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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18 views

How to visualize compatibility between different versions of different software?

I have five different software products (let's call them A, B, C, D, and E), each with several different versions. Each version of one product is compatible with at least one (and usually several) ...
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1answer
13 views

Interpretation regression coefficients predictors and dummy variables

I have to run a regression predicting the DV (continuous) from an equation with: Y = X1(dichotomous factor, coded 0-1)+X2(dichotomous factor, coded 0-1)+X1X2+M1+M2+M3+...+Mn, where M1...Mn - ...
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5 views

Regression Model for Matched Continency Tables Coefficient Interpretation

Sorry to insist. A number of questions in the same direction (coefficient interpretation) by different contributors, never answered. ...
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7 views

Iterative Differential Expression Analysis for Multiple Categories

I have a dataset which consists of one categorical variable and many numerical variables. This is how my data is formatted: ...
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0answers
12 views

Inference in bivariate continuous distributions

We have two nodes in different positions, which are represented by two random variables X,Y, with two prior bivariate continuous distributions, p_X , p_Y. f(X,Y,U,V) is a constraint on both ...
2
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1answer
19 views

Regression Model for Binary Matched or Paired Contingency Table Results

This is a follow-up question on a prior thread about the same setup as follows: We have two "Methods" ("A" and "B") to diagnose a medical condition. We are not trying to determine which one is better ...
6
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1answer
87 views

Interpretation of Cramér's V

I am trying to understand the value Cramer's V provides. I found the following sentence (from here): "V may be viewed as the association between two variables as a percentage of their maximum ...
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0answers
2 views

Hilog-linear analysis for Categorical data

I found myself in a statistical predicament, and received a few suggestions from friends that didn't convince me a lot. I'm looking for advice on this predicament. I'd really appreciate it in advance. ...
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1answer
20 views

Regression and contrast codings with multiple categorical variables

In regression with multiple explanatory categorical variables, how should I model the problem to compare the effects of the categorical variables with each other? Most contrast coding schemes (e.g. ...
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0answers
14 views

Inter-rater aggrement measuring among multiple participants in classed data

I have 100 items where for each item, multiple facts are given. I want to find the related facts for each item from the given multiple facts using human subjects. So basically I want to categorize ...
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1answer
63 views

How to transform categorical variable into numerical variable when using SVM or Neural Network

To use SVM or Neural Network it needs to transform categorical variables into numeric variables, the normal method in this case is to use 0-1 binary values with the k-th categorical value transformed ...
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0answers
9 views

Heckman Probit Model the number of explanatory variable in selection model?

I run a Heckman Probit model which is sometimes called as Heckit. It consists two parts like this: |1| Y X1 X2 X3, |2| select(Y2 X1 X2 X3) Y covers Y2 but not vice versa. The question is whether i ...
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37 views

Dimension reduction for discrete qualitative and aggregated variables

I know about PCA for multiple dimensions of continuous features but here is a problem I have some trouble to find a method for. I don't have a list of individual countries but rather a discrete ...
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1answer
25 views

Multicollinearity and categorical predictor with three levels

If I have a continuous DV and two IV, where one is categorical with three levels and the other is continuous, what assumptions do I need to check for multiple regression? Scatter plots are for ...
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0answers
38 views

Quadratic categorical variable

My model includes a categorical independent variable. The graphical analysis suggests that the relation between this variable and the dependent one could be quadratic. As regards including a squared ...
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0answers
4 views

Merging data with text identifiers [migrated]

I am trying to merge a bunch of datasets at the company level. The problem is my datasets only identify company name with a text string (i.e. "Ham and Cheese LLP") and further sometimes misspell or ...
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1answer
16 views

Continuous vs. categorical variables in interaction terms

My analysis includes, among others, three independent variables: X (interest rate), Y (type of rate; it is a dummy), and Z (likelihood of bankruptcy). I have transformed the latter into a categorical ...
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1answer
39 views

Correlation between diagnosis codes

How do I run a correlation analysis on medical diagnosis (Dx) codes between two years at patient level. Data runs into 45000+ observations for each patient with different diseases across years and I ...
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0answers
12 views

Solve intercept coefficient Dummy Variable regression

Suppose we have the model $y=\beta_0+\beta_1 x_2+\beta_2x_3+e_i$ where $x_1, x_2, x_3$ are binary variables, taking on values 0 and 1, so for example, if $x_1=1, x_2=x_3=0$. Now we want to regress ...
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36 views

Multiple regression with categorical moderator (age) and continuous IV's and DV

I am doing a multiple regression with 6 IV's, 1 DV, and 1 moderator. I am having a problem trying to understand how to get the effect of the moderator which is age group (i.e. 18-25, 26-35, etc.). ...
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3answers
203 views

Confused on the interpretation of regression coefficients

Let's suppose we have the following regression model: $$Y_i=\beta_0+\beta_1D_i+\beta_2D_iX_i+\epsilon_i$$ where $Y_i$ represents the test score of the i-th student, $D_i$ is a dummy variable that ...
2
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1answer
44 views

Comparing Proportion of Positive Tests

A condition or disease (D) is measured using two different methods (A and B) in a sample of 1,000 individuals from a population. Using method A, the percentage of positive cases is 25%, whereas method ...
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1answer
49 views

Plotting k-means clustering with mixed numerical/categorical data

I have a dataset in CSV format that looks as follows: ...
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0answers
25 views

Fitting linear regression using function of categorical variable in R

I want to fit a linear model for goal differences of ice hockey matches with regressor - difference in forms of teams. So my model has form: $y_{ijt} = \mu + \alpha_i - \alpha_j + \varepsilon_{ijt}, ...
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1answer
81 views

lme summary() interpretation

Need some help interpreting the summary() -function results. I am running a lme from the package nlme in R. I have a simple ...
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23 views

