Categorical data can take on a limited (usually fixed) number of possible values called categories. Categorical values "label", they do not "measure". Nominal and dichotomous/binary scale types are categorical. Some people consider ordinal scale categorical too.

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Q: Including group dummies vs. calibrating dependent variable

I analyze the dataset obtained through a series of simulations and I am interested in understanding the effect of endogenously generated variable $x_1$ on the outcome $y$, across all simulations. Each ...
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6 views

Interpreting negative regression intercept; proportion response to categorical predictors

probably a simple answer and I'm overthinking or something. I have regression output (Zero and One Beta regression with GAMLSS). I'm analyzing the proportion of time spent demonstrating a certain ...
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28 views

Getting estimate and CI for dummy variable in linear model

I have a linear model based on some variables (age, gaming and tasks) on response time. It looks like this: ...
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25 views

Solve KNN classification using both categorical and quantitative variables in r [on hold]

Im new in this field, I am trying to classify a data set (what influence the alcohol consumption of young people, made of 32 variables like age, family situation, absences at school, etc.) using r. I ...
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1answer
43 views

Log-linear model, Poisson regression, categorical variable with 100 levels

I want to compare the incidence rate(asum) of 100 different cities(cityID) to see if there are significant differences among them. Given that the incidence rate is following Poisson, so it is a ...
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32 views

Influence of categorical variables on continuous outcome

I have a dataset of independent samples where we investigated whether an outcome variable 'TTI' was affected by four levels of relative humidity combined with two levels of oxygen. TTI does not seem ...
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8 views

Q: Probability of category k yielding the maximum occurrence count after N IID trials

Assume we have a categorical distribution for random variable $X$ with $M$ categories. We generate $N$ IID realizations of the random variable and count the occurrences of each category in the sample, ...
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11 views

How to get correlation of each predictor to response

I am wondering how can I get the correlation from one predictor to a repsonse when I am looking at a given data set with many predictors. For example, the output of GLM in R would be exactly what I ...
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15 views

Error: Variable has <2 category levels [closed]

I am using lrm in R to run logistic regression on my data set that has dimensions of 1252 by 96: ...
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18 views

Clustering, reducing number of levels of categorical variable

I'm dealing with this big dataset which has: 1 categorical variable with 90 levels that represent some sort of "geographical area" 3 continuous variables What I'm trying to do is to "aggregate" ...
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32 views
+100

Problems with representing and analysing non-network data as a network?

Suppose I have a dataset with 200 observations of 30 categorical variables. The dataset describes websites and different kinds of design features they deploy (or do not deploy). If I were to convert ...
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26 views

How to treat categorical predictors in LASSO

I am running a LASSO that has some categorical variable predictors and some continuous ones. I have a question about the categorical variables. The first step I understand is to break each of them ...
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11 views

Aggregating Dataset with many categorical variables [closed]

I have this dataset wich is structured like this ...
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1answer
22 views

Regression with Quantitative and Qualitative independent variables

I'm new to statistics and I would greatly appreciate any help on this. I have a response (heart beat, a numerical variable) and five other independent variables. Four are numerical (Age, Weight, ...
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11 views

How to use dummy variables for prediction

I have a sales data and in that data I have introduced dummy variables to capture the sales trend like "is the store open on sunday"."is the sale more that certain threshold" etc. Now if I train a ...
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18 views

Perfect collinearity between one level of two categorical variables

I am setting up a logistic regression model with mostly categorical independent variables (answers to survey questions). Some of the variables have levels like "High-Medium-Low-NotApplicable". The ...
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24 views

How to plot a categorical variable from a GLM

How do you correctly plot results from a GLM used to test a categorical variable? Here is a reproducible example in R: ...
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9 views

3-way interaction with a mixed of continuous variable and categorical variable with 3 or more levels?

Has anyone conducted 3-way interaction with a mixed of continuous variable and categorical variable with 3 or more levels? To be exact, it is 3-way interaction between a continuous variable, a 3-level ...
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1answer
10 views

Conditional probability sub-model so solve setting with a factor that has many levels

I stumbled upon a post of the http://www.win-vector.com/ blog where they treat the problem when a factor with many levels occurs. In my understanding instead of using the factor itself, they use the ...
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18 views

Dummies with different significance

A friend asked me this question to which I cannot answer: he is running a linear regression and he has 3 categorical independent variables which, if used altogether, would give multicollinearity. If ...
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1answer
33 views

How can I combine nominal with ordinal data to build a unique variable?

I performed an Interview with 44 questions Protocol. The structure of questions is based on 18 variables. Major variables are coming from theory. Every major variable consists of 3,4 or more question ...
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7 views

How do I prove that using OLS on de-meaned data gives the same estimates as using a dummy variable regression?

I obtained the FOCs for the dummy variable regression and know that I have to manipulate them to get the FOCs for the regression on the de-meaned data but am not sure how to go about it, as in how to ...
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23 views

How to use permutation test to create null distribution for categorical data?

Consider a population of 1,000,000 individuals. I have examined them all and identified 1000 samples which I believe are not like others. To confirm this I analyzed the 1000 sample regarding one ...
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14 views

Categorical data as continuous?

