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 do interpret insignificant categorical variables for logistic regression

I am trying to interpret categorical variables with more than two classes. Some are significant whilst other classes are not. what can I infer from the insignificant ones? does this mean the ...
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8 views

Normalizing Data in Multiple Categories

I couldn't decide if this question belonged here or on the Math stack exchange, but I'm posting it here since it seems more directly relevant. Basically, I have a bunch of categories, labeled, say, ...
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Sample size for binary/categorical variables

I have a data set composed by 1000000 projects. Each project is characterized by its size in terms of KBs and a binary variable that is 1 whether the project is active, 0 otherwise. The distribution ...
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11 views

Relationship between number of Principal components and Exploratory factors.

Would like to know is there any heuristic relationship between the number of components identified from PCA analysis and the number of hidden factors provided by EFA analysis on the same data set?
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2answers
44 views

Understanding dummy (manual or automated) variable creation in GLM

If a factor variable (e.g. gender with levels M and F) is used in the glm formula, dummy variable(s) are created, and can be found in the glm model summary along with their associated coefficients ...
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30 views

Splitting factors in R [migrated]

I have a factor with values of the form Single (w/children), Married (no children), ...
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38 views

Converting factors to numeric values in R [migrated]

I have factors in R that are salary ranges of the form $100,001 - $150,000, over $150,000, ...
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0answers
18 views

How to examine the change of event sequences

Let's assume we have a sequence of events $x_1, x_2, ...,x_n$ and each event can be described as a categorical variable from domain $\{A, B, C...\}$. The time interval between two consecutive events ...
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16 views

Hierarchical choice modelling

I am trying to model students choices on studying from year to year and was thinking that a HLM would be the way to go, however I have become stumped in how to progress. The variable I am trying to ...
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2answers
70 views

Treating ordinal variables as continuous for regression problems

In the social sciences I have encountered that it is common to treat ordinal variables as continuous, for example variables originating from rating or Likert scales (strongly disagree, disagree, ...
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13 views

Convert a numeric variable into categories - median? absolute value?

Hi: I have a three numeric, continuous variables that are the factor scores that result from a factor analysis of 14 likert items. The analysis suggested three factors. The scores range from about -3 ...
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1answer
25 views

Does the degrees of freedom depend on whether the variable is continous or dummy variable?

In my dataset there is a lot of multicollinearity between the independent variables, therefore it is not possible for me to include them all in the same regression (especially because I have a small ...
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1answer
28 views

Do dummy variables count as independent variables when calculating degrees of freedom in a multiple regression?

The degrees of freedom in a multiple regression equals N−k−1, where k is the number of variables. Does k include dummy variables? For example, I have the model: ...
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1answer
24 views

Equal-size categories vs unequal-size categories

I'm trying to reduce the size of my dataset, which is composed of 200,000 projects. Each project is defined by its size and a binary value that is 1 if the project has active users, 0 otherwise. Most ...
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20 views

Finding multivariate clusters with survey data (in R)

I'd like to conduct a multivariate cluster analysis on data from the American Community Survey's PUMS microsample (individual level records). I've only performed cluster analysis before when there are ...
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1answer
24 views

Can I use the chi-squared test of independence with skewed data?

I have two variables, both categorical, one with skewed responses. How do you deal with skewed data in the chi-squared test? Are there any other relevant tests? I want to perform the test in SPSS.
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2answers
73 views

When to dichotomize a variable for correlational analysis? [closed]

This is the question I am trying to answer : I’m working on a thesis project and have a variable that is normally distributed and related to happiness. I am considering to split my sample into ...
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21 views

combining two categorical variables

I have one five point Likert scale variable (importance levels) for accessibility to a certain facility, and another three-level categorical variable (preferred distance). I want to combine these ...
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2answers
56 views

Time trend or time dummies in a panel

I'm doing a cross-country panel and wondering about the inclusion of time. I've seen people put time dummies for each year in the regression and others instead put a single time trend variable. It’s ...
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1answer
31 views

Grouping predictor factor levels based on response variable

I've read that it's bad to do this, but am looking for details as to why. Suppose we're trying to fit the linear model $Y_i = \beta_0 + \beta_1 X_{1i} + \beta_2 X_{2i} + \epsilon_i$ where $Y$ is ...
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24 views

Dimension reduction for likert questions, cronbach alpha

I need some input on how to proceed with my data. I have collected data from household survey on 180 sample to find out the importance given to the attributes in a residential location decision. The ...
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1answer
13 views

feature representation for DNA bases classification

I'm currently dealing with large DNA sequences for machine learning purposes, I'm basically improving existing methods. What I have is several millions of DNA sequences : ACGTAGGCAGGCTTTC ... In ...
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17 views
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1answer
49 views

Fisher's exact test or chi-square test

I have a 2x4 table with nominal data (the columns are simply YES/NO, the rows are four categories) ...
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25 views

Weeding out multi-collinear categorical variables

I have a huge amount of features that are categorical variables and I'm trying to find a system for weeding out categorical variables that are close to being multicollinear. Is vif a reasonable ...
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1answer
19 views

Is a model nested within itself before collapsing categorical variables?

