Questions tagged [categorical-data]

Categorical (also called nominal) data can take on a limited number of possible values called categories. Categorical values "label", they do not "measure". Please use [ordinal-data] tag for discrete but ordered data types.

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Latent Profile Analysis in R with continuous and categorical variables

I am trying to do an LPA with categorical and continuous variables. The tidyLPA package is amazing for continuous variables but models don't seem to converge with categorical variables, and the ...
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Which package works for mediation analysis in R when variables are categorical?

I am assessing pregnancy data where my exposure is categorical variable (either dichotomized or ordinal), potential mediator is categorical (dichotomized or ordinal) and the outcome is also ...
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Testing for correlation of two (or more) variables

I have a data set with almost just nominal/categorical variables and one integer. I would like to do mixed effect models (due to having fixed effects) with the data but my models are not converging. I ...
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19 views

Multiple Correspondence Analysis to inform a composite variable

I have 28 categorical variables, some binary, some with many levels (n=161). I want to use some of these variables to make a composite variable to investigate a latent characteristic, and then test ...
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5 views

Where to find large survival dataset with at least one time dependent variable? [closed]

Looking for a large dataset for survival analysis where at least one of the variables is time-dependent. For example, this a sample dataset: ...
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19 views

Represent Integer Categorical feature as both Numeric and Categorical

I'm dealing with tabular datasets where it's really hard to tell if the integer column is Numeric or Categorical. My main consideration is the accuracy of the model that I am building (no deep ...
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Does using a grouper algorithm in an explanatory or causal inference model use up degrees of freedom?

For example, say I'm performing a regression to explain how much various factors (age, sex, diagnosis, procedure) affect total annual medical cost among patients. There are thousands of diagnosis and ...
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19 views

Variogram of categorial data?

I have a thematic map as raster data with classes assigned as numbers: 1,2,3,4. These are categorial classes and have no linear meaning. I am interested if there is spatial autocorrelation in this ...
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26 views

Linear regression or something else?

Premise: I know there are lot of questions like this one. The reason why I'm posting it anyway it's because I'm not sure about the real nature of one of my two variables. I want to determine if two ...
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Analysis of One Binary Variable and Continuous Variables - Ecological Data

I have a dataset that I am trying to analyse, it consists of: A binary variable which indicates a tree species (0 = deciduous 1 = evergreen) with 100 measurements each. N which is leaf nitrogen ...
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Panel Data in R - Can I implement a plm regression with categorical data?

I am working (In R) on a panel modelling of an econometric problem. I have : one dependent variable : Y with values in real positive numbers two explanatory variables : VAR_1 (real positive), VAR_2 (...
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Analyzing a categorical variable with 'Only A', 'Only B', and 'Both A and B'

I may not be searching the correct terms to get an education on this seemingly simple question: I am analyzing the correlation between two categorical variables with Pearson's chi-square test and its ...
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Is there an R function for finding couples of categorical variables more similar to each other? [closed]

I'm working on a dataset containing only categorical variables. I'd like to find a function (I don't know if it's possible with cluster analysis) that allows me to cluster the most similar variables ...
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Uneven intervals for a score

I want to create categories to classify some variables into "Good", "Regular" and "Bad" performance. Each variable has its own measure and its own reference value (like a ...
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Deriving joint probabilities from marginal probabilities & polychoric correlations

Given three ordered-categorical variables: $u_1, u_2, u_3$ with $K$ categories, I'm trying to derive their expected variance-covariance matrix using their marginal probabilities, thresholds, and ...
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12 views

hierarchical clustering with categorical data

I have a dataset of 10K patients (row variables) with 10 disease conditions (such as heart condition, asthma, diabetes etc) along the columns. All the disease conditions are binary variables (yes/no). ...
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How do I study the association between categorical rasterised environmental variables in R?

I would like to study the association between categorical rasterised environmental variables in R. Is there any way to do it in R?
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Interpreting t-values in a categorical regression model: R [duplicate]

I am having trouble understanding how to interpret t-values of a categorical variable in a multivariate regression. Please see an example below. ...
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1answer
72 views

Understanding which categorical variable has a bigger influence on continuous dependent

I am running a linear regression for Explanatory purposes. Y is continuous and all the explanatory variables are categorical. I understand that the regression coefficient of these variables is the ...
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17 views

Multivariate Regression: Both Continuous and Categorical Predictor Variables

I am involved in a meta-analysis assessing the role of multiple baseline characteristics (e.g. age, BMI, symptoms and signs) in a given disease. One element of our analysis includes a multivariate ...
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Checking conditional effects under all categorical predictor levels

When using many predictors, especially categorical ones, there is a possibility of overfitting due to the remained small number of data points for analysis. Is there also a possibility to check ...
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GLM in R: Subset Covariate to specific factor Levels

I like to conduct a GLM in R like this: glm ( Y ~ X + Z + a + b + c + d, quasipoisson(link="log")) with Y as dependent Variable (Count Data, integer) X as ...
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Estimation of Conditional Probability of Two Categorical Distributions

I trained a neural network model that can predict how much a given legal article could be cited for a given case description. In this model, if I feed the neural network with two different arguments - ...
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24 views

One hot encode nominal categorical variables for random forest? [duplicate]

I looked for this before but I couldn't find it exactly, so let me know if it's a duplicate. My question is, should categorical variables be one hot encoded to run Random forests? Or just transforming ...
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28 views

Analyzing Relationship across Categorical Variables

I am working on some corpus data related to semantic tagging and syntactic constructions. Finally, I prepared a table of results yet I am unable to go on further due to lack of statistical knowledge. ...
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Should I log a variable that is not normally distributed to be able to make categories for crosstabs?

