What is it about?
Adverse childhood experiences (ACEs) are cumulative traumatic events originally associated with poor adult health and well-being. Most of the previous research on ACEs has used cut score points on the number of ACEs. However, Poisson regression is the most accurate statistical analysis methodology for cumulative events or count data. This study examined this statistical method with other methods of statistically analyzing the cumulative effects of ACEs on children’s problem behavior.
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Why is it important?
Over 25 years, a large number of studies reported inappropriate statistical methods in studying the cumulative effect of adverse childhood experiences (ACEs). We show that Poisson regression is less biased and provides better estimates of their association with children’s functioning.
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This page is a summary of: Poisson regression is the best method to analyze cumulative adverse childhood experiences., School Psychology, February 2025, American Psychological Association (APA),
DOI: 10.1037/spq0000686.
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