Investigating which type of maltreatment has the largest impact on health: The challenge of measurement error
Abstract
To answer the question of which type of maltreatment has the largest impact on health outcomes, researchers often simultaneously enter multiple maltreatment predictors in a single regression model. However, this approach of mutual adjustment is problematic, as some maltreatment types (e.g. physical neglect) are often measured with more error than others (e.g. physical abuse). Greater measurement error attenuates effect sizes and reduces statistical power to detect associations, implicitly creating the appearance that better measured maltreatment types are more impactful. The attenuation is particularly severe in mutually adjusted models, as maltreatment types tend to correlate with each other. Researchers comparing maltreatment types should routinely report on reliability estimates such as McDonald’s omega and present separately-estimated associations next to the mutually adjusted model.
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