear Model out of sample

Suppose I have a response vector and an ANOVA design (for simplicity, assume it’s a one-way ANOVA with two treatments). A few Generalized Linear Models (Poisson, Negative Binomial, etc) are fitted to ...
1
vote
1answer
29 views

Interpret GLM Output (Gaussian - identity) with B0 close to zero

I am doing a GLM (guassian - identity) using R. I am modeling different variables (8) to try to understand what creates brand value in an organization. Some extracts from the output are: ...
6
votes
1answer
181 views
+50

Likelihood and estimates for mixed effects Logistic regression

First let's simulate some data for a logistic regression with fixed and random parts: ...
2
votes
0answers
24 views

Derivation of normalizing transform for GLMs

How is the $A(\cdot) = \int\frac{du}{V^{1/3}(\mu)}$ normalizing transform for the exponential family derived? More specifically: I tried to follow the Taylor expansion sketch on page 3, slide 1 of ...
-2
votes
0answers
16 views

polynomial regression model [on hold]

Please, could you help me in answer on my question which it is as follows: I have 7 factors with 3 levels and no. of experiments are 27 tests, Can I build polynomial regression model with these data ...
0
votes
0answers
20 views

General Linear Model (GLM) with Continuous Variable and Categorical Variable (SPSS)

I would like to perform a GLM with a continuous variable and categorical variable as fixed factors. For e.g. Weight predicted by Height and Gender. From what it seems, the univariate GLM option in ...
2
votes
2answers
21 views

AR terms and independent variable as regressors

After trying several models with my data, R^2 and p values are showing my model looks like below. ACF plot tells me AR term is significant. Insights into data tells me change in 'x' would have ...
0
votes
0answers
15 views

SAS syntax to find differences in regards to a control treatment

I am working with a data set of bacterial cell counts, using flow cytometry. I recorded the cell number in 3 different species of bacteria, all treated with 3 different compounds (L-aspartic acid, ...
0
votes
0answers
59 views

GLM, Regression analysis, or other

I need to resolve a question with the use of SPSS, but don't really know what model to use. The question talks about the environment (scale variable (from not at all concerned - very concerned)), I ...
1
vote
1answer
21 views

glm with offset for rate data

I am attempting to fit a GLM to rate data. In my case it is the number of provisioning visits to a bird nest per hour. I model the data like in the example below including time as an offset. ...
0
votes
0answers
15 views

Does it make sense to only drop a specific level of a categorical variable? [duplicate]

I don't have SAS and the dataset with me, so I made up this table (from my memory). Basically this is what I got: After deciding to leave the variable $age$ and $risk$ in my model, I created this ...
0
votes
1answer
41 views

Binary logistic regression with interaction terms

I have been reading several CV posts on binary logistic regression but I am still confused for my current situation. I am attempting to fit a binary logistic regression to a series of continuous and ...
1
vote
2answers
45 views

Is it possible for Cramer's V to be negative?

To my understanding, Cramer's V cannot be negative because of the way we define it. But here's what I got from SAS:
1
vote
1answer
78 views

Count data on proportion or different kind of type?

I really do not know which kind of variable my response data is. I cannot find any answer to my question in the world wide web. I have the results from a survey of 900 farmers. Each farmer told how ...
2
votes
0answers
51 views

Nonnegative generalized linear model

Is it possible that all the parameters of a generalized linear model are constrained to be non-negative? If so, when? Any examples?
2
votes
1answer
43 views

Wald test and Type III test don't agree?

I am having trouble understanding the output here. In the green table, it seems like SAS is saying "Gender F" and "Gender M" are not significant. However, in the blue table, seems like it's saying ...
0
votes
1answer
42 views

Linear Model or Logistic Model: Can Someone Recommend a Book?

I have a huge data set that looks roughly like this: ...
2
votes
1answer
35 views

When do we use multinomial regression and Poisson regression?

They are both regression methods for discrete dependent variables. I have a discrete dependent variables like $\{A, B, C, D, E\}$, and $A$, $B$, $C$, $D$, $E$ can be cardinal data(10, 20, 30...) or ...
0
votes
0answers
18 views

Using glm(family = guassian) on data that is actually Poisson. Strange non-symmetrical bias

Let's say I want test the consequences of assuming a normally distributed response variable in a glm model when it is really Poisson. I simulate some data with some quadratic terms. ...
0
votes
0answers
12 views

Comparing beta estimates within the same sample, same independent but different dependent variables

I have a GLM with 5 independent variables (Gen-Score (GS) (independent variable of interest), Gender, Age, Sibship and year of birth) and I want to show that the GS predicts measurements of lean mass ...
0
votes
1answer
72 views

Too many p-value less than 0.0001 is alarming?

