Tagged Questions

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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16 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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0answers
20 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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0answers
12 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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2answers
64 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
31 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
29 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 ...
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0answers
17 views

What is the average error for the model? [on hold]

Anybody knows what is the average error for the model? I don't understand what the term "average error" means at all. Does that mean the residual standard error on n degrees of freedom?
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1answer
25 views

How to correlate categorical personality and music genre preference scores?

I'm currently a third year Biology student and I've annoyingly screwed myself over by not following the golden rule of stats, always know how to analyze your data prior to conducting the experiment. ...
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0answers
27 views

Scoring function for categorical data

I would appreciate guidance on the following problem. There are three sets of urns, Set 1, 2, and 3. Each set contains the same number of urns, Urn 1, 2, 3. Each urn contains some number of Red ...
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0answers
28 views

Split Factor Levels Or Not In Variable Selection

This question is related to previous ones but I believe distinct. I am primarily interested in prediction and I have access to LASSO variable selection (but without factor level grouping) using the ...
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0answers
8 views

Team level analysis: how to aggregate control variables such as tenure, gender and working status?

I'm currently conducting research on a team level analysis (59 teams) in which i estimate the effect of voice climate -> team voice behavior, team voice behavior -> team learning behavior, and, team ...
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0answers
31 views

glmnet: How to make sense of multinomial parameterization?

Following problem: I want to predict a categorical response variable with one (or more) categorical variables using glmnet(). However, I cannot make sense of the output glmnet gives me. Ok, first ...
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0answers
31 views

Multivariate regression with categorical response variables

Explanation of Data: I started with a data set where each user belong a specific group and their contribution to different domains. After multiple pivots and pre-processing attempts, I got my data in ...
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2answers
90 views

Treating predictors as numerical or categorical variable in regression

I have a set of data that I am using regression analyses on. All of the columns are numeric (as far as I can see) a mix of integers and reals. However, two of the columns are being read from the CSV ...
2
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2answers
157 views

When can a continuous variable be treated as categorical?

I have a continuous variable, which can take any value between 0 and some large, though not infinite, number. Let us assume that the maximum possible value is 1000. The values are nowhere near ...
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0answers
29 views

Predictive model with combinations of dummy variables of different length

I would like to try to predict the amount of a public contract based on historic records where the main variables that I can fit against include: contact duration (continuous) number of buyers ...
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0answers
38 views

Finding an interested value in a categorized variable [migrated]

Could please someone answer me how to solve the following problem. A very small part of my dataset is: ...
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2answers
40 views

Handle missing values in factor variable

I have a huge dataset for a binary classification problem (about 1.5 million rows), and the feature space is quite large (145 dimension). Some of these features are factors (YES, NO), but there is ...
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1answer
35 views

Multilevel: Can I include two dummy variables of a 7-dummy-set into a random slope?

I am calculating a two-level linear multilevel analysis. A look at the random intercept random slope model showed me a significant decrease in my model deviance if I include two dummy variables. Those ...
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0answers
20 views

Do I need to transform object scores of principal components obtained from CATPCA before regressing?

As part of my internship I have obtained a dataset containing 11 categorical explanatory variables and a number of categorical response variables. Using CATPCA i have reduced my explanatory variables ...
2
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1answer
45 views

Interpretation of betas when there are multiple categorical variables

I understand the concept that $\hat\beta_0$ is the mean for when the categorical variable is equal to 0 (or is the reference group), giving the end interpretation that the regression coefficient is ...
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2answers
29 views

Comparing prepostest different observational categories

Two groups of individuals are subjected to two different treatments. We have video recordings of them pre and post treatment. Observational categories are registered every minute for a series of ...
0
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1answer
26 views

Ways to test bar charts with few bars to see if they come from the same distribution?

I have survey data with ordinal/categorical data. Most of the time the answers to question are Yes/No. I want to compare the bar charts (normalized) of yes/no from participants who gave a particular ...
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1answer
30 views

build model with complicated types of feature variables

I have been asked to build a model to predict a life span of a material based on a couple of features. The features can be classed into the following categories: 1) The feature variables just have 0 ...
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1answer
35 views

Spearman's rho for nominal / metrical data

Can Spearman's rho be used to calculate correlations between nominal (i.e., locations such as 1 = City1, 2 = City2, 3 = City3) and metrical data (i.e., revenue generated in US dollars)? I also heard ...
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2answers
116 views

Simplifying variable effects in a GLM in R

Apologies, but it looks like my question is off topic for this forum. Thanks for all the excellent replies though. For those who have come across this question if they've been looking for something ...
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2answers
55 views

Forcing nlme to give the results for the levels of a treatment as “absolute” values instead of contrasts

I am using a nonlinear model to fit an equation to data using nlme in R. Several values (one by treatment) are estimated for a fixed effect. As usual, by default ...
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0answers
15 views

Summary of Probabilities

I am trying to summarize the ages of a population of five people. I have the following observations with an "Average" calculated at the end: ...
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1answer
56 views

