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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Regression with some observations having more than one factor level

I have data I want to analyze using multiple regression or machine learning: the response is cells for which I measured viability (a continuous response) and the independent variables are the genes in ...
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56 views

Reducing variable candidates for multivariate regression step by step

I have a set of possible candidates that I want to use in a multivariate regression. I am trying to reduce this set by the following procedure (using Stata): Step 1: univariate regression (if ...
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12 views

What statistical test should be used to compare two independent sample over time (pre- and post-test) for categorical variables?

I have baseline and follow-up surveys, asking the same 33 questions. A typical question is: How well do you think your family knows what you are good at? Very Well Well ...
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12 views

how to deal with panel data with categorical variable in regression

I have got a panel data regarding to electric consumption(including total consumption,AC consumption and light consumption) among different buildings.There were categorical variables I have already ...
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8 views

2X2 Factorial Design with Likert-type Responses

I have a 2x2 design completely between subjects. Both independent variables are dichotomous. The dependent variable is a 7 point Likert-type item. But I'm not sure how to analyze it. I know ANOVA, ...
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1answer
21 views

Correlation dummy variable and continous/discrete variable

I am looking at the relationship between a dummy variable specifying an economic cycle (i.e. either zero or 1 for expansion or recession) with a categorical variable, in this case risk premium over a ...
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11 views

How to estimate dependency or in-dependency between variables [on hold]

Is it possible to estimate "the rate/degree (or something similar)" if there is dependency between 4 different types of variables that are categorical. If the 5th variable is a outcome variable(the ...
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0answers
24 views

Correlation of 2 categorical variables in linear model

I have this dataframe with two categorical variables (Sex and Ethnicity (only Asian or European)) and I need to fit a linear model to estimate the weight of a fetus given the day of the echography and ...
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35 views

Hierarchical clustering with categorical variables

Can categorical variables be used in hierarchical clustering? I have heard only continuous variables are used, but have seen people discussing categorical variables may / may not be used as well. ...
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5answers
212 views

Clustering of variables: but they are mixed type, some are numeric, some are categorical

I have a dataset with 15 variables. Some variables are numeric, continuous. Other variables are boolean, dichotomous (true/false). There's also one variable categorical, nominal. ...
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42 views

Correlation between event occurrence and data

I'm trying to figure out what's causing my stomach pain recently and I have logged the following data twice a day: A grade on a scale from 1 to 10 on how much my stomach hurts Foods (unique names) I'...
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1answer
24 views

Multinomial Model of Discrete Choice

Can anyone explain me the differences between Multinomial Logit Model and Conditional Multinomial Logit Model? Multinomial Logit Model $$P(y_n=j|z_n=z)=\frac{exp(z'a_j)}{1+\sum exp(z'a)}$$ ...
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22 views

How to use categorical data without excessive number of input nodes (neural-network)

After playing around with neural networks, I'm having a bit of trouble with using categorical data. Using the rough guide: h = s/(alpha*(i + o)), where h = hidden nodes, s = no. of samples, alpha ...
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43 views

multilevel model with categorical outcome in R?

I am examining social interaction data in individuals within two groups. Each social encounter has been coded to one of 4 categories, and these encounters are nested within individual, whom are nested ...
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35 views

What is the dummy variable trap? [closed]

I am currently trying to run a fixed regression. The dependent variable is the online rating for a book and one of my control variables is a dummy which describes whether the book is an eBook or a ...
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0answers
5 views

Ordered categorical variable dummy coding

Basic question, does the following coding for ordered categorical variables make sense?1 ...
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2answers
22 views

Sample size of the levels of a categorical variables

Is there a generally acceptable sample size for the levels of a categorical variable included in a regression analysis? For example, if we have a variable color with 3 levels: 5 reds 140 blues 155 ...
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0answers
9 views

Variable Importance (Linear Models) for dummy encoded predictors

I've built a model using glmnet under the caret package. I have dummy encoded predictors (4 levels for 1 variable) and want to estimate the variable importance of each variable (using varImp) . Since ...
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0answers
17 views

Statistics, R: Build linear regression model with differently contrast-coded variables

I want to build a linear regression model where I predict a mean of a group of participants (how they rate something on average). Predictors should be age (continuous) origin (deviation coded, each ...
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10 views

analysing interaction between binary categorical factors which don't explain the whole variation

I have a large dataset with 2 binary variables relating to gender & ethnicity, and one output variable, also binary. The overall incidence of the output variable is roughly 70% true. Running ...
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4answers
274 views

With categorical data, can there be clusters without the variables being related?

When trying to explain cluster analyses, it is common for people to misunderstand the process as being related to whether the variables are correlated. One way to get people past that confusion is a ...
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51 views

Modeling the importance of data points in Logistic Regression

Given N data points where each entry of a point represents a value of a feature, and we need to use this data to model a binary Logistic regression model. e.g. lets say the data points represents ...
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1answer
20 views

what is the appropriate one-class classifier for sequenced categorical data?

