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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6 views

Predicting continuous response with a mix of categorical and continuous variables

What regression method should I use to construct a model predicting a continuous response with a mix of categorical and continuous variables? I would do this with SPSS (16.0) and was thinking of using ...
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51 views

Quick Exploratory Analysis of Categorical Data

Does anyone know of a tool (preferably free) that does quick analysis of exploratory data mainly categorical with date. Using R and Python I can create time series and histograms, perform tests such ...
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1answer
102 views

“Dummy variable” versus “indicator variable” for nominal/categorical data

"Dummy variable" and "indicator variable" are labels frequently used terms to describe membership in a category with 0/1 coding; usually 0: Not a member of category, 1: Member of category. On ...
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1answer
18 views

Full effects from Poisson GLM

I am running a Poisson GLM with count data as response variable and both continuous and categorical variables as predictors. I made use of the following (dispersion is OK): ...
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1answer
16 views

identify nature of missingness for categorical variables

could you please give me some hints for identifying the nature of missingness for categorical variables' missing value? I mean, I gave a fast search on google scholar but I didn't find anything ...
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8 views

Canonical correlations for categorical (binary) variables

I have a data set with all categorical variables (most binary). Some variables code social factors, others code mental health issues, a third group code degrees of support from various sources ...
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7 views

In R, using glm to model call counts in treated/not treated forests [closed]

Ok, so I'm new to using R and trying to learn this on my own because my uni doesn't have a prof who uses R. I've tried googling for answers, and I feel like I'm sort of getting answers, but I'm still ...
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3answers
46 views

Testing and reporting interactions in multiple regression

I have a model with two between-participants predictors -- one continuous (a), and one categorical with two levels (b) -- and ...
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10 views

Linear mixed model construction validation

I have 6 groups of fish made up of 8 individuals. Each group is tested three times under different treatments. These group level treatments are hungry , ...
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0answers
10 views

dependent and independent categorical variable across eight trials

Study: significantly selected color for a particular letter. My sample size is 30 and the study is within subject. Independent variable -> letters (total 8)... Dependent variable -> colors ( total ...
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15 views

Medical Malpractice Datasets [closed]

I hope this is the right place to ask this question. I'm looking for medical malpractice and error datasets from hospitals. To be very precise, for a given hospital I'd like a total count of deaths ...
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21 views

Appropriate classification model for combination of continuous, binary and categorical inputs

I have a binary classification problem for classify my samples to two classes (class_1 and class_2). I have different kinds of ...
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0answers
16 views

creating an indexed dummy variable as a predictor in OLS

I am performing on OLS with two predictors and a response variable. The data is a time series of 450 days approximately. There is an irregular pattern in my response variable - it sometimes ...
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0answers
24 views

A measure of correspondence between ranked ordinal data

I would like to find an appropriate way to measure the similarity between two sets of data with the following characteristics: Both sets contain 10 categorical observations. The categories ...
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13 views

Treating categorical variables as continuous in CFA

On reading a number of prominent CFA studies on the structure of PTSD symptoms, I notice how every study appears to treat the variables as continuous. This puzzles me, as their data come from ...
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0answers
16 views

Loading data with missing values as numeric data [migrated]

I am trying to impute missing values using the mi package in r and ran into a problem. When I load the data into r, it recognizes the column with missing values as a factor variable. If I convert it ...
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2answers
26 views

Kernel methods on Categorical Data

I have a basic understanding of kernel methods and the kernel-trick and the advantages of it, why it is preferred over conventional machine learning algorithms etc. However, I have some trouble using ...
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0answers
49 views

How to transform continuous data with extreme bimodal distribution

Is there a way to transform a continuous predictor variable (grant) that has a bimodal distribution into a normal distribution (see density plot below)? I have tried log(x+c), z-score and inverse ...
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0answers
31 views

Comparing two population of non ordinal data (categorical data)

I have 2 dataset $D_1$ and $D_2$ whose elements can assume values between 0 and 1. The cardinality of $D_1$ and $D_2$ is the same. Think for example at the measurement of the temperature in a set of ...
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0answers
53 views

How to fit OLS with many categorical levels, on more than one category

This question is not meant to be a software question, but I will illustrate the issue using R a bit. My Understanding of the Simple Case If I have a simple linear model with a categorical variable ...
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0answers
19 views

Can I run a multidimensional scaling analysis with purely categorical data?

I have data where participants categorized facial expressions using one of seven emotion labels (Angry, Disgusted, Fearful, Happy, Neutral, Sad, and Surprised). Can I take the resulting confusion ...
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1answer
17 views

Log Linear Models: Interpretation when None Fit

This is question 9.6 from Categorical Data Analysis by Alan Agresti (Wiley, 2013). The question asks us to find a Log Linear with the best fit for a 2x2x2 contingency table. The following are the ...
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0answers
39 views

variable error on logistic regression/ proc catmod- Building predictive model

I am using logistic regression to fit a model with categorical/multinomial varaibles. data-description: There are over 300 variables as independent variables, sample size is 5000 which is divided into ...
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0answers
14 views

How to determine significance across categories of binary data?

I have subjects that fit into one of three, mutually exclusive groups, "favorable," "intermediate," and "unfavorable" based on their genetics. They can then be classified as either a "responder" or a ...
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1answer
81 views

Is there any correlation or causation here?

I have the following data, where 2 properties (P1 and P2) can be either True or False ...
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28 views

Sample size for logistic regression with categorical independent variables

Trying to find a sample size for logistic regression I found a rule of thumb in http://www.medcalc.org/manual/logistic_regression.php I cite: Sample size considerations. Sample size calculation for ...
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16 views

How can I evaluate binary response models that have weighted observations?

