Hi SAJ,

nice to hear you again and to know that you are managing to find the right path to your analysis.

I hope that you will manage to get interesting results. I am happy to have helped a bit

As for your points (I repeat your numeration):

1) I think it is good. I understand that you have read the warnings about the interpretation of CA on stacked tables. But, from what you write, it seems so.

3) I wrote in one preceding post of mine that the issue of assessing the statistical significance of CA clusterings (or, generally speaking, CA results) is a complex one.

I have read Greenacre's Chapter 15, where he pointed out some hints: someones are easy to perform, others are difficult and require specific software. I have write to Prof. Greenacre himself to ask for some advices, and I am waiting for his reply. I wrote to the Past user Forum as well as to this forum, but I did not received any reply until now.

As far as the statistical significance of the division, e.g., of the Parties into two broad groups, I would act in the following way (but please note that I am not so sure about): I would perform a non-parametric test (e.g., Mann-Whitney) to test the significance of the median difference in vote between the two broad groups. The same (I guess) could be performed in relation to the Nationality (to keep with the dataset I worked on).

More "orthodox" ways (I found them in Greenacre book) are:

A) to perform chi-square test on the contingency table, to see if there is a significant association between rows and columns.

This can be easily performed with the CA's results and Excel.

Steps:

-take CA's results and get the total inertia (it is present in the output analysis or you can just sum up the inertia of the various axes as provided by Past output window)

-multiply this total inertia by the sample size (in our case, the table's grand total)

-so you get the chi-square value for your table

-go in Excel and use the function DISTRIB.CHI() and inside the parentheses put the chi-square value, then ";" and then the degree of freedom of your table. The latter is equal to the (number of row-1)*(number of columns-1).

-you get the probability associated to your chi-square values.

NOTE: Instead of using Excel, may be you can use any statpack by analysing the table.

B) to perform a similar analysis applied to the relevant axis:

-Take the inertia explained by the first axis

-multiply this by the table's grand total in order to get the chi-square contribution of this axis

-test this values referring to the table here attached

-if your values is greater than the corresponding value in the table, then that dimension is significant (assuming that your data are statistical valid [e.g., from random sampling]), that is there is less the 5% of possibility that it has arisen by chance.

To be sincere, I am unsure about the effect of different sample size on CA results. What I can say is that Moldovan profile is near the average, that is its "distribution" does not differ a lot between profiles.

4) When you will have to present your analysis, I think that you could start from the original table, and then perform the CA providing the scatterplot. Then you could wish to sort the table(s) according to CA results and provide some descriptive graphs (histograms ?) of the groupings you devise.

It could be nice to facilitate (along the scatterplot) the eyeballing of groupings by means of dendrograms of the cluster analysis on rows/columns scores on the relevant axes.

On this latter topics, I attach an interesting article found on the web. I also attach a PDF that explain the cluster analysis (it is from Minitab Guide, but I think it can be useful anyway).

As for program, I use various program, since each one has its own strong points (SPSS, but mainly PAST, MiniTab, SigmaPlot11).

So, I think it all.

I hope this can help and that this quite long reply does not confuse you.

I look forward to know about your results, and I hope that you will manage to do all by yourself. In any case, if you have any problem do not hesitate to contact me (here or privately [you can find my mail in my website]).

Good luck and happy new year,

Kind regards

Ciao!!

Gm