Linked Questions

1 vote
0 answers

F - test to compare two nested models [duplicate]

I want to fully understand how F test is used to compare two nested models. Every information I found about it, is only standard use i.e. to compare model with model containing no variables. How I ...
John's user avatar
  • 532
1 vote
0 answers

Right term for "Leave-Multiple-Feature-Out" feature importance? [duplicate]

I am working on a ML problem incorporating four data streams, each producing multiple features. We would like to know if each of the data streams provides a significant addition to the model ...
M.G.Poirot's user avatar
32 votes
3 answers

How to deal with multicollinearity when performing variable selection?

I have a dataset with 9 continuous independent variables. I'm trying to select amongst these variables to fit a model to a single percentage (dependent) variable, ...
Julie's user avatar
  • 811
10 votes
3 answers

Why is ANOVA not p-hacking?

Say we have some data with many parameters. As an example let's say I'm an not-so-ethical journalist working for a food website and I'm looking to write some clickbait article "backed by science&...
gazm2k5's user avatar
  • 315
7 votes
4 answers

Null hypothesis for ANOVA for regression

Context: I know the "classic" ANOVA framework: we have $n$ groups and $k$ measurements of a variable $X$ for each group. Let $µ_1$, $µ_2$, ..., $µ_n$ be the mean of $X$ in each group. ...
Basj's user avatar
  • 632
9 votes
2 answers

Is there a multiple testing problem when performing t-tests for multiple coeffcients in linear regression?

This question comes from a discussion on the recent post by @rvl It's all in the family; but do we include the in-laws too? Here's a common scenario that I've seen many times. A researcher runs a ...
Chris C's user avatar
  • 2,630
3 votes
2 answers

If I have one non-significant factor level in a glm, is that entire variable now considered non significant?

I have a question similar to this one, but I just wanted to follow on and ask if the entire variable is now insignificant? I have a factor with 3 levels. When doing the model simplification, it showed ...
trizzo's user avatar
  • 31
2 votes
2 answers

Is there anything like a two-way ANOVA but for continuous independent variables and a nominal dependent? Also, alternatives to logistic regression?

I want to determine the interaction between two of my continuous (scale) independent variables on the one dependent variable, which is dichotomous (cases are coded as 0 and 1). I was going to use a ...
Sophia's user avatar
  • 21
2 votes
2 answers

How to get P-Values of Categorical Features?

I have dataframe which contains numerical and categorical features. I am trying to get p-values of these variables using OLS. I'm creating dummies to get p-values of categorical features. But in this ...
talatccan's user avatar
  • 121
5 votes
0 answers

How to determine the significance of an interaction?

My question is simple: How do you determine the overall significance of an interaction (i.e. the marginal effect of $X$ on $Y$ for different values of $Z$)? But the background is a bit long-winded,...
landroni's user avatar
  • 1,133
2 votes
2 answers

How to interpret Pr(>|t|) of factor variables? [duplicate]

How to interpret Pr(>|t|) of factor variables? The reason asking is the following: ...
mavavilj's user avatar
  • 4,129
2 votes
1 answer

Why does overall-F-test is considering right tailed only?

I've seen this overall F-test several times, and when they compare F-statistics or $\alpha=5$% with its p-value always use right tailed, whereas the hypothesis is formualed as $$H_0:\beta_0=\beta_1=\...
LJNG's user avatar
  • 331
2 votes
3 answers

Linear regression: F-test for lack of fit (using ANOVA to test regression model) - intuition?

This is the data set: I'm looking at a simple linear regression. The data is quite trivial. ...
Florin Andrei's user avatar
1 vote
2 answers

Multicollinearity and Interaction Effects

I know similar questions were asked before. However, none of the existing answers help me with my problem: I have a gls model with y=B0+B1X1+B2X2+B3X1X2+e. The VIF value for X1 and the interaction ...
Dave's user avatar
  • 11
2 votes
1 answer

How to run backward elimination in $R$ with both categorical data and numeric data? [closed]

Usually in backward elimination, we start with the full model of all covariates, check the $p$-value of $t$-statistic for each covariate (which is compared between the full model and the model minus ...
The One's user avatar
  • 225

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