Linked Questions

3
votes
1answer
482 views

Difference of variable selection and importance estimation

Isn't variable importance estimation a necessary prerequisite for variable selection? Is there any use case where you want to select non-important variables for your model? So, why is variable ...
6
votes
1answer
246 views

When the effect size of a covariate is high and yet not significant

I was reading this answer to the question on whether all covariates should be kept in the model or just those that are statistically significant, and I noticed the point number 2: The effect size ...
2
votes
0answers
790 views

Insignificant squared term but significant linear term

I am estimating the following model: $\ln(y) = \alpha + \beta_1x + \beta_2x^2 $ $\hat\beta_2$ is insignificant while $\hat\beta_1$ is significantly different from zero. However they are jointly ...
1
vote
1answer
360 views

Is it ok to repeat MANCOVA until all interactions are significant

In order to enlighten the relation of three (related) scales describing psychopathology (1 anxiety score and 2 shame scores) with demographic data (gender, place of residence, age etc) collected by ...
0
votes
1answer
562 views

Linear Regression Feature selection: multiple-regression p-value filter versus Lasso / Recursive Feature Elimination

I have been thinking of this problem for days and I can't seem to arrive at a conclusion for feature selection in Linear Regression. Please tell me what is wrong with this simple approach versus ...
4
votes
0answers
497 views

GLMM with 2 insignificant variables has lower AIC or BIC compared to same model without those variables…?

Background This post has been heavily edited from its previous version (three months ago). I am investigating habitat selection of 35 territorial wolves over several years of denning seasons (41 ...
0
votes
0answers
571 views

Interactions Dummies with an Independent Variable

In my model I want to include two dummies ($d_1$,$d_2$) and also the interaction effects of these two dummies with another independent variable, $x_1$. The interaction terms are $x_1\cdot d_1$,$x_1 \...
3
votes
2answers
112 views

If a regression term doesn't do what it was intended to do, is it alright to remove it?

This is going to look like a duplicate of a common question--something along the lines of "Should/can I remove insignificant regression terms?" That type of question has been asked--and answered--here ...
0
votes
0answers
190 views

If removing another variable makes another variable insignificant should it be removed?

This is a logistic regression used for the goal of prediction. Originally a model had ten variables. Two variables were removed using a clustering procedure. Then one variable was removed due to ...
0
votes
2answers
148 views

Regression coefficients significance

What are theoretical reasons to keep variables which coefficients are not significant? I have several coefficients with p > 0.05. What's causing large p values?
0
votes
1answer
106 views

R - Analysis of a Qualitative Predictor with 30 levels [duplicate]

I'm running a multiple linear regression in R. In my linear regression I have 'country' as a qualitative predictor, which dramatically increases the adjusted R^2 value, and lowers my BIC. I want to ...
1
vote
1answer
55 views

Is there anything wrong with this sort of model reduction (p value + AIC)?

I have fitted a model with 7-8 covariates. Here's what I do to reduce it: I first look at the p-values. I select all covariates with p-values > 0.05. Then I remove them one by one, get the AIC, and ...
0
votes
1answer
39 views

Understanding regression modelling: 3 factors, 3 continuous predictors

I am a bit confused about how regression modelling works. I have a response $y$, 3 continuous predictors, and 3 factors. I don't have anything else available. I fit the model ...
0
votes
1answer
38 views

Variable selection for Cox regression repeated for multiple covariates of interest

I am doing a retrospective analysis of the effect of various measures of haemodynamics in sepsis on mortality. I will separately look at the effect of 5 independent variables: 1) shock index 2) blood ...
0
votes
0answers
29 views

Smaller p-values on a selective multiple regression analysis [duplicate]

When I run a multiple regression analysis in Excel on 20 independent variables and 1 dependent variable (in two goes), I obtain in the summary a set of p-values. When I select the (six) ones that are ...

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