Can someone suggest an algorithm for an outlier detection system? My requirements are: it supposed to be a one class classifier, where on training phase, it only fed 'normal' data however the normal ...
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2answers
21 views

Question on Interaction terms with a dummy variable

I have the following model. Sales = B0 + B1.Age + B2.Mobile where Mobile is a dummy variable that has the value of 1 if mobile, and 0 otherwise. Age is a ...
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1answer
30 views

Excluding a level in your categorical variable to fit your hypothesis

I have a categorical variable with 3 levels: Attention Deficit, Other Types of Deficit, No Deficit. My hypothesis is only interested in comparing Attention Deficit and Other Types Deficit using ...
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1answer
36 views

preprocessing and input format for gradient boosted trees

I'm using MlLib library de Spark and trying to perform Gradient-Boosted Trees algorithm on my data, that has mostly categorical features (and just two numerical features). in the example given in ...
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0answers
97 views

How to find the maximum number of independent pairwise comparisons between groups

I have the following situation: Consider a dataset that is comprised of a number of factor levels x = gl(5,1) > [1] 1 2 3 4 5 > Levels: 1 2 3 4 5 I want to ...
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4 views

Embedding categorical values

Is it possible to perform embedding of a dataset that contains only categorical values e.g. n f1 f2 f3 1 2 1 3 2 2 2 3 3 1 3 2 4 1 4 1 where n is an object and f1, f2, f3 are ...
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Can the variability of this multi-variate categorical data set be computed?

I have a set of Survey responses in the format shown below. I want to provide a mathematical measure of Variability to show "how different" the population is, but I'm not sure how to do so without ...
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0answers
13 views

Analysing a three way interaction

Im currently analyzing a three way interaction in R and my data looks like this: ...
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1answer
99 views
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1answer
23 views

Cluster Analysis for Website Data [duplicate]

I want to perform cluster analysis on the data of a website. The data is mainly visitor history(97000 rows) and has following variables: a)User Device Category b) Traffic Marketing Channel c) Traffic ...
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2answers
43 views

Linear Regression (R): Need to convert categorical variables to factor or character?

I'm running a linear regression in R. If i have an independent variable Gender with only values 0 (for Male) and 1 (for Male), do i need to convert them to factor ...
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0answers
18 views

How to check for goodness of fit for a SEM with lavaan using categorical data (Probit)

I am going to try to give as much information as possible. I have a data base describe(Df) So all binary variables except one with 1,2,3. Therefore I wanted to ...
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1answer
12 views

Multiple logistic regression: levels of categorical predictors that will never be combined – is that a problem?

I am investigating the predictors for adverse events (AEs) from a sample of 400 patients recieving an injection therapy. The outcome AEs is binary and I will use a multiple logistic regression model: ...
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1answer
12 views

Capturing variability using ANOVA on date

I have a dataset of traffic count at several intersections at various dates. Most of the intersections were counted only once. I want to know if there is a significant daily and monthly variability in ...
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1answer
24 views

Removing intercept from GLM for multiple factorial predictors only works for first factor in model

I am running a binomial logistic regression with a logit link function in R. My response is factorial [0/1] and I have two multilevel factorial predictors - let's call them a and b where a has 4 ...
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0answers
27 views

Clustering binary data [duplicate]

How can I cluster household data which has binary variables like owns_car, rented_house (which all had answers in yes/no and being converted to 0/1). My data has 86 dimensions and about 3 lakh rows. ...
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3answers
454 views

Is it valid to derive a mean from categorical data?

I am working on a study to quantify average working hours for doctors. However, when I leave it empty for respondents to fill up, it remains unfilled. Changing it into categories as above yield ...
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23 views

Variance explained - equivalent statistics for categorical data?

I have a multinomial response variable and a multinomial "independent" variable. Is there an equivalent statistics or method for calculating the variance explained by the independent variable?
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1answer
76 views

GLM Categorical Variable Level grouping / simplification

I am trying to find information regarding a technique which is commonly used in the insurance pricing industry. This relates to a GLM model where a categorical variable is used in the model. The ...
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0answers
12 views

picking a kernel SVM, how to normalize categorical + numerical data

So I have a dataset that contains both categorical and numerical data for each data point, and a class for each data point. My goal is to plan to build an SVM model from the data to predict the class ...
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24 views

Using contrasts in Poisson regression

The question is about using contrasts in regression analysis (here, Poisson regression with robust error variance). We have devided the participants in our sample into 6 groups, according to their ...
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0answers
68 views

Sample size for multinomial distribution

Suppose we have multinomial distribution with $k$ outcomes having the same probability $1/k$. What sample size do we need to guarantee with the probability $95\%$ that $m$ of the oucomes occur at ...
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0answers
14 views

Is it possible to scale categorical variable before calculating a distance matrix?

My ultimate goal is to find similar customers by comparing characteristics of non-customers to existing customers. The characteristics are mostly non-numeric. My hope was to scale(data) and then ...
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19 views

How to deal with interaction between several dummy variables and one continuous variables in one or two regression models?

I want to know the relationship between revenue and cost in several conditions. Dependent variables is REVENUE.REVENUE is a continuous variable from 0~1000+.I have several key independent variables: ...
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2answers
33 views

Relationship between categorical factors

I am not sure what this is called in English, but if we have two categorical factors, we can say that one of them (A) is finer than the other (B) if it holds true that if two observations belong to ...
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Significance across Categories of Quantitiative Data

I have a quantitative independent variable that has been grouped into categories (A-G). Example: Age of people by decades (20s, 30s, 40s, etc.) I want to determine if the difference between the ...
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41 views

errors in the orthogonal factor model

I am using R psych package in order to design a factor model. By default, an oblique rotation (oblimin) is performed by fa. The number of factors (fa.parallel$nfact) has been previously estimated. <...