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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How many observations should there be for the less frequent level of a binary variable, in order to include it in MCA?

I am conducting a multiple correspondence analysis (MCA) on several binary variables. This link says: The graphs above can be used to identify variable categories with a very low frequency. These ...
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Interpreting interaction effects for categorical reference group in regression

I am running a regression model in R including the following variables: Intent = continuous DV Attitude = continuous IV Story = categorical IV in 4 levels: Consumer, Heritage, Vision and Product ...
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About the Numbers of Dummy Variables

I have a question on the choice of dummies in categorical regression. If there are 4 categories, can I just choose 2 dummy variables to represent them in the following way: Category-Z1,Z2 c1-1,0 c2-0,...
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How can I do this ordinal regression?

How can I perform a ordinal regression analysis in R with the data shown in table 1? I have already tried to order my data (image 1). But now I have no idea what to do next. 1 - 6 represent class 0 - ...
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Missing "None" class in outcome variable. Least bad way of handling missingness?

I'm dealing with a preexisting dataset with an outcome variable of suicide which entails the following classes, of which multiple can be selected, but they roughly escalate in severity. Check if ...
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Partial effect of numerical variable for a fixed level of categorical variable in regression

I have a regression model (in R) as follows: lm(price ~ time + color + brand) where, price be the second hand price of sth (numerical), time be number of years ...
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Simultanously fitting multiple regression models on one dataset

Suppose there are two groups of (x, y) pairs, and that x and y are linearly correlated but with different slopes and/or ...
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How to determine sample size when performing indirect sampling?

Problem Summary I want to know the minimum sample size needed for a given confidence level and margin of error when performing indirect sampling where samples from the two populations are not one-to-...
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Which statistics test should I use?

Group High is a year in which there was a high temperature change and group Low is a year in which there was a low temperature change. The classes represent an the percentage of coverage for a species ...
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Binning and WoE transformation. Reducing number of categories for high cardinality features

I'm doing a credit default risk project. I have some features like a job title that has >100000 unique titles. What is the best way to reduce cardinality in a meaningful way? The end goal is to get ...
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Using multiple mean tests instead of linear model

First, I would like to apologize because I'm a beginner in statistics and I'm surely confused on some points. This is one of my first statistic work doing for university. I would like to explain a ...
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Clustering high-dimensional, categorical data

I'm trying to cluster ingredients in recipes to see which recipes cluster together. This is a kaggle dataset here: https://www.kaggle.com/datasets/shuyangli94/food-com-recipes-and-user-interactions ...
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How to consider categorial ordinal variable?

First, I would like to apologize because I'm a beginner in statistics and I'm surely confused on some points. I would like to explain a continuous quantitative variable, which is a species activity, ...
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Should I transform numerical variables to categorical variables in GLM?

I'm building a GLM with couple of variables and I have a problem with how to organize my data. I have both numerical and categorical data and I'm struggling as to how should I structure 3 variables. I ...
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Binary logistic regression with dummy variables for several different IVs

I want to carry out a binary regression where the DV is 0 = Never considered giving up pet, 1 = have considered giving up pet. I have several categorical variables that I want to enter into the model: ...
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R statistical test for two groups with three categorial variables [duplicate]

I have two groups, in which three possible outcomes appeared at different frequencies, and I wanna know, if there is a significant difference in-between the groups. For instance, I have two potatoe ...
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R statistical test for two groups with categorial data

I have two groups, in which three possible outcomes appeared at different frequencies, and I wanna know, if there is a significant difference in-between the groups. For instance, I have two potatoe ...
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Interpretation multiple linear regression with cumulative coding for ordinal variable

In order to do a multiple linear regression with categorical variable, I transformed them with the cumulative coding : My problem is in the interpretation of the results of the regression : from what ...
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Logistic Regression on multiple classes (Shouldn't it be only on binary?)

I'm a bit confused with the usage of logistic regression for multi-class classification. My understanding is that a logistic regression is dichotomous (two possible classes), so in the example of the ...
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Ordinal Regression with Categorical Predictors in R (Proportional Odds Logistic Regression)

My independent variable is Party Identification which I think will be best to create dummy variables for (Conservative, Labour) and then Lib Dem would be the intercept if I'm not mistaken. The ...
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Using Cramér's V to evaluate correlation between categorial variables with small numbers within contingency tables

I am evaluating correlations between categorical variables in a data set. I have seen Cramér's V is one way I can calculate this, and I know it takes the chi-squared statistic as one of the elements ...
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How to treat dummy variables and their interactions terms with an endogenous variable in a IV context?

I ran the following model with the instrumental variable Z1 because I think that X is endogenous: ...
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How to find what categorical variables explain a continuous dependent variable?

I am currently working on a statistical analysis for a project, I have a dependent variable ($y$) that represents delays in days, it's continuous and take integer values. I also have a set of over 90 ...
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measure of association between dichotomous variable and non -dichotomous (category of 5 levels) while correcting for multiple confounders?

I have a data with 2 groups (fit/healthy) and dietary intake data as ordered categories (less frequent to more frequent as 1,2,3,4,5). I have to assess the relationship between the groups and the ...
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How to analyze a time series of categorical data?

I have some data that look like this: ...
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Are my random effects nested or crossed?

