Linked Questions

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1answer
428 views

Should a non-significant adjustment variable be kept in a regression model? [duplicate]

I'm working with a structural equation model to study influenza infection risk. As age is a known risk factor to explain infection, I therefore adjusted my infection outcome on the subjects age class. ...
0
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2answers
224 views

How to interpret logistic regression output? [duplicate]

I have the R output for the logistic regression model. It seems that only the intercept and psa are statistically significant. Does that mean I should remove sorbets_psa and cinko from my model and ...
1
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0answers
131 views

Removing insignificant variables? [duplicate]

Suppose you fit a linear regression model on some data with 10 variables. The F-statistic shows that 3 of them are significant (p < 0.05) , 2 are within trend (0.05 < p < 0.10), and the other ...
11
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2answers
64k views

What is the difference between “factors” and “covariate” in terms of ANCOVA? [duplicate]

I am a bit confused on the term "covariate". It seems like the term can mean two different things. In ANCOVA, the term is used for the third variable that is not directly related to the experiment. ...
3
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4answers
10k views

How to identify which features are more likely to contribute to the desired outcome?

This question is in tandem with my earlier question here: Using ML approaches to build a recommender engine for sales team However, now I'd like to discover insights about x features as ...
5
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1answer
2k views

When is it better to use Multiple Linear Regression instead of Polynomial Regression?

In the course I've just learnt Multiple Linear Regression and Polynomial Regression. Why would you ever use Multiple Linear Regression when Polynomial Regression will always fit the data better?
2
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1answer
14k views

How to interpret non-significant effect of a covariate in ANCOVA?

I need to use ANCOVA to analyse effect of executive functions (EF-covariate) on scores collected during a test. I want to compare this effect between a control and schizophrenics group (variable ...
0
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2answers
2k views

How to remove one of the factor from the model?

We have a variable "pos" in the regression which has three values : guard, forward, and center. My regression looks like y~a+factor(pos) But one of the factor's value is insignificant (i.e. forward). ...
3
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1answer
15k views

Regression - What to do with insignificant variables?

Please pardon me if you find this question very silly but this doubt has been troubling me for some time now whenever I want to run a regression. I am working on SAS. I have a dataset which has 24,...
1
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1answer
2k views

what to do if all control variables are insignificant and none affect the main effects?

All the control variables were there because they affected the dependent variables in previous studies. However in my dataset, all are insignificant and do not affect the main effects. Should I ...
1
vote
1answer
4k views

Are insignificant variables included in calculation of predicted probabilities?

When calculating the predicted probabilities in a logistic regression model, do we consider all the variables or just the significant ones? For eg: Let's say my model has: dependent variable Y and 3 ...
1
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1answer
2k views

Help writing covariates into regression formula

Can someone take a shot at writing a formula using covariates into a linear regression formula? I need some feedback to see if I am on the right track. Much appreciated! Here are my basic ...
6
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1answer
204 views

Is there a counterexample to the claim that throwing away “insignificant” predictors doesn't generally harm a model?

I have learned from this site (see question here), and from Frank Harrell's Regression Modeling Strategies that generally speaking one should not remove variables because they are insignificant. I was ...
4
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1answer
177 views

Model selection, issues of judgement

I have a general question on model selection strategies in regression models. In my research, the main goal is rarely prediction but almost always estimation of effects of certain variables. I have ...
0
votes
1answer
716 views

ROC analysis and death/recurrence as binary marker

I am doing ROC-curve analysis on my patient cohort, and I am wondering if it is statistically ok to use "death" and "recurrence" as the binary marker, even though these parameters will be influenced ...
3
votes
1answer
483 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
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1answer
247 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
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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
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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
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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
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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
113 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 ...
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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
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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
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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
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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
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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
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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
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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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