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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Having only binary variables, why is the use of PCA still appropriate?

I often see the use of PCA on large datasets with a lot of binary variables. As i recall, the computation of the principal components is done via eigenvalue decomposition (or SVD) of the correlation ...
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Is MCA equivalent to PCA when all variables are binary?

I am looking to apply principal component analysis on binary (true/false) data, and I have come across the "equivalence between PCA and MCA" (Multiple Correspondense Analysis) for binary data, but ...
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How to conduct a principal component analysis on data set with large number of zeros

I have data for percentage cover of plant species in 500 sites. There are columns for 30 different species in the data set and I would like to drastically reduce this down to a manageable number of ...
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992 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 ...
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194 views

Is Multiple Correspondence Analysis applicable to Multi-valued Categorical Variables?

I have a data-set containing only Categorical Variables. I needed to do Principal Component Analysis on the data set. Eventually, I found Multiple Correspondence Analysis and learnt it. But, in MCA, ...
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50 views

No departure from independence term in constrained correspondence analysis

I am used to think of correspondence analysis (CA) as dissecting the weighted departure from independence through singular value decomposition, but I cannot relate this to constrained correspondence ...
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805 views

Assumptions for Canonical Correspondence analysis

I have been trying to find the major assumptions a Canonical Correspondence Analysis makes when doing its analysis. I have had a hard time finding anything useful. I did, however, find the assumptions ...
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357 views

Do I need to standardize environmental data before canonical correspondence analysis?

I have a dataset of 15 environmental variables (soil physical and chemical properties) and about 25 "species" variables for about 40 sampling sites. I want to do a CCA to analyse the effects of the ...
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115 views

It is possible to apply correspondence analysis to a 2x2 contigency table?

I was wondering if it is possible to apply correspondence analysis to a 2x2 contingency table. Since that correspondence analysis is a method for dimensionality reduction, I think it is necessary to ...
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19 views

Interpreting the loads in a biplot

I came across a doubt about the interpretation of the biplot. I know that there are lot of questions related to this topic but I have a very concrete question, but I don't find any response. Suppose ...
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6 views

Dimension reduction - doing a PCA on the coordinates of a MCA

I have a dataset with 25 continuous variables and 2 categorical variables. I want to perform k-means clustering, so as a previous step I am performing a multiple correspondence analysis on the ...
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18 views

Principal Component Analysis on Numerical Predictors alone for Dimension Reduction

I'm trying to reduce the number of dimensions for this 'Network Anamoly Detection' dataset: https://www.kaggle.com/anushonkar/network-anamoly-detection The dataset has a total of 40 features out of ...
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94 views

Input data for Canonical Correspondence Analysis (CCA)

I'm going to conduct Canonical Correspondence Analysis (CCA). In the tutorial I've found at: CCA environmental data are discrete ...
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25 views

identifying what has changed in the data year on year

I have a dataset from one year and the 'same' dataset for the next year. I would like to identify what has changed in the datasets between the years. Both datasets have the same columns. I currently ...
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Display of dimensions in (multiple) correspondence analysis

I am getting into correspondence analysis and was wondering what the correct way is to display more than two dimensions in a biplot. I found examples with biplots showing dimensions plotted in order (...
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What assumptions about the data are require for Multiple Correspondence Analysis?

In multiple correspondence analysis, what assumptions about the data are necessary in order to find the principal coordinates for the rows and columns?
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201 views

Canonical Correspondence Analysis: how to interpret results

I am using Canonical Correspondence Analysis (CCA) to analyze phytolith abundances (similar to pollen) over environmental gradients. As I am new to CCA, I read some background info. The following ...
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I have done crosstabs and a Correspondence Analysis, having trouble reporting and interpreting Chi-Squared and Inertia?

I have data on 1500 cases with two variables (color, genus) with 5 colors and 6 genera. I almost had generally equal spread across genus, but one is disproportionately represented and has about twice ...
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How I interpretate a CCA plot (made with xlstat)?

Here are the 2 CCA (Canonical Correspondence Analysis) plot I'm trying to interpretate. I did them using the appropriate function in xlstat. I want to know how I should interpretate the fact that in ...
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CCA (Canonical Correspondence Analysis) - Which version of the dataset is more adequate?

I'm currently working on a dataset of +400 samples, with 2 quantitative variables (salinity and depth) and 2 qualitative ones (sequencing method performed and nature of the sample, sediment or water) ...
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278 views

Should PERMANOVA be used to select factors for Canonical Correspondence Analysis?

I am interested in investigating the relationship between species composition and several environmental factors. My question is whether it is appropriate to use PERMANOVA to select a 'best' ...
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370 views

How to analyse multiple choice and overlapping questions in MCA?

I need to analyze a survey about entrepreneurship which has around 50 categorical variables. Therefore, after some univariate analysis, I want to apply Multiple Correspondence Analysis (MCA) in order ...
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42 views

Is there an analog to logit Y-aware PCA for correspondence analysis?

I came across this tutorial of logit Y-aware PCA for dichotomous $Y$s. Does anyone know if there is an analogous procedure for correspondence analysis? It seems that there couldn't be since the Y-...
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534 views

R multiple correspondence analysis loadings

I'm running a multiple correspondence analysis in R using the FactoMineR package: ...
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325 views

Correspondence analysis vs chi square

My data: ...
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How to test for the effects of plant community composition on insect community composition whilst controlling for geographic distance?

