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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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 ...
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62 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 ...
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11 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 ...
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8 views

Goodness of fit indices 5 factor model [on hold]

My model is a 5-factor model with 19 variables. LISREL student version can not compute multivariates above 15 variables. SmartPLS does not compute Goodness of fit indices. I can not find any free ...
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5 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
41 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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19 views

How to choose what dummy variable to exclude in R [closed]

I am running a regression and with dummy and categorical variables. R is choosing the omit the dummy variable that I don't want omitted. I know the interpretation is still the same, but I would like ...
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8 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 ...
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29 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 ...
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1answer
44 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 ...
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2answers
18 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
401 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 ...
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1answer
67 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 ...
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42 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 ...
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1answer
23 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.
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29 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 ...
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1answer
50 views

Analyzing the effect of categorical variables on a correlation coefficient

For my research project, I’m looking for some help on how to analyze my data. The research setup is as follows: I’ve got two normal variables that I want to correlate with each other and a number of ...
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39 views

Graph Interpretation

I would like to ask what could be the most possible interpretation of these two graphs attached. One of them depicts conditional probabilty p(Y|X) whereas the second one shows Y regressed on X. I ...
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19 views

How does GBM model handle categorical variables with many levels

I am using gbm model to fit a continuous dependent variable Y with several categorical variables, say, X, Z, V, and W. Suppose X has many levels (distinct values) and Y has moderate number of levels, ...
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1answer
168 views

Survey Method on Personal Isues

A statistician friend of mine told me of an interesting technique used to obtain honest responses on surveys that dealt with sensitive issues. I recall the general gist of the method, but am wondering ...
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1answer
52 views

Machine learning - curve categorisation

I have curves of the following structure (it is the blue one I am interested in) These curves reflect the volume of blood (actually gamma ray counts) in the left ventricle as a function of time ...
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45 views

Mann-Whitney U-test in R

I'm doing a Mann Whitney U test in R but it won't run the code: downstream<-subset(mydata,Direction=="D") Wilcox.test(Date, Species, data="downstream") ...
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19 views

Interactions between Dummy codded categorical variables in R

I have estimated a mixed-logit model in R.Here are my Results ...
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57 views

Replicating stata results in R

I'm working with a faculty member who wanted me to do the data work in Stata, but now wants me to estimate the models in R as well because the graphics are more flexible. However, I'm having some ...
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41 views

Distances for binary and non binary categorical data

I am computing a matrix of distances for categorical data. I am using the Jaccard distance since as far as I understood it should be working properly with this kind of data. I have BOTH binary and ...
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Dealing with numbers-based categorial data in rf regression: to standardize, or encode?

I'm working with the SEER cancer dataset, and I'm trying to use regression to calculate the months a breast cancer patient can expect to survive given certain variables. Some of these variables are ...
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3answers
94 views

Why do we need to dummy code categorical variables

I am not sure why we need to dummy code categorical variables. For instance, if I have a categorical variable with four possible values 0,1,2,3 I can replace it by two dimensions. If the variable had ...
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1answer
18 views

Variable selection: Why certain categories are chosen but not others?

I'm doing variable selection using the Lasso. To explain my response variable I have several predictors, both categorical and numerical, but I have problems to explain the process that underlies ...
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43 views

Minimum sample size to observe certain outcomes

Given a categorical random variable with large number of possible outcomes and a sufficiently large sample, I observe that 90% of the sample falls into some relatively small number of categories, say, ...
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2answers
18 views

How to compare beta subgroup with beta overall group?

My plain regression looks as follows: tendaystockreturn = alpha + beta * dummy variable that takes a value of 1 in case a director purchases shares Now I want to test whether a subgroup of directors ...
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1answer
37 views

Answering “1” to more than one of the dummies for a single categorical variable?

