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2 votes

Interpreting slope for a categorical variable , outcome is continious

Can I say that changing X from Level 1 (Reference level) to Level 2 will increase Y on an average by 0.406 units changing X from Level 1 (Reference level) to Level 3 will increase Y on an average by ...
Sointu's user avatar
  • 1,019
1 vote

Why does heteroskedasticity not affect $R^2$ and why does it make estimated regression more statistically significant?

As to 4, that is indeed, while empirically often the case, not necessarily true. Consider as a tractable example the expressions for the standard and robust variance estimator (the correct one under ...
Christoph Hanck's user avatar
3 votes

Why does heteroskedasticity not affect $R^2$ and why does it make estimated regression more statistically significant?

As to 5, $R^2$ will tend to $$ 1-\frac{Var(u)}{Var(y)} $$ under homoskedasticity. Under heteroskedasticity (no detailed derivation here), the numerator will be related to some function of the average ...
Christoph Hanck's user avatar
0 votes

Difference between multivariate regression and running multiple linear regression models for every dependent variable

It probably depends on the type of multivariate technique you use, but to answer some of your questions: When we run multiple linear regression models for different dependent variables, each model ...
Shawn Hemelstrand's user avatar
1 vote

How to do a pairwise test of each regression model coefficient over groups?

You can add the binary grouping variable (G) as a predictor to your model together with its product with each predictor variable X (moderated regression), for example, G*X. The regression slope ...
Christian Geiser's user avatar
1 vote

How to deal with a summation term in a regression model?

I would include three dummies (D1, D2, D3) that are 1 if that kind of agreement is on for pair ij at time t and 0 otherwise. You can then calculate the marginal effect as a finite difference for 1 vs ...
dimitriy's user avatar
  • 34.3k
1 vote

Shapley value vs ridge regression

There are several reasons why the two sets of values you computed are not the same: $R_2$ contributions are not partial correlation or regression coefficients The package you use to compute Shapley ...
Marjolein Fokkema's user avatar
0 votes

Same SE for all coefficients of a linear model

Thanks to the answer by Zhanxiong, despite orthogonal variables, there is another possible situation that makes the $\hat\sigma_{\hat\beta_j}$ the same. For example, variables j=1 and 2, when $\sum_{i=...
Chrysanthe's user avatar
0 votes

How to compare linear regression coefficients with factors in R?

I am answering with relation to what I believe your main question is, that is the meaningful interpretation of factor variables in a linear regression. Recall that in a typical Gaussian linear ...
Shawn Hemelstrand's user avatar

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