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From |
Marcello Pagano <pagano@hsph.harvard.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Nested design problem |

Date |
Fri, 16 Nov 2012 07:51:02 -0500 |

m.p. On 11/16/2012 7:32 AM, Steven Raemaekers wrote:

Hello David, Thanks for your response! You can view the connections between people as a directed graph, with arbitrary arrows between people when they have a connection. There is not a value for each possible pair of people, a lot of connections are missing and are then considered irrelevant, but I'm only interested in the subjects which have connections to other people so this should not be a problem. Maybe it is indeed an analysis problem because I have already collected the data and I already know my research question. Then the question becomes more how to choose a statistical model that does most justice to reality. Regards, Steven On 16 nov. 2012, at 13:13, David Hoaglin wrote:Hi, Steven. The problem you describe is interesting. I don't recall seeing anything like it in the statistical literature. I view it as an analysis problem, rather than a design problem (you have already collected the data). Some of the work in sociology on networks may be relevant. I think it would be more appropriate to consider closeness as the dependent variable. Do you have a value of closeness for each of the possible pairs of people? If not, what is the structure of the subset of people for whom you do have closeness? David Hoaglin On Thu, Nov 15, 2012 at 4:44 PM, Steven Raemaekers <s.raemaekers@sig.eu> wrote:Hello, I do not know where else to post this problem so I hope somebody can help me here. I have a statistical design issue which is as follows. As an example, let's say I have a table with information on people in the following format: Id IQ Introvertness … person1 120 80 … person2 110 70 … person3 130 40 … This table contains a number of properties of certain persons, each person is a unique entry in this table. I also have a table which contains relationships between those persons: Id1 Id2 Closeness person1 person2 80 person1 person3 70 "Closeness" is a property of the relationship between person1 and person2. The numbers do not make sense but are just for illustration. Now I want to test whether people that are in relationships "closer" to each other are more intelligent. I also possibly want to take into account other properties of people. In regression terms: I want to regress the dependent variable IQ on the independent variable closeness and introvertness. How can I do this? The problem is, persons can appear multiple time in the list so applying normal linear regression or correlation on this table produces incorrect results. Additionally, there are two sides to the relationship, so there is a connection between the IQ of person1, the closeness of their relationship and the IQ of person2. I believe the thing I need is called a nested hierarchical model/mixed model, but I have no idea how to design this. My questions are therefore the following: 1) What statistical test do I need to test my hypothesis on this data? 2) What assumptions does this test make and how can I check these assumptions? 3) How should I format my data? 4) What are the commands in Stata to execute this test? Thanks very much! Regards, Steven Raemaekers PhD student Software Improvement Group/TU Delft* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Nested design problem***From:*Steven Raemaekers <s.raemaekers@sig.eu>

**Re: st: Nested design problem***From:*David Hoaglin <dchoaglin@gmail.com>

**Re: st: Nested design problem***From:*Steven Raemaekers <s.raemaekers@sig.eu>

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