Linear regression with ordinal scaled variables

A friend of mine is working on a problem set and asked me an interesting question: if we have 2 variables, which are ordinal scaled how to compute a linear regression with those? $$x \in ...
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17 views

How to remedy seasonality in a multiple regression model

I am trying to build an economic model using multiple regression, and I am not sure how to remedy seasonal effects. I am collecting data across several different variables, and building three models ...
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1answer
14 views

paired samples (t-test?) with grouping variable

Im trying to determine the correct analysis for paired data with a grouping variable. I have 3 fish in each of 4 treatments, so 12 fish in total. Treatments are that the fish are fed at one of four ...
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0answers
22 views

Test for significant difference in smoking rate across age groups

I need to compute if there are significant differences in smoking rate across 4 age groups. I can assume a simple random sample from ages 15-55yrs, (made-up details below). I am wondering what type ...
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0answers
41 views

How to fix dummy variables when I calculate predicted probability on logistic regression?

My question is about predicted probabilities in logistic regression. Let me make an example, analyze the relationship marriage (1: married, 0: single) as dependent variable and sex (1: male, 0: ...
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37 views

K fold cross validation with many levels factors. Why cv.glmnet can do it and cv.glm cannot?

I notice that you can have many problems with cross validation if you have a categorical predictor which has many unbalanced levels. It happens often that the levels present in the training set are ...
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11 views

How coefficient of co-relation is calculated for dummy variables?

I'm finding the co-relation between the revenue a movie makes and whether it's a sequel(here sequel is the dummy variable with 1=if sequel, 0=if not sequel). Using the formula: I'm calulating the ...
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1answer
100 views

Dummy variables to control for clustering

I have a panel-data sample which is not too large (1,973 observations). The unit of analysis is x (credit cards), which is grouped by y (say, individuals owning different credit cards). I cannot used ...
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19 views

handling categorical data with a large amount of categories

I have data containing few categorical columns with a huge amount of categories at each (more than 1000 different categories at each column). I have to build a predictive model on this data, using the ...
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0answers
10 views

Testing relationship between a binary variable and an ordinal variable

I want to work out if there is a relationship between having certain characteristics (each coded as 0 if not and 1 if present) and support for a particular policy (measured using a Likert scale which ...
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0answers
15 views

Is ANOVA just a panel data model with dummy variables for group?

This might be a silly question, but I'm confused why ANOVA is different from a panel data model, with dummy variables for group, and inference on the coefficients on the dummy variables. Is this what ...
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0answers
52 views

Is selection/sample bias immediately caused when I don't exclude data?

I'm running a multinomial logistic regression on 8 independent variables for 180 observations in Stata (version 11). The dependent variable is categorical with 7 outcome categories, categories 1-6 ...
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0answers
23 views

How to handle mutually exclusive categorical variables

My data has about 40 million rows with 20 variables, all categorical. I am performing logistic regression. There are two rows that are mutually exclusive. Should I train two separate models, or is it ...
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2answers
58 views

Predicting an output based on whether a variable is above or below a threshold

I want to create a linear regression model to predict an output that uses two different coefficients based on some threshold within the data. For example: df: ...
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0answers
9 views

Creating Dummy Sets in MATLAB for statistics [migrated]

i am looking at creating dummy sets in MATLAB, first i created an array of random variable with 10 instances of min=5 and max =10, and here is my code ...
0
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1answer
24 views

T-test on percentage values (among experimental replicate values)

My experiment involves looking at the precentage of cells in a slide that have a particular property under condition A and condition B. I have one slide for each condition. I have done this experiment ...
0
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1answer
32 views

Antilog of a semilog regression model with dummy variables

I have a semi-log regression model, with two continuous predictors, two categorical predictors (0 or 1 dummy variables) and a non-zero intercept. The response variable is log10 transformed, none of ...
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0answers
31 views

Is it posible to use factor (categorical) variables in glmnet for logistic regression in R?

I'm building a logistic regression in R using LASSO method with the functions cv.glmnet for selecting the lambda and ...
3
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1answer
31 views

Likeness of brands using tweets - is Chi-square appropriate?

I'm trying to determine if brand x is more similar to brand y or brand z using tweets. I have a data set for the words that occurred in each brand's tweets, and I'm considering using the chi-square ...
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1answer
42 views

Exploring correlation between quantitative and non-binary categorical variables

I'm asked to explore the correlation between a quantitative variable (Interest rate) and categorical variabels (Such as State of Residence, Employment length (<1 years, 1-2 years, ..., >=10years), ...
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1answer
23 views

Interpreting Coefficients of a Dummy variables derived from an Ordinal variable

I have a variable that is measure societal complexity (SC) on a 3 point scale. 1 being the least complex and 3 being the most complex, and I think that this can safely be classed as a ordinal ...
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2answers
68 views

Is the chi-squared test appropriate with many small counts in a 5x2 table?

I have two sample populations, A, and B, which are independent. ...
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3answers
85 views

Ask for suggestions on clustering methods on a large dataset with mixed types of variables

I need to build segmentation on a large customer dataset with more than 300K records and many variables, including continuous like income and age, ordinal like education level and membership level, ...
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0answers
3 views

How do I make sure numbers are numeric from a .txt? [migrated]

I'm setting up a script to extract the thickness and voltages from a single column text file and perform a Weibull distribution on it. When I try to use fitdistr() I get an error stating "'x' must be ...
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1answer
49 views

How does caret handle factors?

I have been testing conditional trees and random forests with caret, and I've noticed it does something weird with factors. So, for example, a ctree using the base dataset ...