# multicollinearity

1. ### Common Variance as a Separate Variable

Hi all, I have a regression model exhibiting significant multicollinearity and am trying to figure out how to correct for it, or at least to minimize the effect. I found a suggestion for the following: Treat the common variance as a separate variable and decontaminate each covariate by...
2. ### Multicollinearity in Time Series Data

Hello all, this is my first post here -- hoping to find some helpful advice, and hope to dispense some in the future. Here is my situation: I am building a model to attribute registrations on a web site driven by television advertising. I am comfortable with parsing the outcome variable...
3. ### What to do when the predictors are not what I expected (when the model is fine)?

I would try to clarify the problem and then ask the questions. The problem (variable names are masked due to confidentiality): I ran a binary logistic regression, in which there were 5 independent variables (IVs): A, B, C, D, and E. A and B are my concern. C is also my concern and I would talk...
4. ### Confusions regarding Regression, Multicollinearity and Factor Analysis

I am currently working with a data set that contains about 26 IVs of almost all sorts of scale of measurement (binary, nominal, ordinal and interval scale variables). There are strong reasons to suspect that some variables are probably highly correlated, while some may not be related to any...
5. ### interpreting a model after mean centering

hello, I have to choose the best way to model the relationship between years' experience and time taken to master a new skill. The curve seems to be quadratic, and a quadratic model does have a very high r^2 (over .90). However, as is common in polynomial regression, there is a high degree of...
6. ### Dealing with multicollinearity by separating common variance

On this page, I read about multiple ways to deal with multicollinearity: http://www.chsbs.cmich.edu/fattah/courses/empirical/multicollinearity.html. I determined that the last method suggested may be best for my purposes. I copied it below: "Treat the common variance as a separate variable...
7. ### Logistic regression detection of multicollinearity- is VIF applicable?

I have a model with a dichotomous DV and IVs both continuous/numerical and dichotomous. I checked for collinearity with Pearson. How do I check for multicollinearity in logistic regression? Could I follow the procedure of rotating my IVs as DVs one at a time against the remaining IVs, and...
8. ### Regression Model is not full rank

Hi all, I am trying to detect relationship of crop yield at the end of the growing seasson (1 dependent variable) using amount of precipitation in May, June, July, May+June, June+july, Temperature in May etc. The problem is that I can't get p-values for many of these variables because of the...
9. ### Multiple Regression - Multicollinearity

Hi I'd really appreciate it if anyone could help me with this. I'm doing statistics coursework as part of a Psychology degree and have come across an issue regarding multicollinearity. My coursemates have informed me that this can be reduced/eliminated by using a backwards Multiple Regression...
10. ### Testing for multicollinearity: different scales?

Hi all, I have a question regarding multicollinearity. One of the assumptions of a logistic regression is the absence of multicollinearity. My problem is that I dont know the proper way to test this. I have different sorts of variables, which I want to check for multicollinearity on each...
11. ### ANOVA One-way Vs Factorial ANOVA. Discordant results.

Hi everybody, I have to investigate the influence of many categorical factors (A,B,C) on a continuous response variable (Y). The procedure I'm following is: 1) Make three One-way ANOVA, every time with a different predicotor A, B, C) 2) Make all the three possible ANOVA two-way using the...
12. ### How affects Multicollinearity to likelihood function in logistic regression

Hello, I'm trying to select the best covariates in a logistic regression model by a forward stepwise method based on conditional likelihood ratio test. Everybody know that multicollinearity affects the parameters estimation but, does anybody know how multicollinearity affects the likelihood...
13. ### Test for and remedy of multicollinearity in logistic regression with categorical IVs

I was searching over net how can I test the presence of multicollinearity and what is its remedy in case the IVs are categorical in a logistic regression. I am a SPSS user and found these two links over net which can be useful. But having problem to understand them. Can anyone see it and tell me...
14. ### How to test for and remedy multicollinearity in optimal scaling regression?

I have a data set containing only categorical variables (both nominal and ordinal in nature). The dependent variable is also ordinal (with 4 categories). I was planning to run a categorical regression with optimal scaling instead of ordinal logistic regression aiming at obtaining a single beta...
15. ### Testing affects of non-normal explanatory variables on response variable

Hi all, I'm having real problems with analysing some data (I am using R), and wondered if anyone would please be able to offer me any advice. I have 1 continuous response variable (normally distributed), and I would like to look at the individual affect of each of my explanatory variables...
16. ### Variance Extracted and Multicollinearity in Structural Equation Model

Hello, I am a new user here, and I am quite in need of help with regards to statistical problems. :) I really appreciate it if anyone can help me. I am currently doing a kind of "predicting user behaviour" research using Structural Equation Model (SEM). My software of choice is LISREL 8.80. I...
17. ### will high correlation between covariates in a regression model invalidate t-stat?

deleted. I figured it out. Thank you.
18. ### Cluster analysis vs multicolinearity

Hi you all, I hope you can help me with this following problem: 1. I've runned an factor analysis on my data for fifteen "need" items for sugar and sweets, with some knowledge from the company where I work for and background theorie, these items resulted in four factors. 2. Between these...
19. ### Logistic regression and correlation

Hi I'm building an account management scorecard with logistic regression. Some of the variables have quite large correlations, but they get selected into the same model (thus the effect of the correlation does not explain all the variance). According to Siddiqi (Credit risk scorecards) the...