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.
2
votes
1answer
40 views
Definition of dispersion parameter for quasipoisson family
I try to model quasi-poisson family in bugs language, to handle overdispersion. According to Introduction to WinBUGS for ecologists, this is done by:
$log(\lambda_i) = f(x_i) + \epsilon_i$
$N_i \sim ...
1
vote
0answers
46 views
Understanding the multilevel / random-effects beta-binomial regression model
Suppose we have an outcome variable $y_{ji}$ which is a count of behaviors performed by group $j$ in round $i$, for $j = 1,...,n$ and $i = 1,...,8$. The outcome $y_{ji}$ counts are non-independent ...
3
votes
2answers
97 views
+200
Population model to model year to year dynamics
My task is to assess how various environmental variables affect annual population fluctuations. For this, I would use a model like:
$$
\mbox{log} ( \mu_{i,j+1} ) = \mbox{log} ( \mu_{i,j} ) + R_{j} + ...
1
vote
0answers
16 views
Use GLM weights to regularize noise
I do a GLM containing 8 predictors on a multivariate data set. Six of these predictors encode effects that have actually been manipulated in my experiment (effects of interest), the other two ...
5
votes
1answer
85 views
I log transformed my dependent variable, can I use GLM normal distribution with LOG link function?
First of all, thank you for the great forum!
I have a question concerning Generalized Linear Models (GLM).
My dependent variable (DV) is continuous and not normal. So I log transformed it (still not ...
0
votes
3answers
44 views
GAM log link does not work without starting values
I am trying to estimate a GAM regression model using the implementation of gam from the mgcv package. I have a working Gaussian ...
0
votes
0answers
38 views
Getting the bootstrap-validated AUC in R
In a paper by Faraklas et al, the researchers create a Necrotizing Soft-Tissue Infection Mortality Risk Calculator. They use logistic regression to create a model with mortality from necrotizing ...
0
votes
0answers
33 views
GLM Distribution of Residuals
Generally speaking, meaning the exponential family of distributions allowed under a GLM:
Is the distribution of the standardized deviance residuals approximately normally distributed?
At my place of ...
0
votes
0answers
31 views
1
vote
0answers
46 views
generalized linear models, explanatory variables completely determine response
I am very new to stats, so I apologize for this naive question.
Say I have the following data
...
3
votes
1answer
76 views
Comparing levels of factors after a GLM in R
Here is a little background about my situation: my data refer to the number of prey successfully eaten by a predator. As the number of prey is limited (25 available) in each trial, I had a column ...
0
votes
0answers
17 views
How to handle missing data in Generalized Linear Mixed Models
I'm using SPSS, where I'm considering multi-level data; namely that of individuals in countries. There are no repeated measures and the dependent variable is a dichotomous variable consisting of '1' = ...
11
votes
1answer
220 views
Logistic regression model manipulation
I would like to understand what the following code is doing. The person who wrote the code no longer works here and it is almost completely undocumented. I was asked to investigate it by someone who ...
0
votes
0answers
26 views
GEE: Pairwise comparisons at different levels of a covariate?
I'm familiar with basic regression methods, but have no experience using GEEs. I use SPSS, and I'm trying to use a GEE for a dataset that I have, because there is a repeated measures component in my ...
0
votes
1answer
43 views
Bolasso in R, or other model selection techniques for parametric models
I can't find any packages which allow me to implement bolasso in R, does anyone know of one?
Otherwise, I am interested in model selection techniques which can be implemented in R for logistic ...
1
vote
0answers
20 views
Nested test to remedy pseudoreplication
Data structure:
I have two datasets from two protected areas that differ in protection status. Both areas contain 43 and 37 sites each.
Question:
I would like to know which test would be the best ...
1
vote
0answers
42 views
GRM or mixed effect models
I need your help.
In experiment I have measured the grow of one plant on 40 locations. At one location different number of plants were measured, but always the same species. The distribution of ...
0
votes
0answers
45 views
Is my random variable affecting my response?
I performed an experiment on coral colonies (10 colonies, randomly chosen in repeated measurements); manipulating aragonite/carbon chemistry and temperature (fixed effect) to analyse effects on the ...
3
votes
0answers
52 views
What does the Scale parameter mean in linear regression?
I have started to use the GENLIN procedure in SPSS more than any of the specific dialogues, but I don't understand the Scale parameter or why it has the effects it ...
0
votes
0answers
34 views
Interpreting coefficients of a Poisson regression model
How can I interpret the coefficients of the Poisson regression model if the predictor variables have more than two levels?
Example:
...
3
votes
2answers
58 views
Does there exist a likelihood based experimental methodology book on undergraduate level for psychology / social science students?
I've been looking for an introductory book in statistics and experiment design for a methods course for psychology students. I think I've been looking through at least 30 books and all go through the ...
0
votes
1answer
38 views
GLM conditional distribution from R GLM
I want to obtain the full distribution of a Gamma (or Inverse Gaussian) distributed $y_i$ given a vector of $\bar x_i$ that have been used in the linear predictor of a coefficient. Suppose also for ...
10
votes
3answers
798 views
How are regression, the t-test, and the ANOVA all versions of the general linear model?
How are they all versions of the same basic statistical method?
1
vote
1answer
31 views
Separate specifications for p and n in a binomial GLM
For a binomial GLM, both the probability and the number of trials are important for each data entry. Using the glm fucntion in R, how do I specify them separately ...
2
votes
3answers
97 views
Which glm algorithm to use when predictors are numerical as well as categorical?
I just need a direction on which regression algorithm (preferably glm or similar) algorithm to use when the predictor variables are a mix of numerical and categorical variables. The output is ...
