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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Analysis to assign a categorical var to a ordinal

I have a categorical outcome with > 2 levels and a categorical predictor with many levels. Which model can I use to assign to each predictor level the probability of being in one of the classes of ...
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14 views

ordinal classification using C5.0

My question is about machine learning to predict ordinal variables. Most ML models for classification that I have seen do not make any assumption about the order of different categories. I can see ...
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1answer
21 views

Correlation between a numeric and factor in R [duplicate]

I'm new to R and I'm trying to find the correlation between a numeric variable and a factor one. I have a data frame with the following 3 columns: 1. nr of clicks (range 0:14) 2. response (1= "YES", ...
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17 views

Scaling data constrained to be varying between a floor and ceiling set of values

I have data that range continuously between the values of 0 and 2, usually somewhere in between close to 1 on average. 0 is a "floor" and 2 is a "ceiling." The data describe more than one group of ...
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1answer
23 views

Rearrange regression equation that includes a dummy variable

This is my regression equation: $10 = 5.44 + 0.26X_1 - 3.19X_2$ $X_2$ is a dummy predictor with two levels. Assume that the value of $X_2$ is 1 therefore regression equation is: $10 = 5.44 + ...
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30 views

Can a factor be used as Y variable? Best test?

I have many plant populations of the same species sampled (around 100). What is measured is an allele on one gene, that can be A,B or C. This is what I would like to use as Y variable. Then I have the ...
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31 views

Ordinal or nominal

I designed a questionnaire regarding teacher readiness to conduct / perform certain tasks other than teaching in the classroom. One of the items included is the period of service of the teacher. Here ...
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7 views

Accuracy of rpart for categorical

Below is an example of fitting categorical data using rpart. But how to compare the predictions from rpart with the actual data? Also, is it possible to draw a ROC curve for the testing and training ...
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23 views

Post-hoc Chi Square Test for Pairwise Comparison of 3 Groups

I am trying to do something that in my mind is probably simple and I'm probably just blanking on it. I am using Stata to compare 3 groups on a categorical variable. So, as an example, I would be ...
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52 views

proving regression with dummy variables gives same estimates as separate models

Let ($x_{i1}$, $x_{i2}$, ..., $x_{id}$, $y_i$), $i = 1,..., n$ be an i.i.d. multivariate sample and furthermore assume each observation belongs to one of possible $K$ categories. Assume for each ...
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22 views

Which kind of analysis could be made to associate a set of genes to clinical values?

I have a set of 5 genes that can be mutated or not, so therefore are intended as dichotomous yes/no vars. I want to identify the effect of the mutation of this genes on a continuous response var. The ...
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1answer
25 views

SPSS logistic regression. categorical --> dummies

All our variables (question asked to students in our questionnaire) given by school are answered by: 1) very important 2) important 3) unimportant 4) vert unimportant we want to use these variables ...
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54 views

Generate random correlated categorical variables

Lets say I want to generate 100 observations of 2 likert scaled, normally? distributed variables with 10 categories (1-10) and a pearson correlation of f.e. ~0.8. I am aware that using pearson ...
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57 views

Chisquared on categorical data or a Wilcoxon test on the counts hereof?

This question is related to a question I had in R on SO here The background of my question is fairly simple. I was given two "databases" in the form of data.frames ...
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1answer
19 views

Calculating CI and SD for individual regression lines from a multiple factor glm

We have 2 correlated variables and a lot of binomial factors (around 200), here illustrated with just $f1$ and $f2$: ...
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1answer
18 views

Computation of Yes/No question and 7 point Likert scale into new variable

I could not find an answer to this specific question on the forum so ill make a new post. Thanks a lot for helping! I have 5 Yes/No question, and 5 7-point likert scale items (that each corresponds ...
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1answer
58 views

How to regress two categorical variables

I'm not looking for a detailed answer, just some pointers towards possible things I could read to better understand this problem. Let's say that we have a survey that asks two questions, $X$ and $Y$. ...
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1answer
48 views

Using year fixed effects on data with yearly observations

I have a panel data set with yearly observations of various firms over a period of 5 years. I am running a fixed effects model in Stata using xtreg. Is it ...
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11 views

Dummy and Heckman [migrated]

I'm using Heckman Selection Model which are two consist of 2 equation. i'm using Probit as a selection equation and multiple regression as a result equation. how can put in dummy variables in those ...
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1answer
13 views

Mean comparison of two categorical variables

I'd like to compare people's perception of safety at a certain location [which is a categorical variable on a scale of 1-10, with 1=feel very unsafe & 10=feel very safe] before and after being ...
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7 views

Testing for a 3-way interaction between a within-subjects factor, a continuous IV and a categorical IV in SPSS

I'd like to test whether the moderating effect of a (continuous) personality variable on the effect of an experimental manipulation differs between conditions. Does anyone know how to go about this in ...
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10 views

To demean or to use dummies in maximum likelihood

I have a dynamic panel data with T=20 and N=1500 and I use a maximum likelihood estimation (more precisely its a VAR). Using a dummy variable approach to account for fixed effects introuduces an ...
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3answers
261 views

How would you categorize / extract information out of job descriptions?

I have a bunch of job descriptions entered by users. There are all sort of misspells and bad data. i.e: ...
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16 views

using a dummy to indicate zero values of a overdispersed continuous predictor variable [duplicate]

I have a predictor variable that has many zeros. The predictor variable is simply a count of the occurrences of some behavior. The zeros are qualitatively meaningful. I'd like to use a log ...
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1answer
41 views

Defining NULL group for dummy variables

I am quite new in R and am on a stage of running a regression model there. The approach we have chosen is linear regression with dummy variables. As far as my knowledge and experience go when using ...
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14 views

Interpretation of smaller-than-one odds-ratios in logistic regression with multi-category categorical independent variables

I've run a binary logistic regression analysis, and I’m unsure how to interpret some of the odds-ratios. I tested the predictive capacity of three independent categorical variables on a binary ...
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157 views

Maximum likelihood estimator of joint distribution given only marginal counts

Let $p_{x,y}$ be a joint distribution of two categorical variables $X,Y$, with $x,y\in\{1,\ldots,K\}$. Say $n$ samples were drawn from this distribution, but we are only given the marginal counts, ...
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35 views

Residuals perfectly symmetric about zero against fitted values

Consider a modelling a response $Y$ against two categorical variables (which can take $4\times 2=8$ possible combinations). We have 16 values for the response, with two values for every combination of ...
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11 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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1answer
68 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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113 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
24 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
18 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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15 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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3answers
60 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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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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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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27 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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19 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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25 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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14 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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2answers
27 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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1answer
89 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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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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59 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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27 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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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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57 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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17 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
90 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 ...