I'm trying to test for the effects of plant community composition on insect community composition using ordination, but I need to control for geographic distance. I know CCA can handle three matrices ...
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55 views

Minimize shared variance of columns between factors in Correspondence Analysis

I am using correspondence analysis (CA) to analyze a contingency table. In the columns I have statements about some brands (characteristics) and in the rows I have the brands. My aim is to obtain in ...
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178 views

I want to run a same result of biplot in R

There is a software called Brandmap$^1$ which can return a biplot from a matrix. I am trying to run the same result in R but the coordinates are not the same. First I input a simple matrix into the ...
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31 views

Visualizing a correspondence analysis over time

I have two contingency tables of frequency data examining the same set of variables but at two different time points. I can make two separate before and after correspondence analysis plots but would ...
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291 views

How to interpret the results of my correspondence analysis?

Im looking for help interpreting an CA Factor MAP my df is : ...
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1answer
91 views

Map using correspondence analysis

I was studying by my own correspondence analysis and I got some questions about the map that one gets using this method for some rows and columns. For example the following map: http://www.statmethods....
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364 views

Correspondence analysis: how are row principal and supplement coordinates calculated?

How are row principal and supplement coordinates calculated in correspondence analysis (CA)? Specifically, I am looking for a simple example as how to derive them using linear combinations of the row ...
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142 views

Respondent supplementary points from correspondence analysis using ca package in R?

I am new to correspondence analysis and I'm trying to decipher a paper's application of it. The authors surveyed 100 consumers on attributes that they would assign to different deodorant brands. The ...
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467 views

Applying Multiple Correspondence Analysis when predictors have thousands of levels

I apologize in advance if my english isn't too clear. Please feel free to leave a comment and tell me what part doesn't make sense. I'm currently working on a dataset which contains web data and I ...
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134 views

multivariate analysis of dependent data

I have some diet data I am analyzing that was collected in different locations at different times (over 3 years). The nature of the sampling resulted in multiple predators at the same location. The ...
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644 views

How many chi-squared distance matrix does correspondence analysis make?

I am trying to understand step by step how correspondence analysis work. Suppose AxB (row x column) frequency matrix, roughly you should: 1) Calculate row and column profiles 2) Calculate chi-...
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85 views

Correspondence Analysis - Marketing - Respondent Ideal Points

How would you show respondent ideal points for a related question in the same survey? Specifically, how would you chart each respondents' ideal attribute groupings along the same dimensions created ...
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76 views

Detrended correspondence analysis

I have relative abundance data of monkey species in 4 different types of habitat. I would like to use detrended correspondence analysis. Is this a correct way to display my data? If so, how should I ...
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42 views

Predict/impute one cell of matrix using all other cells

The question: I want to predict/impute one missing cell of a matrix using the contents of all other cells. Anyone have ideas on how to do this? The context: The matrix is n people's responses to m ...
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25 views

Statistical technique to assess nutrition

My goal is to find risk factors for a disease. I think that a malnutrition is a risk factor for this disease. I have 5 variables that indicate the frequencies of ...
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53 views

Trying a multivariate analyses on time series (with R)

I got measures of one variable (that behaves as a time series) for different conditions (some quantitatives, but mostly are qualitatives). For example, this is a "fake" representative plot of this ...
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140 views

Steps to follow for correspondence analysis when each brand is not shown to every respondent

I want to understand the steps followed for correspondence analysis when each brand is not shown to every respondent. Till now I used to assign a number (proportion) to each brand for each attribute ...
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Modelling with multiple-valued variables

I am about to start out analysis of a microbiological data set (ETEC: enterotoxic echerichia coli in children with diarrhea). The variables refer to the ETEC, not to the children. Some of the ...
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Detrended Correspondence Analysis - site ordination with species vectors

I have performed a Detrended Correspondence Analysis for species composition of different replicate survey sites and constructed a site ordination plot. Sites were classified into habitat types, so I ...
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42 views

Perform k-means clustering after MCA for transforming categorical variables - provide weights to variables?

I have a very dataset with many observations (> 1 million), with mainly continuous variables and three categorical variables. After searching for clustering methods for mixed data, I decided to ...
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27 views

Using MCA/PCA together?

If I have a large dataset with continuous, discrete, and categorical data, is it appropriate to use MCA on the categorical features and PCA on the continuous, separately? I'm preprocessing my data ...
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How many observations need to be in place for multiple correspondence analysis with a particular number of questions/categories

I'm wondering about how many observations need to be in place for a particular set of questions. If I have data as follows: ...
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Multiple correspondence analysis, definition of distance between two categories of the same question

From the text : Multiple Correspondents Analysis by Brigette LeRoux The data for this quesiton is: The definition of $f_k$ is $f_k = n_k/n$ where $n$ is the total number of individuals and $n_k$ ...
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Intuition about how the formula for “variance of axis of angle $\alpha$ with horizontal axis” works (multiple correspondents analysis)

From the text : Multiple Correspondents Analysis by Brigette LeRoux the following is given (page 32). For the purposes of this post I'm just considering there to be two dimensions that point clouds ...
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Ranking groups based on multiple criteria

My objective: To give a more sound foundation to the data I have access to. This is an exercise that is aimed to look for some structure and soundness in the interpretation of the data BUT it can be ...