ArticleVaccine2019
Use of three summary measures of pediatric vaccination for studying the safety of the childhood immunization schedule.
Article in Vaccine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- The Childhood Vaccination Schedule and the Lack of Association With Type 1 Diabetes.Pediatrics · 2021Article
- Incidental Brain Magnetic Resonance Imaging Findings and the Cognitive and Motor Performance in the Elderly: The Shanghai Changfeng Study.Frontiers in neuroscience · 2021Article
- Deceptology in cancer and vaccine sciences: Seeds of immune destruction-mini electric shocks in mitochondria: Neuroplasticity-electrobiology of response profiles and increased induced diseases in four generations - A hypothesis.Clinical and translational medicine · 2020Review
- Further considerations on rotavirus vaccination and seizure-related hospitalization rates.Infection and drug resistance · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundSummary measures such as number of vaccine antigens, number of vaccines, and vaccine aluminum exposure by the 2nd birth day are directly related to parents' concerns that children receive too many vaccines over a brief period. High correlation among summary measures could cause problems in regression models that examine their associations with outcomes.
objectivesTo evaluate the performance of multiple regression models using summary measures as risk factors to simulated binary outcomes.
methodsWe calculated summary measures for a cohort of 232,627 children born between 1/1/2003 and 9/31/2013. Correlation and variance inflation factors (VIFs) were calculated. We conducted simulations (1) to examine the extent to which an association can be detected using a summary measure other than the true risk factor; (2) to evaluate the performance of multiple regression models including true and redundant risk factors; (3) to evaluate the performance of multiple regression models when all three were risk factors; (4) to examine the performance of multiple regression models with incorrect relationship between risk factors and outcome.
resultsThese summary measures were highly correlated. VIFs were 7.14, 6.25 and 2.17 for number of vaccine antigens, number of vaccines, and vaccine aluminum exposure, respectively. In simulations, an association would be detected if a summary measure other than the true risk factor was used. The power to detect the association between the true risk factor and outcome significantly decreased if redundant risk factors were included. When all three were risk factors, multiple regression model was appropriate to detect the stronger risk factor. Correctly specifying the relationship between risk factors and the outcome was crucial.
conclusionsMultiple regression models can be used to examine the association between summary measures and outcome despite of high correlation among summary measures. It is important to correctly specify the relationship between risk factors and outcome.
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