If I have a model with a categorical variable $X_1=\{0,1,2,3\}$ and a continuous variable $X_2$, and I have a regression model that includes an interaction between $X_1$ and $X_2$, then I decide I ...
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1answer
58 views

Dummy variables for linear models with multiple levels

I'm currently working with data which has continuous variables and a hierarchical structure attached to it, think of measuring blood pressure, size and weight of different domestic animals (cats, ...
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23 views

Generating a categorical variable from an imputed variable

I am using multiple imputation to impute a continuous variable ($X$) with $\approx30\%$ missing values. I have a question regarding the generation of a new categorical variable ($Y$), starting from ...
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54 views

Logistic regression with binary inputs

Is logistic regression an appropriate classifier when the input data are binary? Say we are conducting an experiment where the subject is presented with blue and green circles of varying shades, and ...
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30 views

Continuous dependent variable that almost looks like a categorical variable

I recently conducted an experiment where people had to decide how much money to take from another participant. People could choose to pick any value between 0 and 100 percent. It turns out that around ...
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1answer
25 views

Inferential analysis on categorical medical data

I am currently conducting a retrospective chart review where I am interested in the efficacy of certain drugs when it comes to treating a certain disease (let's call the disease "A") Multiple drugs ...
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1answer
36 views

test of significance for comparing change between two groups

What test for significance is best to use to test the difference between the change of a categorical variable in a control group and the change in a pilot group? The variable had three categories ...
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55 views

how to code and interpret categorical time varying variable in Cox PH model

I'm working on a project looking at the relationship between exposure to several different drugs on the risk of preterm delivery in a cohort of pregnant women with a particular disease. I'm confident ...
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12 views

Detecting poaching by age class proportion - suggested test for detecting decrease in given age class?

My dataset consists of observations of individuals, recording the date and the individual's age class. Age classes vary in bin size: 0-4 5-9 10-19 20-40 Example ...
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35 views

Interpretation of p-values & reduction of model deviance for factors in anova() vs summary()

My data has 3 major inputs: BLDDAY (a factor), BLDMNT (a factor), and D_BLD_SER (days as an ...
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34 views

Explaining PLS-DA to a layman

I recently learned about PLS-DA in a statistics class. I am able to perform PLS-DA mathematically, but I am having trouble really explaining it. I was wondering if anyone could help me with how to ...
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1answer
58 views

Convert a categorical variable to a numerical variable prior to regression

I am doing a project to estimate students' final graduation GPAs based on several variables. I have students' first year GPAs, high school GPAs, their race, where they come from, and their ACT score, ...
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Correlation between a categorical predictor and a continuous outcome variable

How do I perform correlation between a categorical antecedent variable and a continuous outcome variable? Like for example, correlating EACH attachment style with another variable, i.e, social ...
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12 views

Assessing quality of a fixed sample size with limited information about full set

Given the level of this site these are probably intolerably newbie questions, but here goes... So I'm studying the cost of public transport in a given city. I have access to data from a hopefully ...
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1answer
29 views

Recoding a variable with three levels into a dummy variable

I need to recode the variable school setting (urban, sub-urban and rural settings) into a dummy variable. I know that when creating a dummy variable, there is one category less (so 2 rather than three ...
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40 views

Minimum observations for creating dummy variables from a categorical group variable

I have an OLS regression with around 1000 observations and created a dummy variable for at least 15 different categories (catholic, muslim, hindu etc). One of the created dummy variables (spiritual) ...
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1answer
154 views

Categorize continuous data effectively (taking into account a response variable)

I wonder what are the better approaches to categorize continuous data (e.g. age) than dividing them with the use of quantiles and cut function (in ...
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18 views

Analysing grade distributions: difference in proportions across years

I have data on grades obtained in a course over three consecutive years. The grade distribution includes the number of students who received a fail, pass, credit, distinction and high distinction. I ...
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1answer
78 views

predict function and categorical variables in R

This is more of a general question about how the predict function treats categorical variables and how to interpret the output from predict. I have a zeroinfl model to predict the number of animals ...
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1answer
78 views

Logistic Regression using dummy variables in MATLAB

I have a model where categorical (mutually exclusive) variables predict bankruptcy. Chi-square is significant. How can I code a logistic regression model in MATLAB ...
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19 views

What if a binary variable is very unbalanced? [duplicate]

For example, if I have gender in the regression formula. My data has 90 Male and 10 Female. I know it is not good to have two groups so unbalanced. The estimate of gender will have relative big ...
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2answers
145 views

I have my data set, now what?

I have a basic understanding of basic statistics, but I believe I've gotten myself out of my depth. I have a data set with a dependent variable (time span) and three quantitative independent ...
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48 views

Logit with dummies when certain number of dummies must be used

In Stata 12, I'm using logit to model a process that is successful or fails and requires seven workers. I have a larger pool of potential workers and am using dummies to signify which seven ...
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15 views

Imputing categorical variables before binarization

I wish to replace the missing values with mode of that categorical variable. In scikit-learn, we can something like Imputer(strategy="most_frequent", axis=0) but ...
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1answer
63 views

Dummy variables in a multiple regression

I have a linear regression model with 3 independent variables (let's say A1, A2, A3) and 2 ...