All Questions
Tagged with categorical-encoding r
122 questions
2
votes
0
answers
45
views
Dropped variable in regression output in R
I am running a linear regression trying to predict an outcome y that is a numeric, continuous variable based on a variable with three levels (A,B,C) and three more variables that represent the ...
Καλλιοπη Προβιδα
5
votes
2
answers
109
views
How to calculate the reference level interaction in regression in R?
I am very confused on calculating the reference level interaction in regression in R.
Here is the sample code:
...
- 364
2
votes
2
answers
94
views
Recreate `lm` Categorical Regression
Consider the code, which contains regression using lm of two categorical and one continuous variables without interaction using data from the correct model:
...
- 639
0
votes
1
answer
57
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Indicator variables/treatment variables as an independent variable?
Can a dummy variable or treatment variable be an independent variable? My independent variable take the value 1 if a flood occurs in a specific country in a specific year and 0 if no flood happens. ...
0
votes
0
answers
34
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Why does removing the offset change the F-statistic of an anova model in R?
When a linear model with only a single categorical variables is defined without an offset, the F-statistic reported by summary() and ...
- 1
3
votes
1
answer
45
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Logistic regression in R: Handling mixed numerical and categorical variables
I'm attempting to fit a logistic regression model in R and need some guidance on handling both numerical and categorical variables simultaneously, especially when looking for significant explanatory ...
- 131
0
votes
0
answers
36
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Opinion about conversion of factor to numeric variable during model development using caret package
caret package automatically converts factor variables to one-hot encoding. We can also convert the factor variable to a numeric variable before training any model. ...
- 107
4
votes
1
answer
278
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Should I remove the intercept when I have one dummy variable that covers all the categories in a categorical variable?
I have a categorical variable that has $4$ categories, and I have two dummy variables, $x_1$ and $x_2$, that cover this categorical variable. The $x_1$ variable has values of only $1$ without any ...
- 43
2
votes
1
answer
454
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When I change my reference level on my GLMER in R, why do the p-values change and why don't the estimates add up? Emmeans solution in answer
I am new to this. My study has three conditions (between subjects - low coordination, high coordination, high coordination with ostensive cues) and three repetitions of a game (within subjects - Game ...
0
votes
1
answer
34
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Differences in Regression model for Dummy Coding (factor vs. recode) [closed]
I have the following problem: I generate Dummy Variables with the recode and the factor command. In my regression I got different output for the "lower middle" variable and couldn't explain ...
- 3
1
vote
0
answers
82
views
Difference between using a categorical variable vs separate dummy variables
I have 2 drug treatment groups, namely Cis and RT. So, a cell is either exposed to none, Cis only, RT only, or a combination of Cis+RT. There is also another cancer modality group.
I would like to ...
- 227
0
votes
1
answer
69
views
OLS model specification that includes all dummy variables with a predetermined coefficient
I'm working with a OLS model that includes dummy variables (quarters of year). Here's what I would specify it:
$$y = \beta X + \gamma_1Q_1 + \gamma_2Q_2 + \gamma_3Q_3 + \epsilon$$
However, in the ...
- 769
3
votes
1
answer
362
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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
3
votes
1
answer
558
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Does it make sense to convert a single dummy variable into a factor?
I have an R lecture script infront of me, where we are using logistic regression to try to predict the probability that an observation belongs to the target class (e.g. y_i = 1) or not (e.g. y_i = 0). ...
- 31
0
votes
1
answer
32
views
Finding model for categorical Data
I'm trying to find out a model that adequately describes effects of gender and length on food choice. For gender; 0=Male and 1=Female, length; 0=Subadult 1=Adult, Choice; F=Fish I=Invertebrates and O=...
- 3
0
votes
0
answers
23
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Showing names of levels in glmer R [duplicate]
I have a simple question that would help me a lot in interpreting my results
I ran a glmer model in R with the following variables:
a binary DV that is dummy coded
a categorical IV1 named "...
- 23
3
votes
2
answers
1k
views
Which groups are reference groups in a regression model with interaction?
What are the reference groups in a regression model where there are interaction categories? Using the iris dataset in R, I've created a category with three levels ...
- 615
3
votes
5
answers
2k
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Multiple linear regression with lm() in R, why is the intersection dependent on the name of the "first" country
I have a question about the function lm() used for multiple linear regression analysis.
Context: We have a dataset (that I cannot share) where $y$ is the proportion ...
Louise
1
vote
0
answers
2k
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How to interpret SEM mediation analysis results (using Lavaan in R) with binary exposure and outcome variables
I have built SEM model in R using Lavaan. My aim is to report on the indirect effect.
The data I am using is confidential, so I will not be able to share it or provide a reproducible example. Since I ...
- 11
0
votes
1
answer
68
views
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
2
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1
answer
117
views
how to interpret classes dependence that are not the reference class in a linear model
If we run the three following codes:
...
2
votes
1
answer
178
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Am I interpreting my lm() summary() results correctly in R?
(this question I originally posted in stack overflow)
I want to know if I am interpreting the factor() function in R correctly. Suppose I have a variable with 10 ...
- 355
1
vote
1
answer
504
views
should I use n-1 dummies variables or all variables for a multinomial logistic regression?
Recently I have been working with gut microbiome data, like abundance and its metabolic content (but for purposes of the question this may be indifferent). I'm inexpert in the field of multinomial ...
