All Questions
Tagged with categorical-encoding generalized-linear-model
27 questions
2
votes
1
answer
49
views
Dummy encoding for the multinomial response variable
I am reading about multinomial response models from the book Multivariate Statistical Modelling Based on Generalized Linear Models by Fahrmeir and Tutz. I am trying to understand the following ...
3
votes
1
answer
362
views
Categorical variable disappears in Poisson GLM summary?
For the variable SelfEthnicity there is meant to be 4 levels.
I have made it so there should not be a reference category, but the R output still only shows 3 Ethnicities.
...
user383651
0
votes
0
answers
107
views
GLM specifying a subset of contrast matrix for factor variable
I'm fitting a binomial GLM with the following formula:
glm(outcome ~ categorical:continuous:factor)
I would like to see the interaction of categorical and ...
0
votes
1
answer
68
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Are these effects missing from my glm output because of a possible dummy trap?
I have a few generalized linear mixed model questions. I have an experiment that asked "is there a differential response between asexuals and sexuals by population density?". I am ...
- 55
1
vote
1
answer
4k
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Interpreting GLM output with categorical data
I am having trouble identifying which reference level R is using for my response variable matnew. I know it sometimes chooses alphabetically, which in this case is "Fail", but I'm not sure ...
- 31
0
votes
0
answers
37
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Can I just use one effect-coded variable instead of two dummy variables when I perform a regression, if there are 3 groups?
To make things simple, let say I ran a basic psychometric experiment and I want to test whether the response time (i.e. a continuous variable) can predict the performance score (i.e. a continuous ...
3
votes
1
answer
909
views
Interpreting the effects of dummy interactions
Warning
This question is quite long, and maybe a lot of you will think it is too long. I however thought, and hope, that if this question gets a proper answer, it will actually be a really good post ...
- 528
0
votes
1
answer
29
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Recalculate the standard error using a different base?
I want to run a GLM with a factor, say car type, as one of the independent variables.
Suppose car type has the following levels: sedan, SUV, and truck. And suppose the base level is currently sedan.
...
- 237
1
vote
0
answers
70
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Interpreting the covariate p-values in a multivariate generalized linear model?
If a covariate in a GLM is "significant" does that mean it is significantly different from the base case (the group not shown)?
Say we have three groups, Control, Exp1, Exp2. We are ...
- 11
1
vote
1
answer
585
views
Why are variables in GLM being split into multiple output variables
I have input for glm that looks like
BMI $grp PRS age gene
24.2 1 3.0 77 0.0
33.8 1 4.0 89 0.0
30.3 1 7.0 58 0.0
I’m inputting this into ...
- 133
0
votes
1
answer
61
views
How to analyse count data that include 0 as a category?
I'm testing the yield of corn subject to two treatments: Temperature (Cold and Warm) and Light Color (Red, Blue, Natural.) The number of plants per plot that produced no cobs, one cob, two cobs and ...
- 51
0
votes
1
answer
54
views
How to handle potential ambiguity when one-hot encoding?
Let's say I have two categorical features: Movie, Director. I one-hot encode both the Movie and Director features for use in a linear regression model.
The problem is that two or more movies may be ...
- 1
1
vote
0
answers
2k
views
When do I have to use orthogonal contrasts instead of non-orthogonal ones?
This is the same question as asked here, but of course I think with a different twist.
A definition of orthogonal contrasts is given in another (great) answer to a popular question on Cross Validated ...
- 712
1
vote
1
answer
486
views
How can I compute the standard error and confidence intervals for the base level on a variable?
I'm running a GLM with a tweedie, log-link function. That said, I have a categorical variable that transformed to dummy variables leaving off one of those variables when I modeled.
Now that I'm ...
- 235
0
votes
0
answers
33
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? ...
- 123
1
vote
1
answer
1k
views
Do we need a reference dummy variable for non-mutually exclusive groups?
I am trying to build a GLMM and have converted a group of factors to dummy variables. Many have multiple groups and I would like to test the interactions between them as well. Do I need a reference ...
- 11
0
votes
1
answer
1k
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h2o glm tweedie for categorical variables?
To build a tweedie glm for categorical variables, the document suggested that I can use data['variable_name'].asfactor().
However, in the model output, there is ...
0
votes
0
answers
36
views
Finding the fitted probability for an aliased constraint in a binomial model?
For a binomial model, with probit link function:
model = glm(response~A+B+C, family = binomial("probit"), na.action = na.omit)
where A and B are continuous, C is ...
0
votes
0
answers
168
views
Model failed to converge in lme4::glmer() when the a factor is centered or releveled
I'm running a mixed-effects model using glmer() function. The modeling works well with R's default dummy coding. But if I center or relevel a factor of 2 levels, the model failed to converge. I am ...
- 43
3
votes
1
answer
4k
views
Results of Type-3 Wald Chi-Square Different for GLMM with Different Contrast Coding
I have just completed a multilevel, longitudinal logistic regression testing, at four different time points, whether participants in an experimental group are more likely to have committed any drug-...
- 2,187
2
votes
1
answer
585
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regression models and dummy variables
I have a output variable and 1 categorical predictor and 3 continuous predictors.
...
- 796
6
votes
2
answers
14k
views
Using Non-numeric Features
I'm just starting out with machine learning. The example I was shown during a mini course I took was the predicting of the sale price of a house given features like:
size of house
number of floors
...
- 1,298
6
votes
2
answers
11k
views
Removing intercept from GLM for multiple factorial predictors only works for first factor in model
I am running a binomial logistic regression with a logit link function in R. My response is factorial [0/1] and I have two multilevel factorial predictors - let's call them $a$ and $b$ where $a$ has 4 ...
- 73
6
votes
1
answer
5k
views
Reference level in GLM regression
In GLM regression I have always been told to set the reference level of categorical/ordinal/dummy variables to the level with the most exposure (level with most data), because this somehow makes the ...
- 1,824
2
votes
1
answer
220
views
Model overall effect of predictor within categories
I'm trying to fit a generalized linear model in R, but am quite new to regression, and struggling to work out how to have predictors nested within categorical variables.
An example of my data:
<...
- 1,118
3
votes
1
answer
2k
views
Non Numeric features in Logistic Regression
I understand that the fitted values for Logistic Regression can be expressed as:
$$P(Y_i=1) = \left(1+\exp(-\hat{\theta}^TX_i)\right)^{-1}$$
where $X_i$ is the feature vector, which will work well ...
- 211
16
votes
2
answers
63k
views
Understanding dummy (manual or automated) variable creation in GLM
If a factor variable (e.g. gender with levels M and F) is used in the glm formula, dummy variable(s) are created, and can be found in the glm model summary along with their associated coefficients (e....
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