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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181 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 ...
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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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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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1answer
796 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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16 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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21 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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1answer
225 views

Multiple Correspondence / Correlation Analysis

I'm a little bit new to statistics, so I'm not sure what I really need. I have a table like the following with some categorical/nominal values (like Gender and Age Group) and a ratio scaled value (...
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1answer
18 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 ...
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7 views

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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21 views

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 ...
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1answer
194 views

Multiple correspondence analysis for clustering (unsupervised learning) [closed]

I have limited stat/coding knowledge yet I try to do user clustering using unsupervised method using R. I have about 2795 observations gained from survey (mixture of categorical and scale questions). ...
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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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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 ...
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936 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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1answer
87 views

What statistics could an online book store use? [closed]

This is a theoretical question. If I had an online bookstore what kind of statistics would I keep. The number of times a book was viewed is one example. Another example may be the number of visitors ...
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2answers
248 views

Cluster users based on file access and application usage

I have access to file access data for employees in my organisation. For each employee I can see what read/write operations they carried out in the last month or so. Per operation, I see a user ID, ...
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Difference between canonical correpondence analysis and canonical correlation analysis

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 ...
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1answer
149 views

Statistical Measure for Bidirectional Relationships

I have a karma website where you can create a topic and someone can upvote the topic once. People who receive upvotes from another individual tend to upvote topics from the other individual. What is ...
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1answer
9k views

interpreting NMDS ordinations that show both samples and species

I am using the vegan package in R to plot non-metric multidimensional scaling (NMDS) ordinations. I am using this package because of its compatibility with common ...
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3answers
216 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 ...
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1answer
823 views

Is it effective to use one hot encoding of categorical data as input to PCA for anomaly detection?

I have a mixture of numeric and categorical inputs, the categorical inputs are relatively low cardinality (perhaps 10-15). I want to use PCA for anomaly detection, but am not sure how best to encode ...
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1answer
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Preprocessing survey data for clustering

I want to find 4-10 clusters in survey data with 100 questions answered by 2000 individuals using a technique such as K-means or Gaussian Mixture Models. There is no response variable so the ...
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1k views

Regression with an unknown dependent variable - estimating “likelihood” to do something

This probably seems like a really strange question, but let me try to explain what I want to do; hopefully it will make sense. I have a data set with a couple dozen variables, such as age, level of ...
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3answers
171 views

Problem with PCA

I am trying to do some PC analysis on my data coming from lipids measurements in different samples. I only have one factor: if samples are diabetic or non-dibetic. Here is the PCA graph I get: As you ...
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5answers
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How to find the similarity between movie preferences (in the form of a probability vector)of two users?

I am working on recommender systems, and using some methodology I have got a probability of each user liking a movie. To elaborate, say user $u_1$ has the following distribution for movie preferences ...
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1answer
1k views

Ecological modelling: multivariate abundance time-series data

I am working with a dataset that consists of abundance counts of 6 microbial taxa in a lake measured weekly for 20 weeks. I also have environmental data (temperature, nutrient concentrations, ...
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68 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 ...
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4answers
1k views

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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4answers
6k views

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 >...
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2answers
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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 ...
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3answers
31k views

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 ...
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1answer
168 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 ...
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1answer
105 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 ...
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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 ...
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0answers
31 views

Detrended Correspondence Analysis or Non-metric multidimensional scaling

For an ecology project I am analysing how and if the species composition of a habitat type (heathland for example) changes through time. This was done by measuring fixed plots within a habitat type ...
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1answer
392 views

Row normalization before correlation analysis for abundance data

I work with datasets in which protein abundances are reported across samples. I have some measurements of biological samples that should be more or less equal in protein abundance. After getting ...
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2answers
699 views

Factor analysis with categorical responses and missing data

I factor analyzing a measure with 55 categorical items (3 categories each). I am use CFA to test a 7 factor model. I have a very large sample (>10,000), but approximately 20% of the sample is missing ...
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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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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 ...
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0answers
51 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 ...
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1answer
27 views

Calculating a “nice” deviation from an average [closed]

I am not a statistician. But I've ended up working on a product that needs some statistics. Hopefully I can explain my question well enough. Let's say I run a store that sells shirts. Small, Medium, ...
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2answers
181 views

Problems with representing and analysing non-network data as a network?

Suppose I have a dataset with 200 observations of 30 categorical variables. The dataset describes websites and different kinds of design features they deploy (or do not deploy). If I were to convert ...
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3answers
5k views

How to cluster survey data?

I have designed a rather long (250 Qn) survey designed to uncover user clusters. The questions are such that the pattern of answering should elicit user clusters, but I am having trouble uncovering ...
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0answers
295 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 ...
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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 ...
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1answer
1k views

Do I always need to log transform my data to do a canonical correspondence analysis?

I have species relative abundance data (as percentages) and several environmental parameters- and I have done normality tests on my data and it all seems to be normally distributed, but do I need to ...
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0answers
248 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) ...
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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 ...