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 ...
427 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. ...
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 ...
18 views

### After the linear regression on the main predictors, how to include the interactions of them?

I'm currently using R to do a multiple linear regression with 7 main predictors. I've already completed the first step of regressing the dependent variable onto those main predictors. ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
130 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 ...
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 ...
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 \...