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.

Filter by
Sorted by
Tagged with
0
votes
0answers
6 views

Correspondence Analysis GSVD (generalised single value decomposition) proof

I'm not able to found a simple proof or just a normal detailed proof of: \begin{aligned} \mathcal{X}^{2} &=n \text { trace }\left(\left(\mathbf{F}-\mathbf{r c}^{\prime}\right)^{\prime} \mathbf{D}_{...
0
votes
0answers
14 views

Quality of an MCA in R [duplicate]

I'm trying to perform an MCA (Multiple Correspondence Analysis) on a large sample of individuals (>15 000) and 8 variables with R. When I perform that MCA using Factominer, my first dimension 1 ...
1
vote
0answers
51 views

What are the metrics to assess the quality of a multiple correspondence analysis (MCA) model?

We are trying to implement a multiple correspondence analysis (MCA) model. I was looking for metrics to assess the quality of an MCA to evaluate our model. Sadly, I didn’t find much literature about ...
1
vote
0answers
11 views

Should I consider the contribution of a variable in correspondance analysis if the $cos^2$ is weak?

So I have this table that represents contribution and cosinus of variable in CA I noticed that the most popular choice ( 1-5 hours ) has the weakest contributions and the weakest cosinus. It made ...
0
votes
1answer
54 views

What are the assumptions of Multiple Correspondence Analysis?

Is it possible to make Multiple Correspondence Analysis (MCA) with nominal data (such as country or gender) ? And more broadly, what are the assumptions of MCA? For me, MCA is a type of factor ...
0
votes
1answer
14 views

Canonical Correspondence Analysis on non-ecological data

I have two datasets: one with samples (rows) taken at different months of the year and abundances or counts of different types of particles I found (columns), and the other with samples (rows) and the ...
0
votes
0answers
28 views

Unsure on how to interpret Multiple Correspondence Analysis plot ? MCA

I came across this handout: https://www.displayr.com/interpret-correspondence-analysis-plots-probably-isnt-way-think/ . Whilst it has explained alot for me, i am still uncertain on how to interpret it ...
1
vote
0answers
32 views

Feature selection with PCA and CA?

I am studying some factorial methods, namely, PCA and Correspondence Analysis and I have a few questions for you. It is clear that the principal axes in PCA are linear combinations of the original ...
0
votes
0answers
37 views

Understanding the chi-squared distance in MCA

I am having some confusion regarding the chi-squared distance in multiple correspondence analysis. Specifically, I do not wholly understand how the definition of the distance plays back to the idea ...
2
votes
1answer
25 views

Visualizing shared instances of p-values<alpha across large numbers of treatments

Assume a data table that presents the p-values of a large number of independent runs of a statistical hypothesis test. Each run represents a single test with two possible hypotheses (i.e., null and ...
1
vote
0answers
18 views

Multiple Correspondence Analysis probabilities class membership

Is it possible to get probabilities of class membership based on Multiple Correspondence Analysis which uses hierarchical clustering? I am thinking along the lines of Latent Class Analysis that ...
0
votes
1answer
50 views

Detrended canonical correspondence analysis in R

Is it possible to perform a Detrended Canonical Correspondence Analysis in R? Im looking to analyse ecological (pollen) data to investigate beta diversity through time. As far as I can tell I have to ...
0
votes
0answers
16 views

What does the parameter assignment change when clustering using Multiple Correspondence Analysis (MCA) in R?

I'm using MCA with FactoMineR in R to see whether there are particular clusters (co-...
0
votes
0answers
48 views

Multiple Correspondence Analysis to inform a composite variable

I have 28 categorical variables, some binary, some with many levels (n=161). I want to use some of these variables to make a composite variable to investigate a latent characteristic, and then test ...
1
vote
0answers
41 views

Multiple Correspondence Analysis as PCA

The book "Multiple Factor Analysis by Example Using R" states that MCA can be thought as an unstandardized PCA of the transformed Complete Disjunctive Table (basically an indicator matrix). ...
1
vote
0answers
122 views

Accounting for spatial structure in constrained ordination analysis (vegan)

I am looking to use ordination to test whether certain environmental measures influence the microbial community in soil samples. I am a bit confused about the correct way to define the model and ...
2
votes
1answer
79 views

How can I solve "horseshoe effect" on ordination analysis (Canonical Correspondence Analysis)?

