All Questions
Tagged with categorical-encoding linear-model
18 questions
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Understanding the process of tweaking contrasts in linear model fitting to show all levels
The accepted answer to this question on SO accomplishes exactly what I need: Comparing all factor levels to the grand mean: can I tweak contrasts in linear model fitting to show all levels?
However, I ...
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How to combine 2 ordinal variables?
I have an assignment that gives two ordinal variables: Education (1-poor, 2-medium, 3-high), Wealth (1-poor, 2-medium, 3-rich). The chi-square test rejects the independence of these 2 variables, so my ...
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How to write a regression formula with dummy variables
my regression is relatively simple. I have a dependent variable, age (A), and its values for 8 types of employees (T) for 6 years (Y). I run it in R and get some meaningful results, which show how A ...
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Interpreting categorical variables with reference level in linear model
I wonder how should I report the results of categorical variables with reference level in linear model?
The response variable of my model is Duration (time taken to reach 25C for an animal model). My ...
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Is there a fundamental mathematical reason that ordered factors are represented as orthogonal polynomials in linear regression?
At least for R, Chambers/Hastie write in their book "Statistical Models in S" in chapter 2.3.2 "Coding Factors by Contrasts":
Ordered factors are coded so that individual ...
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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 ...
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2
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Why are models based on coded (-1,1 etc) and non-coded variables (as they are) very different? What should I use for publications?
I am doing factorial experiments in R. I noticed when I use my variables as they are vs. coding them into -1,1, they are all very different. Here is my sample code. ...
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How do I interpret price elasticity when using state specific dummies and price, dummy interaction
I have price volume data for 3 states for which I want to calculate price elasticity for each state.
The model has the following setup:
$$
\ln(Y)=A_1+ A_2\ln(P) +A_3D_1 +A_4D_2+ A_5\ln(P)D_1 +A_6\ln(P)...
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It is possible to use regression to measure the correlation between a continuous variable and a dummy variable?
I have 3 columns: one column is a continuous variable (e.g., age) and the other two columns represent dummy variables with values 1 and 0 (yes/no).
What kind of regression do I have to use to measure ...
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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 ...
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Can I use month as a numerical variable (and not as a categorical variable) in linear regression
Let's say my response is $Y$.
I know for a fact that $Y$ decreases during winter time, and then starts to increase around spring. So, does it make sense to use month (not as a categorical variable) as ...
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1
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Do I need to get dummies for "binary" categorical columns?
My question is about a multi-variate linear regression model. I am experimenting with Python's sklearn library with the Ames Housing data set: http://jse.amstat.org/...
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1
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Can SAS Least Squares Means estimation algorithm be translated for a design matrix in Reference coding?
My question is whether it’s possible to compute lsmeans defined in this SAS algorithm if the design matrix is not in GLM form. In particular, in R, if one feeds that design to model.matrix(), then ...
- 2,754
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Dummy variables and interactions
To avoid perfect multicollinearity, a common practice is to drop one dummy variable when encoding categorical variables in a linear regression model (avoiding dummy variable trap). I am using this ...
- 213
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27
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Multiple linear regression with dependent as a dummy predictor
I have a model $Y = \alpha + \beta_1X_1 + \beta_2X_2$.
$Y$ has a bimodal normal(ish) distribution, so I'm looking to see if the relationship between the predictors and the response is different for ...
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Multiple regression with dummy variables and interaction term
We have done a multiple regression analysis to see how gender and experience affect salary. We used a dummy variable for gender and then we also added the interaction variable (female work experience)....
user234982
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Coding categorical variables for linear regression and random forest, factors/characters
I am a newbie in Data Science so that do not judge me for this questions.
Making a regression model (linear model, lm_model) with numeric and categorical variables, I realized that Estimate ...
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3
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Difference between fixed effects dummies and fixed effects estimator?
I started to read about panel regression models. However, I am a bit confused about the different model specifications in the fixed effects model:
Does a fixed effects panel regression always mean ...
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