When using multiple dummies for a categorical variable: what happens if a few of your observations can check off "1" in more than one of the dummies? Does it matter? Does it only matter dependent on ...
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24 views

Quantify shift between different categories

Let us consider a ordinal variable with four values say A,B,C,D (A greater than B greater than C greater than D) and a person can have any of these values at a given point in time. I have data which ...
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1answer
47 views

How to determine whether a set of data are qualitative or quantitative?

Assume a data set with multiple columns, where the categorical data are coded. What is the best rule(s) or rule of thumb to determine whether each column contains qualitative data or quantitative ...
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11 views

Finding the effects of certain levels of a factor predictor

I have fitted a binary classification gbm model, and one of the predictor variables, Affiliate has 50 different levels. Given ...
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1answer
121 views

How to represent categorical data in a pie graph form?

I have been asked to produce a pie graph of some categorical data. On a simple scale it look like this: ...
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31 views

AICc and K for categorical factors and interactions

I am new to multimodel inference. I am trying to create a model that has multiple categorical factors and possible interactions. For example say that my model is... Y ~ X1 + factor(X2) + ...
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25 views

Pairwise chi-squared tests with Bonferroni correction

I have two categorical datasets, say, $A$ and $B$, which are sparse. I would like to apply pairwise $\chi^2$ tests to a certain categories, which are sufficiently populated (say, have expected values ...
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18 views

Adonis on categorical data

I wish to run Permanova on categorical data (example CSV structure is below) without any successes. Is Adonis can handle categorical data, an example script will be great. Thanks a lot I have a this ...
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8 views

One-hot encoding before or after split into training and test sets?

Is it safe to do my one-hot encoding of categorical variables before splitting the data into training and test and cross validation sets? I ask because this process alters the dimension of the data, ...
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1answer
34 views

Is Student's $t$-test the right choice?

I have 2 patient populations taken from the same time period that underwent 2 different surgical laparoscopic procedures. I want to compare the rate of conversion to an open surgical procedure. In my ...
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94 views

I do not have hypotheses for my research and I have got only categorical data. what kind of data analysis can i conduct? also

I do not have hypotheses for my research and I have got only categorical data. what kind of data analysis can i conduct for correlation between variables? also is chi-square used only for hypotheses ...
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1answer
22 views

Analyse data with ordinal and continuous independent variables and a categorical dependent variable

I'm trying to find a test that will allow me to test the relationship between a categorical dependent variable and several independent variables that are both continuous (interval) and ordinal. If ...
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25 views

Evaluating the $H_0$ of a contigency table

I have a 2 way contigency table with variables $A=\{a_1,a_2\}$ and $B=\{b_1,b_2\}$. I have the observed cell frequencies $O_1=a_1b_1$, $O_2=a_1b_2$, $O_3=a_2b_1$ and $O_4=a_2b_2$. My null hypothesis ...
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interpretation of Goodman Kruskal Gamma

Value of Goodman-Kruskal Gamma = 1 or -1 means that X and Y are monotonic but not strictly so i.e., $X_1 < X_2$ implies $Y_1 \leq Y_2 $. Can someone please explain this to me with an example?
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77 views

logistic regression with dummy variables for fractional factorial design

We have conducted a survey experiment with varying amounts of incentive (factor 1 = I1, I2, I3, I4, I5). The experiment was conducted stepwise in three subsequent studies (factor 2 = S1, S2, S3). ...
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41 views

How do you draw a random sample of unique IDs in a large dataset?

Rookie here -- I have a a large data set with about 75,000 observations, and 2000 unique IDs. Therefore, each unique ID has about 37 observations. I'm trying to draw a random sample of unique IDs, say ...
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Combining categorical and continuous variables to calculate a factor

I have a categorical predictor (income) and three continuous predictors (area, no. of bed rooms and no of cars). How can I form a single factor from these variables? In other words I want to combine ...
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22 views

Filtering Samples of Unequal Size and Correlating Categorical with Non-Categorical Data

Suppose I have a large number of samples, some of which only contain one observation, and some of which contain up to 12. Each observation can fall into one of four categories per sample. This ...