**85 correspondence-analysis questions.**

I have a questionnaire of 80 questions that I need to do dimension reduction on. About half the questions are ordinal (Likert-style questions), and the other half are qualitative/nominal. I've been ...

I am being asked to apply a statistical technique that I do not think is optimal. I have asked before, but was told my question was vague. I have re-worded it appropriately here.
I am being asked to ...

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 ...

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 ...

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 ...

I was reading the article Multiple Correspondence K-means: Simultaneous versus sequential approach for dimension reduction https://link.springer.com/chapter/10.1007/978-3-319-55477-8_8
I have this ...

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 ...

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 ...

I'm trying to understand the predicted patterns of a Canonical Correspondence Analysis (CCA). I understand one of this method's strengths in understanding ecological patterns lies in its assumption of ...

I am bit confused between two terms Canonical Correpondence Analysis and Canonical Correlation Analysis.
Are the two some how related or they are entirely different techniques?
Do they point to ...

Good day.
There are two questions to the community.
Can PCA / CA results be described by means of average, standard
deviations, medians, etc.?
How to use them in regression models and
typical ...

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 ...

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 ...

I have a dataset of discrete (ordinal, meristic, and nominal) variables describing morphological wing characters on several closely related species of insects. What I'm looking to do is conduct some ...

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, ...

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 ...

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 ...

I'm trying to interpret the results of Co-correspondence analysis (CoCA) with the R package cocorresp. The descriptive paper is rather unclear about how to interpret the results. I've performed the ...

I want to find relevant variables to do a market segmentation.
I have run an MCA with 10 variables on R. Among them :
1 is a supplementary qualitative variable (whether our customer has churned or ...

Im looking for help interpreting an CA Factor MAP
my df is :
...

in Asselin (2002) http://www.ipc-undp.org/conference/md-poverty/papers/Louis-Marie_.pdf , the expression of the categorical composite indicator of multiple correspondence analysis (qualitative ...

I have set of dichotomous variables and I am using Multiple Correspondence Analysis to develop an Index out of these variables. I have earlier tried Principal Component Analysis (PCA), but then ...

I want to analyse how the presence of reef fish species relates to benthic habitat cover at numerous survey sites (reef fish are measured via simple abundance counts and habitat cover is measured in ...

I've been dealing with a dataset full of categorical variables and had some issues to apply dimensionality reduction techniques as PCA is no great fit for such datasets.
After some research, I came ...

Having too many species in the data, makes the species labels overlap in a plot of a canonical correspondence analysis. This makes it difficult to interpret. Is there a reasonable possible solution?
...

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 ...

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 ...

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: ...

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 ...

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' ...

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 ...

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 ...

I want to display species coordinates relative to an environmental variable using ordination surface (ordisurf in vegan package)...

From a website
you can think that Correspondence Analysis is a categorical data
version of PCA. But the main usage of Correspondence Analysis is
different from that of PCA, and it is more like ...

I have a data set with six continuous variables. I would like to perform a multiple correspondence analysis (MCA) with fuzzy coding. I was able to create the fuzzy coding, so for each original ...

I am trying to measure distances between basket assortments in a grocery shopping.
I have all information that who buys what in every shopping by online and offline.
I want to see the pattern of the ...

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-...

I'm using the FactoMineR package in R to do a Multiple Correspondence Analysis on a large set of data. Specifically, I'm looking for correlations among a set of five categorical variables.
I used the ...

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

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....

Can we use percentage values obtained from secondary source instead of frequency values in the contingency table for using the correspondence analysis?
eg: in a contigency table with row variable ...

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 ...

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 ...

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 ...

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. ...

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 ...

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 ...

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 ...

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 ...

- pca
- r
- multivariate-analysis
- categorical-data
- data-visualization
- factor-analysis
- spss
- biplot
- interpretation
- binary-data
- ecology
- correlation
- dimensionality-reduction
- clustering
- vegan
- logistic
- canonical-correlation
- regression
- chi-squared
- references
- survey
- biostatistics
- distance
- discrete-data
- permutation-test

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