I'm working with a binary response data set, but the importance of each observation varies over a factor of 100. Models to fit the data can accept a weight for each observation. But when it comes time ...
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0answers
17 views

the approach of performing correlation analysis between categorical and numerical

What are the approaches to perform correlation analysis for the following pairs: ...
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1answer
12 views

How valid is it to run one-way ANOVA on other means?

For background, I have a set of data where I asked two sets of 50 people to repeat a task 12 times, which generates a single number. Each 1x12 vector represents a single vector of data. I then group ...
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16 views

How can I group different levels of classes of a categorical variable in logistic regression?

Suppose I have a categorical variable neighborhood, which can take the classes Neighborhood1, Neighborhood2, Neighborhood3. I would like to know which neighborhoods can be grouped and what ...
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3answers
36 views

What to do when some categories have too few observations

I have an ordinal, categorical variable with five levels, of which the last two have only one observation for each. Should I leave them alone, omit them, incorporate them in another category, or do ...
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1answer
50 views

Multiple Regression with Categorical Predictor Variables of More than Two Levels

I'm planning on running a hierarchical multiple regression. In the first step, I would like to enter demographic characteristics, second step continuous predictor variables of interest, and third step ...
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0answers
18 views

Autoregressive distributed lag (ADL) models and Dummy variables

Is it okay to use an Autoregressive Distributed Lag (ADL) model with a dummy variable as the dependent variable? Or should I use a combination of logit/probit with an ADL model? I realize it might ...
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0answers
9 views

Testing for differences within a categorical variable: question about contrasts

I have a three-group categorical variable coded as: 0, 1, and 2. I ran an OLS regression with the above variable as an independent variable. I found that groups 1 and 2 are each significantly ...
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45 views

Significance testing of categorical variables - is chi squared as good as it gets?

I am testing categorical variables for significant relationships, 5 age groups and 3 answer options (yes/no/don't know). Is there a test which will specifically tell me if e.g. age group 1 is ...
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35 views

How to create dummy variables for interaction term between categorical variables?

I'm building a logistic regression model estimating the probability of hospitalization based on several predictor variables, including indicator variables for various diagnosis categories (coded as ...
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2answers
107 views

Linear regression including categorical variables with hundreds of levels

I am trying to teach myself data science by solving some of the problems available on the internet. Currently I am trying to predict a fraud event with the aid of 4 categorical variables. Each of the ...
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1answer
36 views

Too many significant dummy variables in fixed-effect panel model

I am doing panel analysis of state drug policies. My data set includes 50 states and ten time points. I am using one-way state fixed-effect models, controlling for heteroskedasticity and ...
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0answers
12 views

Dealing with categorical variables in regression [duplicate]

I have this categorical variable that represents the country for a person. How can I use this in regression model. If there had been less levels for a category I could have used dummy binary variables ...
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19 views

zinb estimates change when using factor variables

I use Stata SE 13 and I have a problem with the command zinb in Stata. I have binary variable female which is 1 if respondent is female, 0 otherwise (no other ...
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1answer
33 views

Interaction Dummy

I have a model: $$ \ln({\rm earnings}) = 2.618656-0.0899657{\rm female}+0.382019{\rm white}-0.2754126{\rm female}\times{\rm white} $$ ${\rm female}$ and ${\rm white}$ are dummy variables. t= ...
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1answer
42 views

Coding of categorical random effects in R: int vs factor

I have a problem with coding of a 2-level categorical predictor variable in R, and subsequently using it as a random slope in lmer(). I can keep the factor as numeric, coded using the treatment ...
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0answers
29 views

Dummy variable interpretation [duplicate]

I have a model: $$ \ln({\rm earnings}) = a+b_1{\rm female}+b_2{\rm white}+b_3{\rm female}\times{\rm white} $$ ${\rm female}$ and ${\rm white}$ are dummy variables. t= female=-1.65 white=8.86 ...
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1answer
70 views

Dummy variable interaction regression [duplicate]

I have a model: $$ \ln({\rm earnings}) = a+b_1{\rm female}+b_2{\rm white}+b_3{\rm female}\times{\rm white} $$ ${\rm female}$ and ${\rm white}$ are dummy variables. I have interpreted $b_1$ and $b_2$: ...
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1answer
86 views

Interpretation of interaction term

I have a model: $$ \ln({\rm earnings}) = a+b_1{\rm female}+b_2{\rm white}+b_3{\rm female}\times{\rm white} $$ ${\rm female}$ and ${\rm white}$ are dummy variables. I have interpreted $b_1$ and $b_2$: ...
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1answer
29 views

Factor analysis with categorical reponses and missing data

I factor analyzing a measure with 55 categorical items (3 categories each). I am use CFA to test a 7 factor model. I have a very large sample (>10,000), but approximately 20% of the sample is missing ...
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17 views

Categorical Variables - Factor Reduction - Can I use the dependent variable?

I am working on a basic fraud detection model. I have about 10 independent features and I am trying to predict if a given transaction is genuine or fraud. Most of the features are categorical and each ...
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3answers
121 views

Why are mixed data a problem for euclidean-based clustering algorithms?

Most classical clustering and dimensionality reduction algorithms (hierarchical clustering, principal component analysis, k-means, self-organizing maps...) are designed specifically for numeric data, ...
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2answers
43 views

Interaction between a dummy variable and a variable with a quadratic form

I am finishing up an econometrics assignment and this problem has me stuck. I have estimated a regression equation for ln hourly wages on a gender dummy variable, several race dummy variables, a ...
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1answer
33 views

Convert categorical percentage data into an overall mean

I have survey data in which the answer choices were "categorical" (0, <15%, 15-30%, 30-45%, 45-60%, 60-75%, 75-90%, >90%). In retrospect, this should have been a free response question, but I'm ...