Contents
What is a factorial analysis of mixed data?
In statistics, factor analysis of mixed data ( FAMD ), or factorial analysis of mixed data, is the factorial method devoted to data tables in which a group of individuals is described both by quantitative and qualitative variables. It belongs to the exploratory methods developed by the French school called Analyse…
How to use are factor analysis on mixed data?
The data is from a survey where subjects have answered questions of many types: yes/no; continuous; scales. My aim is to use FA as a method for analyzing the underlying factors. I do not yet know what factors I’m looking for.
Which is a gain of a mixed method analysis?
mixed methods analysis is very simple. It is that: (1) effectively combining more than one source or type of data and/or more than one approach to analysis will deliver a gain over using a single source, type of data, or approach to analysis, and (2) effective integration of sources and analyses will also deliver
Who is the founder of mixed data analysis?
It belongs to the exploratory methods developed by the French school called Analyse des données founded by Jean-Paul Benzécri. The term mixed refers to the simultaneous presence, as active elements, of quantitative and qualitative variables.
When to use PCA or MCA in FAMD?
Roughly, we can say that FAMD works as a principal components analysis (PCA) for quantitative variables and as a multiple correspondence analysis (MCA) for qualitative variables. When data include both types of variables but the active variables being homogeneous, PCA or MCA can be used.
The FAMD’s original work is due to Brigitte Escofier and Gilbert Saporta. This work was resumed in 2002 by Jérôme Pagès. The most complete presentation of FAMD in English is included in a book of Jérôme Pagès. ^ Escofier Brigitte & Pagès Jérôme (2008).
When to use pcamix for mixed data analysis?
Use PCAmix method to analyze a data table where observations are described by quantitative variables and qualitative variables. Available in Excel with XLSTAT. What is Factorial analysis of mixed data? Factorial analysis of mixed data is a method initially developed by Hill and Smith (1972).
What are the advantages of using mixed methods?
Using a mixed methods study has several advantages, which we discuss below. Compares quantitative and qualitative data. Mixed methods are especially useful in understanding contradictions between quantitative results and qualitative findings.
Which is the proper way to handle mixed type data?
The proper way of handling mixed-type data. State-of-the-art distance metrics. Fun fact: Scikit-Learn doesn’t have any distance metrics which can handle both categorical and continuous data! How can we then use clustering algorithms, e.g. k-NN, if we have a dataset with mixed-type variables?
Why are distance metrics useful for mixed type data?
Then, we can say that old and short patients of a certain hospital will be quite similar to each other, whereas a young and tall patient won’t be that much similar to an old and a short one. The distance metrics are just algorithms which can tell you what is the similarity between two instances based on their attributes.