Linked Questions

1 vote
0 answers

PCA on categorical variables [duplicate]

I am working on a dataset with many categorical variables for a clustering problem. I've done one-hot encoding where a categorical column with 5 levels will become 5 columns, each has the standard ...
Bruce Jinru Su's user avatar
3 votes
1 answer

Should ordinal variables be normalized for PCA? [duplicate]

I need to analyze my (ecological) data with PCA, but the data don't seem to meet the assumption of normality very well. The problem is, that out of my 9 variables only two are continuous and the ...
Silas the Magic Car's user avatar
1 vote
0 answers

Item Factor Analysis, Item Response Theory and Exploratory IRT [duplicate]

I would be grateful if someone could explain the difference between Item Factor Analysis, Item Response Theory and Exploratory IRT. Any references especially for the exploratory IRT are welcome. Nikos
Nikolaos Tsigilis's user avatar
218 votes
6 answers

Can principal component analysis be applied to datasets containing a mix of continuous and categorical variables?

I have a dataset that has both continuous and categorical data. I am analyzing by using PCA and am wondering if it is fine to include the categorical variables as a part of the analysis. My ...
Nikolina Icitovic's user avatar
64 votes
8 answers

Does it ever make sense to treat categorical data as continuous?

In answering this question on discrete and continuous data I glibly asserted that it rarely makes sense to treat categorical data as continuous. On the face of it that seems self-evident, but ...
walkytalky's user avatar
  • 1,897
43 votes
1 answer

Doing principal component analysis or factor analysis on binary data

I have a dataset with a large number of Yes/No responses. Can I use principal components (PCA) or any other data reduction analyses (such as factor analysis) for this type of data? Please advise how I ...
Cathy's user avatar
  • 431
29 votes
4 answers

How to handle ordinal categorical variable as independent variable

I am using a logit model. My dependent variable is binary. However I have an independent variable which is categorical and contains the responses: ...
rahmat's user avatar
  • 291
17 votes
3 answers

What are the assumptions of factor analysis?

I want to check if I really understood [classic, linear] factor analysis (FA), especially assumptions that are made before (and possibly after) FA. Some of the data should be initially correlated and ...
Sihem's user avatar
  • 343
20 votes
3 answers

Item Response Theory vs Confirmatory Factor Analysis

I was wondering what the core, meaningful differences are between Item Response Theory and Confirmatory Factor Analysis. I understand that there are differences in the calculations (focusing more on ...
SimonsSchus's user avatar
9 votes
3 answers

What is Item Response Theory (IRT) called for continuous response?

I would like to model my problem using something similar to Item Response Theory, but my responses are not binary. They are continuous in $[0, 1]$. What are these models/the research field called?
user1141785's user avatar
13 votes
3 answers

Factor scores from discrete, ordinal responses

Is there a principled way to estimate factor scores when you have ordinal, discrete variables. I have $n$ ordinal, discrete, variables. If I make the assumption that underlying each response is a ...
fgregg's user avatar
  • 1,190
14 votes
3 answers

Non-parametric measure of strength of association between an ordinal and a continuous random variable

I'm throwing here the problem as I received it. I have two random variables. One of which is continuous (Y) and the other one which is discrete and will be approached as ordinal (X). I put below the ...
user603's user avatar
  • 21.7k
10 votes
2 answers

Recommended procedure for factor analysis on dichotomous data with R

I have to run a factor analysis on a dataset made up of dichotomous variables (0=yes, 1= no) and I don´t know if I'm on the right track. Using tetrachoric() I ...
cada's user avatar
  • 101
7 votes
2 answers

Factor analysis for ordinal variables that have different categories

I have a data set that contains about 40 categorical variables that are taken as independent variables (and believed to be related to some unobservable human resource factors) and 4 categorical ...
Blain Waan's user avatar
  • 3,565
11 votes
2 answers

Similarities and differences between IRT model and Logistic regression model

Despite the basic similarities like both of these model the probability of success rather than modelling the response variable directly; I believe that there are more reliable answers which point out ...
Artiga's user avatar
  • 333

15 30 50 per page