Stephen R. Cole
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View article: Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons
Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons Open
In epidemiology, some have argued that multiple comparison corrections are not necessary as there is rarely interest in the universal null hypothesis. From a parameter estimation perspective, epidemiologists may still be interested in mult…
View article: Clarifying Contradictions: Transportability in 17OHP-C Trials and Preterm Birth Outcomes Using Doubly Debiased Machine Learning
Clarifying Contradictions: Transportability in 17OHP-C Trials and Preterm Birth Outcomes Using Doubly Debiased Machine Learning Open
Following the Meis et al. trial that identified a benefit of 17-alpha-hydroxyprogesterone caproate (17OHP-C) in reducing the risk of recurrent preterm birth (PTB) (risk difference (RD) -18.6%, 95% confidence interval (CI): -28.2%, -9.2%), …
View article: Double robust variance estimation with parametric working models
Double robust variance estimation with parametric working models Open
Doubly robust estimators have gained popularity in the field of causal inference due to their ability to provide consistent point estimates when either an outcome or an exposure model is correctly specified. However, for nonrandomized expo…
View article: Effectiveness of dolutegravir-based vs boosted darunavir-based first-line 3-drug regimens in people with HIV with advanced disease: A trial emulation
Effectiveness of dolutegravir-based vs boosted darunavir-based first-line 3-drug regimens in people with HIV with advanced disease: A trial emulation Open
View article: Accounting for Missing Data in Public Health Research Using a Synthesis of Statistical and Mathematical Models
Accounting for Missing Data in Public Health Research Using a Synthesis of Statistical and Mathematical Models Open
Introduction: Accounting for missing data by imputing or weighting conditional on covariates relies on the variable with missingness being observed at least some of the time for all unique covariate values. This requirement is referred to …
View article: Empirical Sandwich Variance Estimator for Iterated Conditional Expectation g‐Computation
Empirical Sandwich Variance Estimator for Iterated Conditional Expectation g‐Computation Open
Iterated conditional expectation (ICE) g-computation is an estimation approach for addressing time-varying confounding for both longitudinal and time-to-event data. Unlike other g-computation implementations, ICE avoids the need to specify…
View article: Empirical Sandwich Variance Estimator for Iterated Conditional Expectation g‐Computation
Empirical Sandwich Variance Estimator for Iterated Conditional Expectation g‐Computation Open
Iterated conditional expectation (ICE) g‐computation is an estimation approach for addressing time‐varying confounding for both longitudinal and time‐to‐event data. Unlike other g‐computation implementations, ICE avoids the need to specify…
View article: A causal inference framework for leveraging external controls in hybrid trials
A causal inference framework for leveraging external controls in hybrid trials Open
We consider the challenges associated with causal inference in settings where data from a randomized trial are augmented with control data from an external source to improve efficiency in estimating the average treatment effect (ATE). This…
View article: A causal inference framework for leveraging external controls in hybrid trials
A causal inference framework for leveraging external controls in hybrid trials Open
We consider the challenges associated with causal inference in settings where data from a randomized trial are augmented with control data from an external source to improve efficiency in estimating the average treatment effect (ATE). This…
View article: Exposure effects on count outcomes with observational data, with application to incarcerated women
Exposure effects on count outcomes with observational data, with application to incarcerated women Open
Causal inference methods can be applied to estimate the effect of a point exposure or treatment on an outcome of interest using data from observational studies. For example, in the Women’s Interagency HIV Study, it is of interest to unders…
View article: A minimal nontrivial example of higher-order evidence
A minimal nontrivial example of higher-order evidence Open
Higher-order evidence (ie, evidence about evidence) allows epidemiologists and other health data scientists to account for measurement error in validation data. Here, to illustrate the use of higher-order evidence, we provide a minimal non…
View article: Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps
Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps Open
Importance Accurate assessment of gestational age (GA) is essential to good pregnancy care but often requires ultrasonography, which may not be available in low-resource settings. This study developed a deep learning artificial intelligenc…
View article: Double Robust Variance Estimation with Parametric Working Models
Double Robust Variance Estimation with Parametric Working Models Open
