All Questions
Tagged with correspondence-analysis categorical-data
24 questions
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Correspondence analysis
I have a question. I have the following categorical data from an open text diary study:
Individuals reported emotions in different situations.
Each individual reported their emotions in 3 to 5 ...
- 1
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0
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43
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MCA weights to construct a score
I have a set of variables all measured on a nominal scale. I have applied the MCA function within the FactoMineR package to reduce the dimension of my data set. Next I would like to calculate a score ...
3
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1
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242
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Should low frequency categories be eliminated or amalgamated in multiple correspondence analysis?
This is just a theory question so no code or example is required I think. I want to know if there is a rule of thumb for what constitutes low frequency in MCA? Should the variable be eliminated? Could ...
- 107
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1
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425
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MCA : interpretation for contribution and correlation
According to the definitions:
The correlation matrix reports the correlation of each variable with each dimension.
Contribution refers to the contribution of each category of each variable to the ...
- 367
4
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2
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514
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MCA : what is the difference between indicator method (default) and Burt method ? and which one to use?
I have a dataset with 28 ordinal variables and 1402 individuals and I am tasked to apply MCA method to create a socio-economic score SES in order to assign individuals into socio-economic groups based ...
- 367
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490
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GLM with scores/principal dimensions from MCA
I hope someone can help me understand how to run this analysis!
I have a dataset with many categorical variables (i.e. color, pattern, texture) associated to each animal in each interaction between ...
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1
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679
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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 ...
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265
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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 ...
- 107
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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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124
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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
...
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3
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1
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598
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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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425
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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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4
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2
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220
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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 ...
1
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0
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642
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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 ...
- 143
1
vote
1
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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, ...
- 119
1
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1
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231
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Variability Analysis for Nominal Variables
I have a very large datasets (billions of observations) made of multiple nominal categorical variables (nominal, not ordinal), and I want to outline the set of variables that accounts for the most ...
- 1,984
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2
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1k
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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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4
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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 >...
- 169
2
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3
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1k
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Which analysis for a set of (0/1)binary variables alone?
I have a dataset I would like to analyze and plot
It consists of 100 binary variables (0/1) for about 2,000,000 observations
There is absolutely no quantitative variable, nor anything I could use as ...
- 21
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0
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368
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PCA on a heterogenous correlation matrix better than MCA?
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 ...
- 279
3
votes
1
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754
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How to interpret this correspondence analysis plot with individuals as nominal variable?
Background: Although correspondence analysis is used mainly for visualizing similarities of categories of two or more nominal variables, I tried following: 39 students (from the same survey as in this ...
- 3,979
5
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2
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8k
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How to best display crosstab data?
I have a 10x10 matrix composed of two variables with 10 brands each. One variable is the brand purchased, the other is the brand considered. My matrix shows a crosstabulation between the two. I need ...
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7
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2
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9k
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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 ...
- 3,625
224
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6
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273k
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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 ...
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