Hi everyone,
I have conducted an average linkage, hierarchical cluster analysis using the Sneath and Sokall similarity coefficent as all my variables are binary (present=1, absent=0), but co-absence shouldn't weigh as much as co-presence in the clustering. Now I have found that the stopping rules in cluster analysis supported by Stata are the Calinski–Harabasz pseudo-F and the The Duda–Hart Je(2)/Je(1) index. However, both of these are for continous data.
Is there any way I could for instance use an adaptation of the Goodman ad Kruskal's gamma statistic for categorical data or something else like it in Stata?
FYI: I have nearly copy-pastet this post https://www.statalist.org/forums/for...on-binary-data as the problem described there is nearly the same as mine, however, no solution is provided. I am hoping a solution has been found since 2017.
Related Posts with Stopping rules in cluster analysis on binary data
Sample size calculation using Cohen's d / Hedges's gHi everyone, Can anyone please advise me on how to perform a sample size calculation using Cohen's …
Customization of graph combine with three graphsHi Statalisters I am working on a visualization where I am interested in the following graph combin…
Logit FE regression in cross-sectional data.Dear Statalist, I have read about this topic in various discussions but I could not take a clear re…
Ceo transition from male to femaleDear community, I have an unbalance panel data where I want to create the following variables with …
Errors while testing for serial correlation and generating a new variableDear everyone, I am new to this page. I want to ask two questions, please I want to apologize if …
Subscribe to:
Post Comments (Atom)
0 Response to Stopping rules in cluster analysis on binary data
Post a Comment