I’m researching the correlation between democracy and the amount of foreign aid per capita received in developing countries. My database contains panel data from the same population (N=121) in ...
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Adding categorical features to each pixel of an image for use in CNN model

I am building a model which generates new image from an imput image. I have a training set of input images and desired generated images and I also have some categorical data for each pixel of an image ...
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Poor performance using Neural Networks

I have the below dataset which tells the number of visitors at different locations. I am trying to predict the 'Count_in' column which describes the count of the visitors at a given location and a ...
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22 views

selecting principal component for wealth index?

While creating a wealth index using the household asset (dichotomized ), Can we take the second principal component (comp 2) if it has more relative positive eigenvectors (For example: as shown in the ...
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19 views

Analyze which level of a categorical variable has changed the most between two given distributions

I want to analyze whether the frequencies of a categorical variable X (e.g. icecream color) collected in a second survey are higher or lower than in a first survey. I know that one can use Chi-square ...
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14 views

Multicollinearity in multiple linear regression with only categorial variables

I have to do a multiple linear regression with a numeric dependent variable and three categorial variables (2x2x4) as independent variables. Do I have to check for multicollinearity and if so, why and ...
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How to identify coefficients for all levels of categorical variables when you have multiple of them

I have an equation like y ~ x1 + x2 + x3 + x4 where the first 3 variables are categorical and the last one is continues. I want to identify the coefficients for all ...
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52 views

How to find the optimal cut point of a categorical variable?

I have two categorical variables (x and z) as shown in the frequency plot below. Y-axis is the count of variable x. As evident in this plot, there is a clear relationship between x and z variables. I ...
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Is it reasonable to convert factor (only 0/1 involved) into numeric data?

If I have a simple data with only 2 levels of factors: ...
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Regression between two interest rates

I am trying to predict one interest rate that depends on the other. When Plotting it on scatter plot the relationship is mostly linear in the middle part of the curve. The only issue is on the extreme ...
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How to use an F-test to understand if a categorical input is statistically significant?

I am trying to understand F-tests in general and how to apply one for a particular problem for a data set in "Introduction to Statistical Learning with Applications in R". The data set is ...
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23 views

Interpretation the correlation between continuous and categorical variables

Question I implemented the approach mentioned in this answer and applied it to a car dataset, where I am focused on the correlation between brand (categorical) and the price (continuous variable). The ...
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38 views

Logistic regression coefficient interpretation

There is one binary dependent variable (Winner/Loser) and there are three independent variables which are also categorical in nature: Age (Below 31, 31-40, 41-50, 51-60, 61 and above while retaining ...
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How to correct zero cell counts for odds ratio calculations when variable has >2 categories

I am trying to calculate odds ratios for several univariate models with a binomial outcome. The problem is, for some of my variables, I have at least 1 zero count cell. It seems that the Haldane ...
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22 views

Interpreting logistic mixed model estimates of a model with continuous and categorical predictors

Newbie here. Sorry in advance if I express poorly as I don't completely master yet the vocabulary of statistics! I am performing a logisctic mixed model - with glmer - which presents as follows: CE ~ ...
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6 views

Creating an index using transactional data

I have a dataset of a series of leases. Variables we have: precinct, date (in quarters), lettable area, price as well as a few others. These assets are not homogenous, although are comparable. In some ...
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1answer
20 views

Ordinal vs. Nominal?

Say I have a dataset of patient information, and some variable X representing labels for degree of a burn, with possible values of X = {1,2,3,4,5}: 1: First-Degree Burn 2: Second-Degree Burn 3: Third-...
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The most important matrices for evaluating a predictive model for customer churn

My questions is as above. What are the most important matrices (f1, precision, recall...etc) that I need to prioritize my work to improve for evaluating how good a model predict customer churn and the ...
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17 views

Multiple regression: Is it acceptable to include a categorical covariate with few observations across levels?

I am interested in the influence of age and body mass index (bmi) on brain size in a patient group. I have the following multiple regression model (using R): ...
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1answer
37 views

Best solution for sports statistics [closed]

I have created a floorball sports statistics in excel. It works like this: I put in data from each match (mininal required data like who was present and who scored etc.) and then I have sheets which ...
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1answer
38 views

Checking the normality and assumptions of residuals in a regression model with a categorical IV

I have conducted a hierarchical regression with 2 categorical variables. One of which I am controlling for (ethnicity-dummy coded). I need to check the assumptions of normality, linearity and ...
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15 views

correlation between discrete and continuous variable

Suppose I collect data of three variables $X_1$, $X_2$ and $X_3$, where $X_1$ and $X_2$ are continuous and $X_3$ is discrete. I know that there are various measures of correlation between a continuous ...
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21 views

polychoric factor analysis and use of factor score in subsequent models

To predict the impact of gender egalitarianism on life satisfaction (7-scale ordinal variable), I wanted to create a factor score from a relevant group of variables (mothers should work: agree to ...
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Up to what number of distinct values should I transform a categorical variable in a dummy variable?

When working with categorical variables, it's common to do some sort of transformation. Usually people apply a one-hot encoding. Putting it simply, we transform a categorical into a dummy variable. ...
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25 views

General procedures to check conditions for hypothesis testing?

I am going to have a linear by linear test(lbl_test in R, and the related doc can be found here) but the math underlying it is still a mystery to me after trying my best to comprehend this ...

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