Linked Questions

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3answers
3k views

Is it advisable to drop certain levels of a categorical variable? [duplicate]

Let's say that I have one categorical variable with six levels, and I then create five indicator variables in order to represent the six levels. If two of the five variables are insignificant, then do ...
1
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2answers
5k views

What to do with dummy variable that is not significant? [duplicate]

I´m running a binary logistic regression to predict the purchase probability for a product. My model contains mostly dichotomous and categorical variables. One variable, let´s say "decision maker", ...
7
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1answer
2k views

If a factor variable is to be dropped in model selection, should all levels be dropped simultaneously? If so, why? [duplicate]

In answer to a previous question factor pooling in model selection was discussed. If a factor or categorical variable is to be dropped in model selection, should all levels be dropped simultaneously? ...
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0answers
2k views

GLM and categorical variable R - remove one category [duplicate]

I am currently running quasipoisson models with a continuous response variable and 13 covariates. I am using glm() and summary()....
1
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1answer
920 views

How to Interpret p-value for categorical variable in multiple linear regresion? [duplicate]

I have a query on how to interpret the result for multiple regression with categorical variables. I have categorical variable called Stay_In_current_city_years which has 5 levels. After running the ...
1
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0answers
208 views

How to drop certain values for a factor variable while fitting a GLM? [duplicate]

My response var is a binary variable. In the predictor variable i have a type variable with levels as l1,l2,l3,l4. And when i run a logit (glm(redonse ~ type, family = "binomial"), Some levels of type ...
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
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2answers
50 views

R linear regression - how to handle when some factors significant while others aren't [duplicate]

I'm playing with the Titanic data set, and trying to figure out what to do about the results I got from a lm that predict the age of the passenger. How should I handle the Cabin values? Some Cabin ...
0
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1answer
43 views

What to do with statistically insignificant dummy/categorical variables? [duplicate]

From the research I've done the common answer is that you can not remove insignificant dummy variables from a regression. I'm having a hard time finding academic papers or books that back up this ...
0
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0answers
35 views

Does it make sense to only drop a specific level of a categorical variable? [duplicate]

I don't have SAS and the dataset with me, so I made up this table (from my memory). Basically this is what I got: After deciding to leave the variable $age$ and $risk$ in my model, I created this ...
0
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0answers
32 views

Dropping dummies from regression by putting them into the reference group [duplicate]

I have the following result of a logistic regression: ...
0
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0answers
31 views

GLM Logistic regression in R: one category is significant, but others are not. Should I drop the variable? [duplicate]

so I am using GLM for logistic regression in R and I have some variables with many factors. I ran the model and has the result like this: My question is: 1. Is this variable significant? ...
207
votes
9answers
94k views

Algorithms for automatic model selection

I would like to implement an algorithm for automatic model selection. I am thinking of doing stepwise regression but anything will do (it has to be based on linear regressions though). My problem ...
9
votes
3answers
8k views

How to apply coefficient term for factors and interactive terms in a linear equation?

Using R, I have fitted a linear model for a single response variable from a mix of continuous and discrete predictors. This is uber-basic, but I'm having trouble grasping how a coefficient for a ...
3
votes
2answers
6k views

Should the final R glm include only significant levels of factors

I am running a glm in R on data with quite many predictors (~50), both initially continuous and factors. The response is binary and the volume of the data is OK (~100K rows), in order to model non-...

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