- 11
0
votes
0
answers
793
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Missing outputs or coefficients from multiple linear regression?
I have a multiple linear regression I have completed below:
...
- 155
1
vote
1
answer
3k
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Using dummy variables in a linear regression model in R - no need to manually encode when using factor or character string vector types?
A source of confusion that I often come across relates to when people want to use categorical data, where the number of categories is greater than 2, in a linear regression (simple or multiple) and ...
- 179
1
vote
1
answer
180
views
Custom-define contrast - mix between dummy and Helmert coding
I'm trying to use custom-defined contrasts. They are sort of a combination of traditional dummy coding and the last contrast produced by reversed Helmert coding.
In short, I want to compare each of ...
- 153
1
vote
1
answer
3k
views
Is one-hot encoding required for categorical variables in R (logistic regression)?
I created a logistic regression model in R and fit the model using the MumIn package. I have several categorical variables that were coded as factors. For example, season (summer, fall, winter, spring)...
- 39
1
vote
1
answer
2k
views
Interaction effects in regression models - should I include reference category?
I have a question about coding interaction effects using dummy coding which I’d be really grateful for your advice on please.
Imagine I want to design an experiment to measure the impact of amount of ...
- 11
1
vote
1
answer
4k
views
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
1
answer
800
views
Difference-in-Difference with two control groups and one treatment group over the same period of time using RStudio
So I'm trying to run a regression for one of my economics classes with one treatment group and two control groups over a period of time. I'm currently trying to create a dummy (binary) variable to ...
0
votes
0
answers
241
views
Framework for applying weights to binary variables in regression
Say I am training a ridge regression model on nothing but binary variables. The context being that each variable represents a player - a value of 1 meaning they were playing the game at the time, ...
- 89
2
votes
1
answer
713
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"Group mean centering" a dummy Variable in R for multilevel analysis: how can i do this?
have somebody an idea of how to group mean center a dummy Level 1 predictor in R?
Enders & Tofighi (2007) describe a method to center a dummy variable through substracting the proportion of the ...
- 21
1
vote
0
answers
43
views
3
votes
1
answer
3k
views
Difference between dummy and factor variable?
I've just learnt about dummy variables. Say this is my data:
Location
Nest
XXX
Yes
XXX
No
ZZZ
Yes
YYY
Yes
YYY
No
And I want to do multicolinearity tests/logistic regression in RStudio, so I don'...
- 149
1
vote
0
answers
380
views
How to code a contrast matrix for repeated contrasts (comparing adjacent levels) where the intercept corresponds with the grand mean?
In brief: How to code a contrast matrix for repeated contrasts (comparing adjacent levels) where the intercept corresponds with the grand mean?
Example-Problem:
A factor of 10 levels.
Each contrast ...
0
votes
0
answers
633
views
Why do sum and treatment contrasts give the same coefficients in linear regression?
I have been given a dummy dataset upon which linear regression is performed and treatment and sum contrasts outputs are compared.
In this scenario the coefficients are exactly the same and I don't ...
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
3
votes
1
answer
352
views
Helmert coding for mixed models in R
I am using R to analyse data from an experiment with six conditions. Condition has two dimensions: for cognitive load, I have two levels (load and ...
- 31
0
votes
2
answers
468
views
Regression/classification models and dummy variables [duplicate]
I want to build regression model (linear and logit) but one of my independent variables is categorical variable with levels "Gym", "School", "Hospital", "Others"...
- 1
0
votes
1
answer
139
views
Interpreting categorical variable if reference class includes several levels
I have a dataset with several categorical variables. I have been running some regressions and used dummy coding for these categorical variables. The problem is that some specifications lead to perfect ...
- 5
0
votes
1
answer
241
views
Regression in R - dummy variables
Hey I want to build a model in R and one of my idependent variable is categorical (it takes 10 different values). I change the type of this variable from "char" to factor and build a model ...
- 117
0
votes
2
answers
72
views
R: Interpreting high co-efficient with low p-value for a binary variable
I am looking at baby weight data. Now a baby's gender is either male or female. A linear regression model to predict a baby's weight has a high coefficient (-0.38 for female and +0.38 for male). It ...
NRS2000
2
votes
1
answer
68
views
Interpreting logistic regression coefficients of a variable overall and levelwise
Context
Let Y be a logical vector and X1 a factor with 3 levels.
Since Y is binary, logistic regression is used.
...
- 462
0
votes
1
answer
1k
views
Time effects with dummy variable - regression
I am doing a multiple regression analysis and I wanted to inspect the time effect by using factor(Year) in R. However, I got the following summary results:
Do you ...
- 3
1
vote
1
answer
996
views
Impute missing values of dummy variables, using R's {caret} package: predicted values in between {0;1}?
I'm using {caret} to impute missing data resulting from non-response to survey questions. All of these variables are defined as numeric, though most are dummies. ...
0
votes
1
answer
29
views
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
views
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
2
votes
1
answer
841
views
Adding a Dummy Variable to glm in R?
I'm running a glm in R with two categorical variables, one of which is binary, the other of which can take on five values. I would like it so that my model returns an intercept value that reflects the ...
- 87
1
vote
1
answer
338
views
How to code non-exclusive variables for logistic regresion
I have a question about logistic regression in R. I want to study the influence of certain comorbidities in patients in predicting deceased status(Y/N). So far, I formatted all my comorbidities(17) ...
- 11