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A Monte Carlo examination of an MTMM model with planned incomplete data structures

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
Psychology Research Institute > Health, Education and Well-being
ID Code:1525
Deposited By: Mrs Fiona Harkin
Deposited On:23 Dec 2009 09:10
Last Modified:03 Jul 2017 16:13

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