2
votes
1answer
83 views
Goodness of fit in a GLM with scaled deviance
On this page, I am interested in the section “goodness of fit”, which is near the bottom of the page and contains the table of deviance functions.
The author states that the scaled deviance, i.e. ...
1
vote
1answer
22 views
Starting coefficient vector for GLM
I would like to know how R chooses its starting coefficient vector for a GLM when its start argument is left blank and defaults to ...
0
votes
0answers
44 views
How to interpret results of GLM with a beta distribution in R?
I'm currently working on a project where my model is a GLM with a beta distribution. The dependent variable is bimodal. I've done this before, in Stata, but I'm having some difficulty interpreting ...
1
vote
0answers
28 views
Error with Syntax for GLM with inverse.gaussian family in R
In my data set, I have 3 covariates ($V_1, V_2, V_3$) and response ($V_4$), generated by a program specifically written to generate random variables using an Inverse Gaussian distribution, in which $ ...
0
votes
0answers
26 views
3
votes
1answer
133 views
Using R for GLM with Gamma distribution
I currently have a problem understanding the syntax for R for fitting a GLM using the Gamma distribution.
I have a set of data, where each row contains 3 co-variates ($X_1, X_2, X_3$), a response ...
0
votes
0answers
34 views
Reference for R VGLM function
Could someone please either explain to me what the VGLM function in R does or point me towards comprehensive documention? Currently, the only documentation I can find does not explain what a Vector ...
1
vote
0answers
39 views
GLM with unequal sample size
I am trying to figure out how to run a GLM with a poisson distribution in R. The data has 4 treatments: A(n=16), B(n=17), C(n=16), D(n=20), and 2 time periods. This data is count/area so there are ...
4
votes
0answers
60 views
Which model for panel data with dependent variables from [0,1]?
I'm stuck with a regression modeling problem. I have panel data where the dependent variable is a probability. Below is an excerpt from my data. The complete panel covers more countries and years, ...
0
votes
0answers
23 views
Calculation of Semi-Elasticities
I have one question regarding the calculation of elasticities for gamma and negative binomial regression.
I know that for a poisson regression one gets semi-elasticities. Dividing by the mean of the ...
1
vote
1answer
34 views
Generalized Linear Model estimating multiple parameters concurrently
Is there an extension of the generalized linear model that is able to estimate (using maximum likelihood) more than one parameter of a distribution at once. For example, I know that for a gamma ...
4
votes
1answer
133 views
Which is more accurate glm or glmnet?
R glm and glmnet use different algorithms.
I notice non trivial differences between the estimated coefficients when I use both.
I am interested in when one is more accurate than another, and the ...
0
votes
1answer
74 views
Why is Hedonic Regression used instead of Linear Regression
Why is Hedonic Regression used (especially in housing prices) instead of Linear Regression?
There do not seem to be any libraries in Python (and R) for Hedonic regression, is it too niched a ...
0
votes
0answers
33 views
incorporating averaging models from AIC and still using k-fold cross validation?
Ive a county/district that Ive divided into ~300 grids that are 15km^2 in size attributed with various habitat and economic variables that have been summarized and standardized. I then have 2 types ...
0
votes
2answers
48 views
Transforming nonlinearity in genearlized linear models
Are the buldging rules applicable in generalized linear models? Specifically, to transform the independent variables?
I've only seen it disscused/used in OLS regression.
Thanks in advance
0
votes
1answer
48 views
Simulating responses from a factorial experiment for power analysis
I am thinking about a factorial experiment with two factors. Both factors are ordered factors. Factor 1 has two levels: small and large. Factor 2 has four levels: never, sometimes, frequently, and ...
0
votes
0answers
33 views
Factorial design with repeated-measures and binary outcome variable
I have a question on how to analyze some data from a psychological experiment.
The design of the experiment is a mixed 2x2x4 factorial: the first 2 factors are manipulated between-participants, but ...
0
votes
0answers
41 views
Restricting model parameters in logistic models in R
Is there any function in R that can solve the problem like this example from the SAS website:
Beginning in SAS 9.3, PROC FMM can be used as an alternative to ...
1
vote
2answers
82 views
Should the predictor variables be normally distributed for Poisson glm?
This is probably a really basic question, but it's the first time I've created a model that defines Poisson as its error family.
In setting up my variables to make the model, should I be concerned ...
5
votes
4answers
338 views
What regression analysis should I perform on my data and why?
I am a law student researching which factors influence the CSR (corporate social responsibility, GSE_RAW) behavior of companies. As my studies didn't offer any ...
0
votes
1answer
62 views
How to see how good is my model?
I am using glm to find a model using training data and then use test data to see how well the model is behaving. My response variable is ...
0
votes
0answers
18 views
Estimating the variance of linear prediction coefficients and parameters
I'm using linear prediction with singular value decomposition (LPSVD) to analyze signals that are damped sinusoids. If my understanding of the theory of linear prediction is correct (and it may not ...
0
votes
0answers
19 views
Choosing prior distribution in LDA
how do you set prior distribution of K in LDA and can it be used for feature selection to improved selection accuracy of document. Abbey
3
votes
2answers
105 views
What is the expected distribution of residuals in a generalized linear model?
I am performing a generalized linear model, where I have to specify a family different from the normal one.
What is the expected distribution of residuals?
For example, should the residuals be ...
0
votes
0answers
18 views
Testing the effect of spatial differences
I have a closed room. I release some bacteria in the middle of it and let it settle onto previously located plates on the floor. Once the bacteria settles I collect the plates and count up how many ...
