A Tutorial in Bayesian Potential Outcomes Mediation Analysis

Miočević, Milica; González, Oscar; Valente, Matthew J.; MacKinnon, David P.

doi:10.1080/10705511.2017.1342541

Cited by 55 publications

(39 citation statements)

References 101 publications

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“…The first step was to evaluate the unadjusted effects of both maternal and paternal age allowing for the effect to be non-linear. Graphical evaluation of the Total Effect, as defined in mediation modeling [ 23 – 25 ], confirmed the existence of parental age risks that were non-linear. The adjusted effects were estimated accounting for potential confounding between maternal and paternal age which are known to be highly correlated [ 16 ].…”

Section: Discussionmentioning

confidence: 99%

The risks of advancing parental age on neonatal morbidity and mortality are U- or J-shaped for both maternal and paternal ages

Thompson

2020

BMC Pediatr

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Background The biologic implications of delayed parenthood have been blamed for a major public health crisis in the United States, that includes high rates of neonatal morbidity and mortality (NMM). The objective of this study was to evaluate the risk of parent age on NMM and to provide results that can serve as a starting point for more specific mediation modeling. Methods Data containing approximately 15,000,000 birth records were obtained from the United States Natality database for the years 2014 to 2018. A Bayesian modeling approach was used to estimate the both the total effect and the risk adjusted for confounding between parent ages and for mediation by chromosomal disorders including Down syndrome. Outcomes included intra-hospital death and nine measures of neonatal morbidity. Results For paternal age, seven NMM (preterm birth, very preterm birth, low Apgar score, treatment with antibiotics, treatment with surfactant, prolonged ventilation, intra-hospital death) had U-shaped risk patterns, two NMM (small for gestational age, admission to neonatal intensive care) had J-shaped risk patterns, one NMM (seizures) was not significantly related to paternal age. For maternal age, three NMM (low Apgar score, treatment with antibiotics and intra-hospital death) had U-shaped risk patterns, four NMM (preterm delivery, very preterm delivery, admission to neonatal intensive care, treatment with surfactant) had J-shaped risk patterns, one NMM (small for gestational age) had a risk declining with age, one NMM (prolonged ventilation) had a risk increasing with age and one NMM (seizures) was not significantly related to maternal age. Conclusions Both advancing maternal and paternal ages had U- or J-shaped risk patterns for neonatal morbidity and mortality.

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Section: Discussionmentioning

confidence: 99%

The risks of advancing parental age on neonatal morbidity and mortality are U- or J-shaped for both maternal and paternal ages

Thompson

2020

BMC Pediatr

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“…The rst step was to evaluate the unadjusted effects of both maternal and paternal age allowing for the effect to be non-linear. Graphical evaluation of the Total Effect, as de ned in mediation modeling (21)(22)(23), con rmed the existence of parental age risks that were non-linear. The adjusted effects were estimated accounting for potential confounding between maternal and paternal age which are known to be highly correlated (16).…”

Section: Discussionmentioning

confidence: 89%

The Risks of Advancing Parental Age on Neonatal Morbidity and Mortality are U- or J-Shaped for Both Maternal and Paternal Ages.

Thompson¹

2020

Preprint

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Background: The biologic implications of delayed parenthood have been blamed for a major public health crisis in the United States, that includes high rates of neonatal morbidity and mortality (NMM). The objective of this study was to evaluate the risk of parent age on NMM and to provide results that can serve as a starting point for more specific mediation modeling. Methods: Data containing approximately 15,000,000 birth records were obtained from the United States Natality database for the years 2014 to 2017. A Bayesian modeling approach was used to estimate the both the total effect and the risk adjusted for confounding between parent ages and for mediation by chromosomal disorders including Down syndrome. Outcomes included neonatal mortality and nine measures of neonatal morbidity.Results: For paternal age, seven NMM (preterm birth, very preterm birth, low Apgar score, treatment with antibiotics, treatment with surfactant, prolonged ventilation, neonatal mortality) had U-shaped risk patterns, two NMM (small for gestational age, admission to neonatal intensive care) had J-shaped risk patterns, one NMM (seizures) was not significantly related to paternal age. For maternal age, three NMM (low Apgar score, treatment with antibiotics and neonatal mortality) had U-shaped risk patterns, four NMM (preterm delivery, very preterm delivery, admission to neonatal intensive care, treatment with surfactant) had J-shaped risk patterns, one NMM (small for gestational age) had a risk declining with age, one NMM (prolonged ventilation) had a risk increasing with age and one NMM (seizures) was not significantly related to maternal age. Conclusions. Under the assumptions of a specific causal model, both advancing maternal and paternal ages had U- or J-shaped risk patterns for neonatal morbidity and mortality.

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“…Given these limitations, and in line with other authors (e.g., Sullivan and Feinn, 2012), we encourage readers to report effect size estimates in any statistical model to assess the magnitude of an effect under study. Alternatively, researchers may consider different strategies entirely to investigate mediation effects (e.g., design approaches; Pirlott and MacKinnon, 2016; or Bayesian analyses; Enders et al, 2013; Miočević et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes

et al. 2019

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The utility of evaluating mediation effects spans across research domains. The model facilitates investigation of underlying mechanisms of event timing and, as such, has the potential to help strengthen etiological research and inform intervention work that incorporates the evaluation of mediating variables. In order for the analyses to be maximally useful however, it is critical to employ methodology appropriate for the data under investigation. The purpose of this paper is to evaluate a regression-based approach to estimating mediation effects with discrete-time survival outcomes. We empirically evaluate the performance of the discrete-time survival mediation model in a statistical simulation study, and demonstrate that results are functionally equivalent to estimates garnered from a potential-outcomes framework. Simulation results indicate that parameter estimates of mediation in the model were statistically accurate and precise across the range of examined conditions. Type 1 error rates were also tolerable in the conditions studied. Adequate power to detect effects in the model, with binary X and continuous M variables, required effect sizes of the mediation paths to be medium or large. Possible extensions of the model are also considered.

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A Tutorial in Bayesian Potential Outcomes Mediation Analysis

Cited by 55 publications

References 101 publications

The risks of advancing parental age on neonatal morbidity and mortality are U- or J-shaped for both maternal and paternal ages

The risks of advancing parental age on neonatal morbidity and mortality are U- or J-shaped for both maternal and paternal ages

The Risks of Advancing Parental Age on Neonatal Morbidity and Mortality are U- or J-Shaped for Both Maternal and Paternal Ages.

Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes

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