I would like to ask for help in the analysis of Canonical Correspondence Analysis (CCA) that I did in the Vegan package in R, with my dataset of species and environmental parameters. The result ...
0
votes
0answers
23 views

Is it possible to code in a CA the additional variables in dummies variables

I'm doing a correspondence analysis as part of a study. Unfortunately, one of the commands I use with R doesn't work because I have supplementary categorical variables that the package doesn't ...
1
vote
0answers
29 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 ...
1
vote
0answers
28 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 ...
2
votes
1answer
439 views

How do I interpret the angles of two concentration ellipses?

Consider a map with two concentration ellipses like this below. The Vomit_y group is (almost?) perfectly vertical, while the Vomit_n group seems to be oriented at about 45 degrees. I understand that ...
0
votes
0answers
161 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 ...
1
vote
1answer
21 views

How to pool variables that rarely occur, particularly with respect to survey data

From the text : Multiple Correspondents Analysis by Brigette LeRoux very infrequent categories of active variables need to be pooled with others when feasible The text doesn't explain how this ...
1
vote
0answers
340 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 ...
0
votes
2answers
89 views

Difference between two groups of people, each person "is" several characteristics

I have two groups of people, A and B (let's say 15 and 25 people). Each person in each group is characterized by a bucket of features (bucket = 6-18 features). Each feature, during qualitative phase ...
1
vote
0answers
27 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 ...
3
votes
0answers
564 views

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 ...
1
vote
0answers
18 views

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 (...
1
vote
0answers
35 views

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?
0
votes
0answers
76 views

Coding a categorical variable: 0-1 or multiple subcategories?

I'm working with R and want to run a correspondance analysis on a dataset containing, among the others, the following factors: city district: 27 levels, each corresponding to a given district ...
3
votes
0answers
60 views

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 ...
2
votes
2answers
219 views

One-hot encoding for SOM

I have a question regarding how I should convert categorical data to numerical data. I'm using this kdd99cup intrusion detection dataset, which has a 41 attributes and class label is the type of ...
5
votes
0answers
3k views

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 ...
1
vote
0answers
501 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 ...
3
votes
0answers
2k 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 ...
1
vote
0answers
36 views

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 ...
1
vote
3answers
710 views

What do to after hierarchical clustering and finding number of clusters

I have a dataset with 10 categorical variables with over 5000 observations, I have clustered and then found the optimal number of clusters using elbow method. Now I'm not sure what to do because I'm ...
2
votes
0answers
319 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, ...
5
votes
1answer
286 views

Is there a specific name for this plot?

This plot represents the popularity of technologies in two "tools", vue and react. In left-top corner are specific technologies for vue but not for react, right-top technologies popular in both tools ...
1
vote
0answers
435 views

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 ...
1
vote
0answers
268 views

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) ...
6
votes
1answer
314 views

How to perform CCA with block design in R

Following example and data are completely fabricated: Suppose I am studying grooming behaviour in apes. I have four cages, 8 apes in each (4 females + males). For 24 hours I did an observations with ...
2
votes
1answer
133 views

What in cross validation from co-correspondence analysis indicates sufficient axes numbers?

The coca function at cocorresp package disponible for R provides a predictive way to relate two biological composition datasets. I need help to understand one step from examples on documentation ...
2
votes
0answers
56 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 ...
0
votes
1answer
240 views

How variables (constrained loadings) are selected in a biplot CCA

I am trying to do a Canonical correspondence analysis (CCA) using the community data and chemical data. I have my family level taxonomic data as community data. In chemical data I have 18 variables: ...
1
vote
0answers
466 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' ...
2
votes
0answers
439 views

How to analyse multiple choice and overlapping questions in MCA? [closed]

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 ...
1
vote
1answer
95 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 ...
1
vote
0answers
45 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-...