Can anyone explain why having too many p-value less than 0.001 is alarming? Like what happens to my model right now: All independent variables are categorical except for Calendar_Year. There are ...
3
votes
1answer
39 views

Constrained Maximization and Likelihood Ratio Tests for Nested Linear Models

Suppose $\boldsymbol \beta \in \mathbb{R}^k$ is a vector of coefficients for a generalized linear model with $g \left[ E(Y|X) \right] = X\beta$ for a link function $g$ and I wish to test the composite ...
0
votes
0answers
27 views

linear or poisson regression for monsoon onset

I was interested to know if I have historical data of onset of monsoon every year (where onset for each year is in Julian day) and I want to do a regression of onset against time to study whether the ...
4
votes
0answers
51 views

How exactly is the sum (or mean) centering constraint for splines (also w.r.t. gam from mgcv) done?

The data-generating-process is: $y = \text{sin}\Big(x+I(d=0)\Big) + \text{sin}\Big(x+4*I(d=1)\Big) + I(d=0)z^2 + 3I(d=1)z^2 + \mathbb{N}\left(0,1\right)$ Let $x,z$ be a sequence from $-4$ to $4$ of ...
1
vote
0answers
27 views

combining and contrasting time course GLMs using R

I am analyzing some time course data in which I have set up a GLM using R for each subject. Each GLM I want to run is an attempt to extract estimates of different behavioral conditions effects on the ...
2
votes
2answers
51 views

What interactions to include in my GLM model?

I realize this might be a too general question, so I'll describe what I'm doing right now first. I'm working for a virtual insurance company and I have this dataset. It has severity (meaning ...
3
votes
1answer
51 views

What exactly does a Type III test do?

I'm having trouble understanding what exactly Type III test statistic does. Here is what I got from my book: "Type III" tests test for the significance of each explanatory variable, under the ...
0
votes
0answers
10 views

Help: Am I using the correct test to detect differences from zero (multivariate ANOVA repeated mesures)

01 August 2014 11:17 Hi, I have 5 measures repeated 3 times under 3 different scenarios (conditions). The measures are survey questions and participants use a visual analogue scale to mark a ...
0
votes
0answers
10 views

Help: Repeated Measures Multivariate Analysis in SPSS

I have 5 measures repeated 3 times under 3 different scenarios (conditions). The measures are survey questions and participants use a visual analogue scale to mark a response from 0.0 to 15.0. Thus ...
3
votes
0answers
48 views

Classical or robust variogram for incorporation into generalized linear model [migrated]

I'm modeling counts of organisms over time at eleven locations. I'd like to account for temporal autocorrelation in the counts, assuming it's present. As the data are not equally spaced in time, ...
0
votes
1answer
30 views

GLM with categorical predictor on R

I need to do a model with a generalized linear model. My data are these: habitat : 0 or 1, group : 1 or 0 , mortality : yes or no, and the numbers of individuals for each case (habitat, group and ...
0
votes
0answers
16 views

CHAID Analysis of Logistic Regression Model

I created a logistic regression model to predict, for a people off work due to illness, the probability each of them would go back to work in the upcoming month. (Based on a number of factors like ...
4
votes
2answers
72 views

Two simple questions regarding GLM

I'm currently doing a modelling project. However, I haven't taken a bunch of statistics classes, so I have to teach myself generalized linear models. I'm reading Generalized Linear Models for ...
0
votes
0answers
35 views

Compare LMM GLMM (generalised linear mixed model, negative binomial) by numerical measure (AIC BIC, cross validation, R² squared) for model validation

How to compare results of generalized linear mixed model (GLMM, negative binomial) with a log transformed linear mixed model (multilevel, hierarchical) . I have a data set (counts), which is nested. ...
0
votes
0answers
49 views

R² (squared) from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

I try to compute the marginal and conditional R² for a GLMM using a negative binomial distribution by following the procedure recommended by Nakagawa & Schielzeth (2013) . Unfortunately, the ...
1
vote
2answers
66 views

Interpreting Residual and Null Deviance in GLM R

How to interpret the Null and Residual Deviance in GLM in R? Like we say the for AIC that smaller AIC is better, is there any similar and quick interpretation for the deviances also? Null deviance: ...
1
vote
1answer
46 views

Interpreting results of a GLM used for eQTL analysis

I am having some issues interpreting the output of the glm model I am using for an eQTL analysis (an analysis of genotype vs. gene expression for a particular ...
0
votes
0answers
27 views

How to represent bayesian loss function in binary classification

I am studying classification using linear regression . Now, I want to map it in Bayesian regression. Let talk about binary classification using linear regression again. Assume that I have a set ...