Questions tagged [correspondence-analysis]

Correspondence analysis is a dimensionality-reduction and mapping technique for nominal variables. It is often applied to a contingency table to explore visually affinities among row and column categories. If a table is 3+ dimensional the analysis is called Multiple Correspondence analysis.

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38
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1answer
13k views

PCA and Correspondence analysis in their relation to Biplot

Biplot is often used to display results of principal component analysis (and of related techniques). It is a dual or overlay scatterplot showing component loadings and component scores simultaneously. ...
153
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6answers
150k views

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 ...
39
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3answers
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Would PCA work for boolean (binary) data types?

I want to reduce the dimensionality of higher order systems and capture most of the covariance on a preferably 2 dimensional or 1 dimensional field. I understand this can be done via principal ...
19
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1answer
15k views

Interpreting 2D correspondence analysis plots

I've been searching the internet far and wide... I have yet to find a really good overview of how to interpret 2D correspondence analysis plots. Could someone offer some advice on interpreting the ...
6
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2answers
7k views

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 ...
20
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1answer
8k views

What is the “horseshoe effect” and/or the “arch effect” in PCA / correspondence analysis?

There are many techniques in ecological statistics for exploratory data analysis of multidimensional data. These are called 'ordination' techniques. Many are the same or closely related to common ...
4
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1answer
8k views

(Multiple) Correspondence Analysis for count data entered as binary variables

I have a data set, 1014 cases and 55 variables which are binary and is in the form of ...
6
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1answer
1k views

Interpreting 2D correspondence analysis plots (Part II)

I'd like to ensure that I understand the process correctly. This is a follow-up question to Interpreting 2D correspondence analysis plots ...
2
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2answers
4k views

How can one interpret the Stata output for Multiple Correspondence Analysis?

As an alternative to conducting exploratory factor analysis on a set of data, with binary responses, I have been suggested to use Multiple Correspondence Analysis (MCA). Following is a curtailed and ...
2
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1answer
2k views

Interpreting Canonical Correspondence Analysis (CCA) Inertia - in Vegan

I am wanting to know if I can use the ratio of Constrained/Total Inertia in my CCA to describe 'The variability explained by my constraining variables'. I am asking because I've seen different ...
9
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1answer
2k views

What criteria to use for separating variables into explanatory variables and responses for ordination methods in ecology?

I have different variables that interact within a population. Basically I have been doing an inventory of millipedes and measuring some other values of the terrain, like: The species and the amount ...
9
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1answer
7k views

Using principal components analysis vs correspondence analysis

I am analyzing a data set concerning intertidal communities. The data are percent cover (of seaweed, barnacles, mussels, etc) in quadrats. I am used to thinking about correspondence analysis (CA) in ...
9
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2answers
2k views

What is French data analysis?

Some statistical methods - I do not remember if it is principal component analysis or something like that - are sometimes called "French data analysis". What is it exactly ? And some people say that ...
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2answers
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Correspondence analysis for a three-way contingency table

I'm wondering how to proceed to perform Canonical Correspondence Analysis and Multiple Correspondence Analysis in R on the following three-way contingency table ...
6
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4answers
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Clustering binary categorical data

I have some data where I have certain classes (c1, c2, c3, c4 ...) and the data comprises of binary vectors where 1 and 0 denote that an entry belongs to a class or not. The number of classes will be >...
4
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1answer
3k views

How best to normalize count data to compare two distributions

Say I have a vector of length 1000. At each position (1 ... 1000) there is a count. I have two vectors with different range of counts such that in vector A the maximum number of counts at a position ...
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4answers
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Grouping samples by clustering or PCA

If I have 5 binary variables with values for 100 observations to give me a 5x100 matrix. ...
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1answer
72 views

Can Y-aware PCA be performed with binary independent variables?

I came across this tutorial for Y-aware PCA using the vtreat R package. In short, Y-aware PCA is PCA on variables that have been scaled to be in y-units. Is it valid to scale categorical independent ...
4
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3answers
1k views

Whether to use factor analysis based on binary multiple response data?

I have a survey where I have asked people which type of computer games they enjoy and whether they consider themselves a hardcore gamer. I allowed people to select multiple genres, but now I am unsure ...
2
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0answers
946 views

R vegan: RDA vs CCA, which test to answer my research question and which results to report?

(if my question should be cut up into sub-questions please let me know, since all those questions are related I decided to ask them here together as one long question) Main question As part of my ...