Linked Questions

5 votes
2 answers
4k views

Why does removing the constant term prevent the dummy variable trap? [duplicate]

I understand that if you have a dummy variable with $m$ categories that you should include $m-1$ categories in order to avoid perfect collinearity between regressors. However I don't understand why ...
Will's user avatar
  • 359
0 votes
0 answers
595 views

Produce a GLM intercept that does not include reference levels for categorical variables? [duplicate]

I realize that a similar question to this has been asked, but it was not ultimately resolved. I have tried the suggestions posted to that question here, but have had no success. I am using the ...
user avatar
0 votes
1 answer
80 views

Why does the coefficient of a categorical variable (coded 0,1) change when we exclude an intercept in linear regression? [duplicate]

...
Nutan's user avatar
  • 151
0 votes
0 answers
43 views

Why does removing the intercept in my categorical GLM result in the same model? [duplicate]

I'm trying to understand what is going on when I remove the intercept in my model using y ~ x + 0 Why do these models have the same predicted values despite one not having the intercept? ...
Ryan Wilkins's user avatar
7 votes
2 answers
6k views

Dummy variables in multiple regression, why use an intercept?

When performing a multiple regression with dummy variables, is it really necessary to include an intercept term in the design matrix? By dummy variables, I mean indicator variables; a one in the ...
bill_e's user avatar
  • 2,831
4 votes
1 answer
4k views

How can logistic regression have a factorial predictor and no intercept?

I tried a regression in the form ${\rm logit}(Y) = {\rm coefficient}\times X + 0 + e$, where $Y$ is a binomial variable and $X$ is a factor variable with $n$ levels. I noticed that removing the ...
Bakaburg's user avatar
  • 2,867
4 votes
2 answers
595 views

Exists an option to avoid reference categories in logistic regression?

I was wondering if there exists an option to avoid reference classes in logistic regression by transformation estimaters (especially the intercept)? Normally the intercept contains the information of ...
T. Beige's user avatar
  • 307
5 votes
1 answer
1k views

Possible to code contrasts comparing each level to grand mean with no reference category?

I'm working on a health care outcome regression model using the deviation contrast scheme described on the UCLA SAS help page here for a collection of dichotomous predictor variables measuring medical ...
RobertF's user avatar
  • 5,984
-1 votes
2 answers
551 views

redundant level dummy variable [closed]

In classical statistical regression analysis (e.g. linear regression) one level of the categorical variable is usually not used to create a dummy variable to create a reference (e.g. there is only one ...
cs0815's user avatar
  • 2,137
1 vote
2 answers
271 views

Why does removing intercept not change predicition of linear model in the precence of factor predictors? [duplicate]

In a linear model that predicts birth rate (TFR) per country from per capita GDP, the country is encoded in "treatment coding", and there are several measurements (different years) per ...
cdalitz's user avatar
  • 5,022
1 vote
1 answer
309 views

Lme4 Crossed Effects Mixed Model w/ Interaction Terms

Greetings Statisticians! I am trying to create a crossed effects mixed model w/ interaction terms in lme4 to describe a regional analysis of MRI data in mouse brains w/ genotype, treatment, and time ...
Lothar the Quick's user avatar
2 votes
1 answer
374 views

Why is it necessary to "ignore" a level when applying sum contrasts?

I am confused about how sum contrasts are set up. As I understand, if I have some $K$-leveled factor, I can use sum contrasts to compare each level to the grand mean ($M_G$), effectively testing ...
Alex Ten's user avatar
0 votes
0 answers
36 views

Logistic Regression with dummy variables? [duplicate]

I am working on a problem where response variable is binary and my features are dummy variables. I observed when I include intercept to model all the dummy variables' p-values are equal to 1. When I ...
CheeseBurger's user avatar