Can I combine three categorical variables into one variable and treat it as continuous? I have not tried this yet, I am using a survey where the data are treated as categorical but I have been advised ...
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17 views

Regression with ordinal response and a mixture of ordinal and nominal explanatory variables [duplicate]

In my problem, I have an ordinal response variable and the covariates are a mixture of ordinal and nominal categorical variables. I tried using cumulative logit model with proportional odds but I am ...
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3answers
52 views

Correlation of two categorical variables

I have a list of N people, with two equivalent test performed (A and B), which can have as outcome 0 or 1 (cancer positive or negative). Test A is the accepted gold standard. Is there any way to find ...
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12 views

Computing bias due to measurement error:

I'm currently doing an exercise and faced with the following question: We have the true form: $y_i=\beta_0 +\beta_1 d_i +u_i $ Where $d_i$ is a dummy variable. We have measured $d_i$ with ...
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1answer
40 views

How to prevent overfitting when encoding categorical variables

Currently, I am working on a binary classification project that include both numeric and categorical variables as predictors. I recently read an article about encoding variable with weight of evidence ...
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19 views

Factoring & Categorical Variables - What's needed?

I'm working on my final project for my machine learning class and am struggling to understand just how much factoring is needed. I will eventually be running a neural network on the data in R to ...
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15 views

How to code dummy variables for structural breaks in VAR

This question is really 2-in-1: 1) How do I code dummy variables for the following series that has 2 structural breaks in trend; an initial upward trend, then a much flatter upward trend, then ...
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18 views

Visualization of categorical data with too many categories

When dealing with data visualization, is it possible to produce a good graph from a table that has categorical data with too many levels and none of the levels have a reasonable amount of entries ...
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1answer
43 views

How do I test for independence with non-exclusive categorical variables?

Introduction I have a categorical contingency table with many rows and a binary outcome, which I count: ...
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1answer
123 views

Codification of Matrix $X$ in $Y=XB+\epsilon$

The variables for the data below is age, group (treatment 1,2,3), Y response variable. ...
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19 views

Dummy-coded moderator (multi-level): Reversing code changes interaction results

I have a diary-study (multi-level data) and hypothesized an interaction effect on level 1 (day-level). The moderator is a dummy-coded variable that was measured at day-level (*eat vs. not eat), the IV ...
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1answer
22 views

Can we use SEM for doing ANOVA?

I am studying the influence of gender on the attribution of motives in romantic relationships. IV= Gender; DV= Love Motive. The analysis can be done using a one-way ANOVA. I was wondering if the same ...
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Can residual deviance and AIC both decrease at the same time when the no of classes are reduced?

I have data on 148 websites' Global Ranks , Total Visits and Average Page views per visit. My objective is to model the Global Ranks on the basis of Total Visits and Average Page views. I have ...
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How to get data for an interaction dummy variable [duplicate]

How do i go about regression model with interaction dummy variable between exchange rate policies and the nominal exchange rate
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2answers
38 views

Regression with variable containing multiple entries per observation - clustering right approach?

Setting and Data I would like to run a 2-stage Hurdle regression with various variables describing the funding activity of companies (number of rounds, amount, etc). Some information on the data set: ...
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28 views

Factor loading of predictor on outcome variable

I know the basic and some more advanced statistics. I want to use multiple lineair regression to see whether the standardized questionnaire PsyCap, leader adaptivity and employability culture can ...
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1answer
111 views

How to visualize data averaged over ranks?

I have data from twelve experiments, with seven days and five animals on each. Based on the seven day mean of each animal's data, it is a assigned a rank from 1 to 5. I would like to combine the data ...
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23 views

Different dummy variable types in regression

I am running ols regressions with firms from different countries and different industries. I want to control for both country and industry membership of each firm. Say I have 1,...,N countries and ...
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7 views

How to infer a relationship between a categorical variable with 2 categories, and a discrete, interval level quantitative variable?

I am looking to use SPSS statistics / graphs to infer a relationship between a categorical variable with two categories, and a quantitative variable (income) with defined parameters (meaning it is not ...
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20 views

How to use categorical data in a regression model in R [duplicate]

I am trying to create a regression model using both categorical and numerical data using R (the effect of variable on a numerical score) When I run the analysis the categorical data is confusing as it ...
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1answer
28 views

Using browser version types/numbers in Analysis in R

I am doing some analysis using survey data. The target variable is a customer satisfaction metric. It would be helpful to find what versions of what browsers, are causing low customer satisfaction so ...
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16 views

Structural Change Cross Sectional Data

I am studying an introductory course of econometrics so sorry if this seems really obvious but, I am estimating a semi log wage equation of male workers where the covariates are Age, Experience and ...
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19 views

Classification and regression tree at once

I would like to understand if there is a machine learning algorithm that is able to handle both, polytomous (categorical) and continuous independent variables at once, to predict a continuous ...
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18 views

What analysis to use? IV: multiple interdependent levels, DV: continuous variable

My dependent variable is a continuous variable, ranging from 0 to infinity. However, my independent variable has multiple interdependent levels. To illustrate, A person has 6 attributes: A1, A2,... ...
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17 views

Understanding Tukey post-hoc Tests for factor variables in GLMs

I performed a GLM, which contained one factor variable (Site), one continuous variable (Days_til_clutch_comp), and an interaction of two factor variables (Host * Egg_type). The levels of Site are: ACT ...