This tag is a signal that the question focuses on a problem particular to multivariate analysis, such as multiple correlations or interactions.
25
votes
6answers
7k views
How can a regression be significant yet all predictors be non-significant?
My multiple regression analysis model has a statistically significant F value however all beta values are statistically non-significant.
All the regression assumptions are met. No multicollinearity ...
5
votes
1answer
1k views
How to choose between ANOVA and ANCOVA in a designed experiment?
I am conducting an experiment which has the following:
DV: Slice consumption (continuous or could be categorical)
IV: Healthy message, unhealthy message, no message (control) (3 groups in which ...
8
votes
3answers
8k views
Significance of coefficients in linear regression: significant t-test vs non-significant F-statistic
I'm fitting a multiple linear regression model between 4 categorical variables (with 4 levels each) and a numerical output. My dataset has 43 observations.
R gives me the following p-values from the ...
4
votes
2answers
957 views
How can adding a 2nd IV make the 1st IV significant?
I have what is probably a simple question, but it is baffling me right now, so I am hoping you can help me out.
I have a least squares regression model, with one independent variable and one ...
25
votes
5answers
7k views
When should you center your data & when should you standardize?
In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividing ...
0
votes
1answer
1k views
Not-significant F but a significant coefficient in multiple linear regression
I have a regression with two continuous predictors and one dichotomous predictor in Model 1 and two interactions of each of the continuous predictors with the dichotomous predictor in Model 2. The ...
0
votes
2answers
695 views
How to interpret inconsistent Beta values in different steps of hierarchical regression analysis?
I did hierarchical regression analysis on my data due to having moderation effects in my research model.
R2 increased from .695 in model1 (main effect only) to .734 in model2 (main &interaction ...
2
votes
4answers
348 views
Why ANOVA/Regression results change when controlling for another variable
This question might be very basic, but somehow I don't understand this point.
Suppose initially I used a univariate regression equation such as
GDP=a+b*Income
...
7
votes
2answers
607 views
How can I use the value of $R^2$ to test the linearity assumption in multiple regression analysis?
The below graphs are residual scatter plots of a regression test for which "normality", "homoscedasticity" and "independence" assumptions have already been met for sure! For testing the "linearity" ...
15
votes
2answers
449 views
In what order should you do linear regression diagnostics?
In linear regression analysis, we analyze outliers, investigate multicollinearity, test heteroscedasticty.
The question is: Is there any order to apply these? I mean, do we have to analyze outliers ...
17
votes
6answers
5k views
Is adjusting p-values in a multiple regression for multiple comparisons a good idea?
Lets assume you are a social science researcher/econometrician trying to find relevant predictors of demand for a service. You have 2 outcome/dependent variables describing the demand (using the ...
9
votes
2answers
2k views
How to deal with collinearity issue when performing variable selection?
I've got a dataset with 9 continuous independent variables that I'm trying to select between to fit a model to a single percentage (dependent) variable, Score.
...
8
votes
2answers
3k views
VIF, condition Index and eigenvalues
I am currently assessing multicollinearity in my datasets.
What threshold values of VIF and condition index below/above suggest a problem?
VIF:
I have heard that VIF $\geq 10$ is a problem.
After ...
4
votes
1answer
1k views
Why are rlm() regression coefficient estimates different from lm() in R?
I am using rlm in the R MASS package to regress a multivariate linear model. It works well for a number of samples but I am getting quasi-null coefficients for a particular model:
...
0
votes
2answers
870 views
How can you have a non-significant multiple regression model w/ significant predictors? [duplicate]
Possible Duplicate:
Not-significant F but a significant coefficient in multiple linear regression
How can a regression be significant yet all predictors be non-significant?
Significance of ...
