model selection

1. Variable restriction in (exhaustive) model selection

Hi all, I have a high number of variables (around 80) with which to model an intermediate-size sample (around 50 points) using GLMs. I would like to do an exhaustive search for the "best" model, but using all of the variables in an exhaustive (or semi-exhaustive, like glmulti's genetic...
2. Which model/test should I choose? (GLM..?)

Hello! I'm new to statistics but I am getting really stuck with my data so I hope someone could help me to choose the best statistical test. I have some test (dummy) data. I have data from 64 different hospitals, for 5 different countries countries, over 5 different years. In all of the...
3. Statistical inference.

Hi there, I would like to ask a couple of basic questions: 1. What is the difference between estimation and hypothesis testing? I mean are they two options for inference? or estimation of the parameters comes first and then we apply the hypothesis testing? 2. How can I determine what is...
4. Statistical inference

Hi there, I would like to ask a couple of basic questions: 1. What is the difference between estimation and hypothesis testing? I mean are they two options for inference? or estimation of the parameters comes first and then we apply the hypothesis testing? 2. How can I determine what is...
5. Statistical Approach for data (uneven intervals)

Hello, What statistical approach would you recommend for a data of the following pattern. In a 12-hour window, each row/ID is an independent data set has multiple occurrences of an event with magnitude of event different at each occurrence and between IDs for example: ID 1 1-hour...
6. mixed-effects models with (g)lmer in R and model selection

Mixed-effects models are wonderful for analyzing data, but it is always a hassle to find the best model, i.e. the model with the lowest AIC, especially when the number of predictor variables is large. Presently when trying to find the right model, I perform the following steps: 1) Start...
7. Which model would you choose?

Dear readers, I am struggeling with the model selection (ICs are very different and many insignificant models). Which model would you choose, and can you give a reason why you would choose this model? And what would an alternative? I would highly appreciate your input!! Model F>P ---R2...
8. 1)Test multicollinearity b4/after Stepwise Log Regress? 2)Final Equatn 3)Model Select

Hi all, I need to perform logistic regression for my study. Pretty new to it but have read up on it and have tried it on SPSS. I would like to seek the advice from all of you regarding it. A brief description on my study: I want to see which factors (categorical and continuous) are...

Hello! I have a quenstion about comparing models. Not models fitted by R itself, but user defined models. Ill explain through this example: Dataset: Tree Diameter Biomass Model1biomass Model2biomass 1 10 50 45 60 2 7 35 52...
10. Testing multiple interaction variables in logistic regression

Hi everyone, For a study that I'm currently conducting I want to know the effect of some of my variables on other variables, which I think should be done by creating interaction variables. However, I'm not sure how I should test for an effect of variable A on a number of other variables...
11. Beta-Regression and AIC (model selection)

Hello, dear fellow R users, I am using beta regression because I am trying to predict percentages (response and dropout rates) of surveys. My aim is now to come up with a final model (I have many different variables and want to reduce them to a final model). I wanted to do that by using...
12. Bayes Factors using BIC statistic (model selection)

Hi, I need to compare four different models (logistic regression), model selection is performed using bayes factors using the BIC statisic. BIC can be transformed to the probability of the data given a model: PrBIC(D|Hi) = exp[-BIC(Hi)/2] And so, we can compute the Bayes factors...
13. Model selection for logistic regression, comparing p-value approach, BIC and CV.

Hi, I need to write a discussion on three approaches of model selection; p-value, Bayes factors (using BIC) and leave-one-out cross validation. The p-value is not preferred, statiscal significance depends on sample size, p-value is based on imaginary data, depends on the intentions of the...
14. Using LASSO with economic fundamentals as potential predictors

I am looking to use LASSO for variable selection, in the context of an economic factor model. My response variable is a balanced panel dataset, with n securities, each having t observations. My independent variables - potential predictors - are k economic variables: each of the k variables is...
15. Correlated Data Analysis

2 down vote favorite I am working on yield of fisheries in three different pools. The yield output was measured in terms of their length gain and weight gain. The other variables considered are length of stay, outer temperature, pool temperature, PH level of water, etc. In this case I...
16. what kind of regression tu use for competition results

hi, we have botanical data and need to analyze this sort of scenario, in terms of students for the simplicity of explenation: we have a series of competitions or trials, each one involves 2 individuals at a time, and each trial has 2 new individuals. We test for a binary score - win or loose in...
17. Model Cross-Validation Issue: Comparing models w/ and w/o error

Hi folks: I'm trying to apply cross-validation of models (e.g. the paper "On Cross-Validation of Bayesian Models" by Alqallaf and Gustafson) in the context of count data and have run into an interesting problem. My understanding of how such cross-validation should work is that one draws...
18. Calculate the number of trials to distinguish between 2 binomial distribution models

Hello, This sounds like a problem that has to be well known, but I can't find a good answer... I have two competing models for the fraction of special objects ('n') in a sample ('N'). One model predicts that f= n/N = 0.15 of the objects are special, the other that f = 0.3 are special. Ie...
19. Advice in Generalized Linear Models (Toxicology Study)

Hi all, I’m new here, and fairly new to GLMMs. I’m using PROC GENMOD to model a count outcome (number of offspring) in a toxicology study. Offspring count data were collected in 10 equally spaced time points for every individual (subject) in the experiment. Besides “time”, I have a nominal...
20. Methods in longitudinal analyses with different follow-up times

Hi all, I am new to this forum, but registered because I am looking for the right method to use in the analyses of two different projects, both longitudinal with different follow-up times for patients. I did some research into the study methods, but wasn't sure and wanted to check on this...