When studying how a response variable depends on an explanatory variable it is convenient to create pairs of matched observations, i.e. pairs consisting of two observations that are homogeneous, except for the studied explanatory variables and the response variable. So, the matching procedure is a method with the purpose to control for different nuisance variables. Normally the analysis of such studies is straightforward, but it is possible to complicate it. Usually an expert that is not necessarily a statistician creates the matched pairs. In that case it is also customary that this expert finds one pair member suitable in several pairs, which means trouble for the analysing statistician. The expert understanding for the statistical problems is however limited in most cases. Therefore it has been necessary to develop a statistical method for analysing the results from a study with matched pairs, where it is allowed for an observation unit to be member of several pairs. An obvious consequence of that is that results from pairs with one common pair member will be dependent. It is therefore necessary to formulate an analysing method that is applicable when there are dependencies between different pairs. Another consequence from allowing the same object to occur in several pairs is that it may lead to a data set with redundancy. This would be the situation if objects a and b form one pair, a and c another and finally b and c a third pair. The third pair is just the difference between the two firsts. Then it is necessary to find a method that remove redundant pair like b and c as well. (Author/publisher) This document is also available electronically via Internet at URL: http://www.vti.se/EPiBrowser/Publikationer/R495A.pdf
Abstract