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Published in: BMC Medical Research Methodology 1/2005

Open Access 01-12-2005 | Research article

Structural equation model testing and the quality of natural killer cell activity measurements

Authors: Leslie A Hayduk, Hannah Pazderka-Robinson, Greta G Cummings, Merry-Jo D Levers, Melanie A Beres

Published in: BMC Medical Research Methodology | Issue 1/2005

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Abstract

Background

Browne et al. [Browne, MacCallum, Kim, Andersen, Glaser: When fit indices and residuals are incompatible. Psychol Methods 2002] employed a structural equation model of measurements of target cell lysing by natural killer cells as an example purportedly demonstrating that small but statistically significant ill model fit can be dismissed as "negligible from a practical point of view".

Methods

Reanalysis of the natural killer cell data reveals that the supposedly negligible ill fit obscured important, systematic, and substantial causal misspecifications.

Results

A clean-fitting structural equation model indicates that measurements employing higher natural-killer-cell to target-cell ratios are more strongly influenced by a progressively intrusive factor, whether or not the natural killer cell activity is activated by recombinant interferon γ (rIFN γ). The progressive influence may reflect independent rate limiting steps in cell recognition and attachment, spatial competition for cell attachment points, or the simultaneous lysings of single target cells by multiple natural killer cells.

Conclusions

If the progressively influential factor is ultimately identified as a mere procedural impediment, the substantive conclusion will be that measurements of natural killer cell activity made at lower effector to target ratios are more valid. Alternatively, if the individual variations in the progressively influential factor are modifiable, this may presage a new therapeutic route to enhancing natural killer cell activity. The methodological conclusion is that, when using structural equation models, researchers should attend to significant model ill fit even if the degree of covariance ill fit is small, because small covariance residuals do not imply that the underlying model misspecifications are correspondingly small or inconsequential.
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Metadata
Title
Structural equation model testing and the quality of natural killer cell activity measurements
Authors
Leslie A Hayduk
Hannah Pazderka-Robinson
Greta G Cummings
Merry-Jo D Levers
Melanie A Beres
Publication date
01-12-2005
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2005
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/1471-2288-5-1

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