collinearity

Hi there, I'm an MSc student in Medical Entomology and I'm in the midst of analysing data for my final project write up. My project is assessing the efficacy of different insecticide treatments applied in experimental huts against malaria mosquitoes. Now my dependent variables are: mortality...

Hi helpful people! My research paper was recently rejected and some of the feedback I received was in relation to the statistical tests done/not done. I would like help in clarifying what I could do differently as the feedback was not to informative. I am attempting to see which baseline...

Hi! Am dealing with a multivariate longitudinal data where we collect data from two group of subjects (cases and controls) at baseline , one month , two month, and at three months . At each of these four time points we collect data (which basically consist of 4000 variable of which many of...

I am trying to run a regression model where the Y is concentration and predictors are stove type (e.g., stove1, stove 2, stove 3) and fuel type (e.g., wood, crop waste, LPG). Stove 3 uses only the fuel type LPG, while Stove 1 and Stove 2 use wood and crop waste. When conducting the multiple...

My question is motivated by a problem with estimation by maximum likelihood. In simple terms, I want to estimate a parameter \beta and have three variables, X, Y and Z, such that Z = X+Y. Using all three variables is pointless and the joint pdf is singular. Now, suppose that instead of Z I have...

Recently came across this article regarding dealing with Collinearity. Does anyone have an opinion on what is the best method? http://bit.ly/14wDcgH

I have been reading about how (multi)-collinearity among predictor variables can be determined by looking at the condition number, or smallest eigenvalue, of the covariance matrix. My question is, if you have the covariance matrix could you not just determine that there is collinearity by...

Hi everyone, I wonder if anyone would be able to help. I'm running multiple linear regressions and have two independent variables. When looking at the collinearity statistics values, tolerance is .999 for both variables and VIF is 1.001 for both variables as well, which just seems really weird...

Hi, I have a collinearity problem with my data. How do I deal with this? the variable which has collinearity is important, so I can't remove it from my equation. Any help would be appreciate. Thanks

I read from a book that the collinearity (or multicollinearity) could possibly lead the signs of the regression coefficients to being incorrect. That is, some coefficient, which should have been positive (negative), is negative (positive) due to the presence of the collinearity. I, however...

Hi everyone, I have been working in R and using lmer() to run mixed-effect linear and logistic regression models to study language processing. I have recently learned a lot about how to code and include multi-level categorical variables in regression models (e.g., dummy coding, effects...