I am using the R package lme4 to build a mixed-effects model. My data is set up in the following way: ...
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Fitting a multinomial glm for a very large dataset

I have compositional data where for two groups, where each is represented by two ages, there are 100 possible categories for which I observed counts: ...
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What statistic would I use to explain the discrepancy between two binary variables?

I have 3 variables in a large dataset: whether students passed their multiple choice portion of their final (binary: pass-fail), whether they passed qualitative portion (binary: pass-fail), and ...
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Test whether two categorical questions are statistically different?

I have two questions (Q1, Q2) and they can be answered with either Yes or No. I want to test if there is a significant difference between the answers to Q1 and Q2, because the questions are related to ...
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Categorical and ordinal variables and one dependent discrete variable

Í have a dataset with two categorical variables: let's say "city type" (categorical) and "living crampedness" (ordinal), and one discrete dependent variable ("house square ...
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Interaction between categorical variables with multiple levels in R

In the dataset I need to analyse, I need to look at whether the effect of people's profession (3 categories) on their scores on a test (I have already tested for this effect and found one) differs ...
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Trying to Understand my Data: New to Statistics

I’m new to statistics and I’m a bit overwhelmed by all of the methods that I’ve been reading about. I’m finding that my biggest hurdle is understanding how my data would fit into different models. I ...
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Categorical linear-model coefficients from a pairwise competition experiment

I am presenting a question for which there may be a simple statistical answer, but I have prefaced it with perhaps a longer explanation, to err on the side of caution, in hopes that the data make more ...
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What hypothesis testing for comparing two categorical distributions?

What statistical test do I need to use to test for a significant difference in the distributions of two different categorical variables? As an example, I need to test whether the distribution of a ...
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Binary variable in regression model (interview question)

I got this question, it may be easy but for some reason for me is not: you are given a binary variable $b\in [0,1]$, that has no predictive power on $y$, but has some on $X$. How would you use it to ...
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interrater reliability with 12 pairs parents rating their own children in categorical variables

Please accept my apologies if the answer to this question already exists. This is the first time for me to do a study investigating the interrater reliability of a questionnaire. There are 12 pairs of ...
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Interpreting output of models with categorical variables in R

I have a data set that contains coral reef data- count of fish (C_TOTAL), the habitat complexity measurement rugosity (RUGOSITY), and the area of the reef that the data was collected at (ZONE- 5 ...
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Wanting an opinion on whether I should run my data as a correlation, comparison, or as a chi squared? [duplicate]

Problem I am trying to analyze my data being the color of my seeds (SEED COLOR) vs how the roots turned out when harvested (ROOT COLOR) and compare the two. I converted all of the colors to a number ...
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Question about proper Data Analysis methods for A Discrete Dataset

everyone. I am a fourth-year statistics student and I wonder if I could have some recommendations for proper analysis methods for this dataset. The dataset contains var1, var2, var3, var4, var5, var6 ...
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comparing data subset to whole

I am trying to write a story about my local high school and its gender diversity in AP programs. I have ethnic data for everyone enrolled, and for everyone in AP programs at the school. What/how is ...
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How to predict next occurrence in sequence where data has both numerical and categorical values?

Lets say we have the following prediction problem. Given data of the following form: Number HasProperty1 HasProperty2 1.5 0 1 1.5 0 1 2 1 0 2 1 0 Where ...
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Is feature scaling needed for dataset containing non-categorical and categorical independent variables?

I have a dataset containing 800+ label encoded (2-level as 0 or 1) categorical features and 4 non-categorical numerical features. The dependent variable is a non-categorical numerical value. Should I ...
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Interpreting a factor variable as numeric when quantity is clear and obviously continutous?

I'm looking at a data set from a famous paper by Box & Cox (An Analysis of Transformations) that reports the results of an experiment with yarn machines. It involved 3 factors with 3 levels each: ...
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what association test is the best for categorical (ordinal) variables

I have two variables: Variable A (dichotomous): positive/negative Variable B (ordinal, three level): disease/ maybe disease / no disease. I want to test the association between these two variable, a ...
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How to adjust regression for colinearity within certain levels of categorical variable?

I'm analyzing results from a large workforce survey, with approximately 110,000 responses to each question. We are interested in how certain demographic variables impact employees' opinions, so we ...
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Too many categorical predictors in multinomial logistic regression

I am not familiar with multi-class prediction so I apologize in advance if this questions seem very basic. Here is my dataset: So within the dataset, I am trying to predict which fare product is ...
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If there is only one categorical variable as predictor in the regression model, is the predicted outcome always same as the average of the level?

I have read somewhere that it is acceptable to have only one categorical variable as a predictor in the regression model. From my understanding, does it mean that the predicted outcome using this ...
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Should we use PCA or Categorical PCA or Multiple Response Analysis if categorical variable is ordinal numeric?

The dataset I use includes several categorical variables where values are ordinal numeric. For example, I have a variable X1 of which possible values are as follows: Value Description of value 1 Bad ...
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Does it make sense to include ZIP code as a covariate in regression model?

Background I have a dataset representing a large group of people that I'm using to specify a Cox proportional hazards model of a binary outcome on some explanatory variables. My outcome variable is a ...
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Which test for a withinparticipant design with 2 categorical variables (with each participant having a value in each condition)

Design : two categorical variables. First : the independent variable : "type" with two conditions : intra & inter. Next, the measured variable : "consistance" with two ...
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