Best way to represent x attributes in y categories in same chart over time series

Is it possible to represent x attributes in y categories over a time series in same chart without losing ability to cross verify between attributes within same category and same attribute between ...
0
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1answer
30 views

OLS with categorical variables [duplicate]

1) When we omit the intercept, aren't we forcing the regression line through the origin? Does that pose any problem because we assume that there is no variable that affects the outcome other than the ...
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0answers
43 views

How to perform a regression on principal components obtained from CATPCA in SPSS

As part of my internship I have obtained a dataset containing 11 categorical explanatory variables and a number of categorical response variables. Using CATPCA i have reduced my explanatory variables ...
4
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2answers
96 views

How to perform residual analysis for binary/dichotomous independent predictors in linear regression?

I am performing the multiple linear regression below in R to predict returns on fund managed. reg <- lm(formula=RET~GRI+SAT+MBA+AGE+TEN, data=rawdata) Here ...
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2answers
47 views

Hypothesis testing: difference between proportions

I am investigating staff inequality between genders and ethnicities in an institution. I have data on contract types (permanent or fixed term) and pay grades for almost all employees. I want to test ...
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0answers
30 views

Categorical Data

I have a questionare. Questionare has six variables, suppose x1,x2,....,x6 and each variable has six questions. each questions has a response , strongly agree, agree, indifferent, disagree, strongly ...
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2answers
18 views

Large difference in number of cases in each category of a variable

I want to run an analysis on a data set. However, the primary predictor variable (5 point scale) varies greatly in size of each group. I plan to create a dichotomous variable from these 5 category. ...
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0answers
88 views

Linear regression with dummy variables: p-value calculation

-The standard procedure (general case) for finding p-values for linear regression coefficients is usually like this: $$Y=b_{0}+b_{1}X+\epsilon$$ Since $\hat{ b_{1} }=\frac{\sum ...
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0answers
4 views

How can mutual information be used in analysing a survey of categorical/nominal data?

I have data arising from independent surveys taken from at least 200 participants. In the survey there is a set of question of categorical and nominal types. I have no knowledge of the nature of the ...
1
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1answer
95 views

(Automated) feature selection in multiple regression with categorical variables

I need a general guide on what are the appropriate approaches to automated feature selection in multiple regression with categorical variables. In my case, I have several numeric and categorical ...
0
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1answer
25 views

Multivariate stats

I have the following data to analyse and not sure what the best method would be. I have percent coverage data for several invasive plant species. as well as several variables including different land ...
0
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0answers
14 views

Joint model for ordinal repeated measures data and MNAR dropout using R

I have a dataset consisting of repeated measures data of graded toxicity scores (0-4) in a large number of patients being treated with a anti-cancer drug. We would like to identify predictors for ...
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2answers
53 views

Time series - plotting continuous and categorical variable

I have one dependent continuous variable and an independent categorical variable. Each one minute window on a time series is marked with one category, for example 10:00 - 4, 10:01 - 1, 10:02 - 5, ...
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0answers
11 views

preprocessing and dummy variables order of procedure

I would please like to know when I should conduct pre-processing procedures (removing near-zero variance, highly correlated predictor variables, and linear dependencies) when planning to create dummy ...
0
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0answers
31 views

Scaling categorical data in regression

It seems odd to scale a categorical variable, but I need to get the correct coefficients for each of my variables in linear regression. Is it correct to scale the same way you would with continuous ...
2
votes
1answer
46 views

Ok to use 0 and 1 for a varaible in a linear regression?

Ok this is a simple quesion that's been bugging me. The question is how to encode a linear model variable with only two possible values and avoid any trouble introduced by using zero. Say you have a ...
0
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3answers
32 views

SPSS - How do I analyse two categorical non-dichotomous variables?

I'm having some issues running an analysis with two categorical variables that are both non-dichotomous... Some background information on my study: My study focuses on how young adults sexually ...
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2answers
415 views

Why does it take R a long time to fit a model with a many-level factor?

I fit a model with a factor with many levels and it takes R a really long time to fit that model. Why is this? For example, if I fit a regression to predict players' salaries, and include a factor ...
2
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1answer
76 views

Generate random data for logistic regression with a categorical independent variable

I am trying to generate a data frame of fake data for exploratory purposes. Specifically, I am trying to produce data with a binary dependent variable (say, failure/success), and a categorical ...
0
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1answer
57 views

Analysing ranked data

I had following question in my questionnaire: Rank following factors: price, quality, advertisement, brand, reference from 1 (very important) to 5 (least important) that influenced on your buying ...
0
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1answer
27 views

Test for correlation between continuous and categorical variable [duplicate]

I am wanting to know what type of statistical test would need to be carried out to determine if there is a correlation between one categorical variable and one continuous variable.
0
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0answers
37 views

Controlling for categorical variables before correlation using residuals?

I’m looking for a way to control for the effect of multiple categorical variables, all of which contain two independent categories, on two continuous variables before I correlate these continuous ...