Bunting, Brendan, Adamson, Gary and Mulhall, PK (2002) A Monte Carlo examination of an MTMM model with planned incomplete data structures. STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 9 (3). pp. 369-389. [Journal article]
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The classic approach for partitioning and assessing reliability and validity has been through the use of the multitrait-multimethod (MTMM) model. The MTMM approach generally involves 3 different groups (method) evaluating 3 traits. This approach can be reconceptualized for questionnaire evaluation, so that the method becomes 3 different scaling types, which are administered to the same respondents on different occasions to avoid carryover effects. A serious limitation of this MTMM model is that data are required from respondents on at least 3 different occasions, thus placing a heavy burden on the researcher and respondents. Planned incomplete data designs for the purpose of substantially reducing the amount of data required for MTMM models were investigated: 1st, a design that reduces the amount of data collected at the 3rd administration by 22%; and 2nd, a design in which data need only be collected at 2 occasions. The performance of Listwise Deletion, Pairwise Deletion, and the expectation maximization (EM) algorithm at dealing with planned incomplete data are examined through a series of simulations. Results indicate that EM was generally precise and efficient.
|Item Type:||Journal article|
|Faculties and Schools:||Faculty of Life and Health Sciences|
Faculty of Life and Health Sciences > School of Psychology
|Research Institutes and Groups:||Psychology Research Institute > The Bamford Centre for Mental Health and Wellbeing|
Psychology Research Institute
Psychology Research Institute > Health and Wellbeing
|Deposited By:||Mrs Fiona Harkin|
|Deposited On:||23 Dec 2009 09:10|
|Last Modified:||14 Apr 2014 15:16|
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