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Cluster analysis would be the best.. On Jul 30, 2013 12:11 AM, "Justice Moses K. Aheto" <[log in to unmask]> wrote: > Based on the very little explanation you provided, I will specifically > recommend Cluster Analysis. > However, remember that the nature of your data or the type of variables > you are considering matters much in deciding which measure will best fit > your situation. > Many thanks and I hope this helps. > > Kind regards. > > Justice Moses K. Aheto. > PhD Candidate in Medicine (United Kingdom) > MSc Medical Statistics (United Kingdom) > BSc Statistics (Ghana) > HND Statistics (Ghana) > > (Chief Executive Officer) > Statistics & Analytics Consultancy Services Ltd. > E-mail: [log in to unmask] > Mobile:0044(0)7417589148 (United Kingdom) > 00233(0)509914602 (Ghana) > > ------------------------------ > *From:* Angelica Neisa <[log in to unmask]> > *To:* [log in to unmask] > *Sent:* Monday, July 29, 2013 6:23 PM > *Subject:* Cluster of items > > Hello Everyone, > > I have a list of 80 people,each of them with a list of personal products > used in the last 24 hours. I want to find groups of items that are commonly > used together. What statistical technique would you recommend to this? > > Thanks you very much for your answers, > > Angelica, > > You may leave the list at any time by sending the command > SIGNOFF allstat > to [log in to unmask], leaving the subject line blank. > > > You may leave the list at any time by sending the command > > SIGNOFF allstat > > to [log in to unmask], leaving the subject line blank. > You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.