Doubly robust estimators have gained popularity in the field of causal inference due to their ability to provide consistent point estimates when either an outcome or exposure model is correctly specified. However, for nonrandomized exposur…
View article: M-estimation for common epidemiological measures: introduction and applied examples
M-estimation for common epidemiological measures: introduction and applied examples Open
M-estimation is a statistical procedure that is particularly advantageous for some comon epidemiological analyses, including approaches to estimate an adjusted marginal risk contrast (i.e. inverse probability weighting and g-computation) a…
View article: Higher-order evidence
Higher-order evidence Open
Higher-order evidence is evidence about evidence. Epidemiologic examples of higher-order evidence include the settings where the study data constitute first-order evidence and estimates of misclassification comprise the second-order eviden…
View article: Finite sample performance of optimal treatment rule estimators with right-censored outcomes
Finite sample performance of optimal treatment rule estimators with right-censored outcomes Open
Patient care may be improved by recommending treatments based on patient characteristics when there is treatment effect heterogeneity. Recently, there has been a great deal of attention focused on the estimation of optimal treatment rules …
View article: Higher-order evidence
Higher-order evidence Open
View article: The PRotective Effect of Maternal Immunisation on preTerm birth: characterising the Underlying mechanisms and Role in newborn immune function: the PREMITUR study protocol
The PRotective Effect of Maternal Immunisation on preTerm birth: characterising the Underlying mechanisms and Role in newborn immune function: the PREMITUR study protocol Open
Maternal immunisation, a low cost and high efficacy intervention is recommended for its pathogen specific protection. Evidence suggests that maternal immunisation has another significant impact: reduction of preterm birth (PTB), the single…
View article: Fusing trial data for treatment comparisons: Single vs multi‐span bridging
Fusing trial data for treatment comparisons: Single vs multi‐span bridging Open
While randomized controlled trials (RCTs) are critical for establishing the efficacy of new therapies, there are limitations regarding what comparisons can be made directly from trial data. RCTs are limited to a small number of comparator …
View article: Accuracy of portable ultrasound machines for obstetric biometry
Accuracy of portable ultrasound machines for obstetric biometry Open
Objective To evaluate the accuracy of two portable ultrasound machines (PUM) in assessing fetal biometry and estimated gestational age (EGA). Methods This was a secondary analysis of data from the Fetal Age Machine Learning Initiative, an …
View article: Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling
Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling Open
Studies designed to estimate the effect of an action in a randomized or observational setting often do not represent a random sample of the desired target population. Instead, estimates from that study can be transported to the target popu…
View article: HIV Prevention Among Men Who Have Sex With Men: Tenofovir Alafenamide Combination Preexposure Prophylaxis Versus Placebo
HIV Prevention Among Men Who Have Sex With Men: Tenofovir Alafenamide Combination Preexposure Prophylaxis Versus Placebo Open
BACKGROUND: While noninferiority of tenofovir alafenamide and emtricitabine (TAF/FTC) as preexposure prophylaxis (PrEP) for the prevention of human immunodeficiency virus (HIV) has been shown, interest remains in its efficacy relative to p…
View article: HIV Prevention Among Men Who Have Sex With Men: Tenofovir Alafenamide Combination Preexposure Prophylaxis Versus Placebo
HIV Prevention Among Men Who Have Sex With Men: Tenofovir Alafenamide Combination Preexposure Prophylaxis Versus Placebo Open
Background While noninferiority of tenofovir alafenamide and emtricitabine (TAF/FTC) as preexposure prophylaxis (PrEP) for the prevention of human immunodeficiency virus (HIV) has been shown, interest remains in its efficacy relative to pl…
View article: Synthesis estimators for positivity violations with a continuous covariate
Synthesis estimators for positivity violations with a continuous covariate Open
Studies intended to estimate the effect of a treatment, like randomized trials, may not be sampled from the desired target population. To correct for this discrepancy, estimates can be transported to the target population. Methods for tran…
View article: FIVE AUTHORS REPLY
FIVE AUTHORS REPLY Open
Journal Article Accepted manuscript Letter Get access Stephen R Cole, Stephen R Cole Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC Correspondence Address: Dr. Stephen R. Cole, Department of Epidem…
View article: The pregnant traveller: An overview of common preventable infections
The pregnant traveller: An overview of common preventable infections Open
Pregnant travellers are often unaware of the various infections that can be acquired during travel and that pregnant people may be at increased risk of severe disease compared to their non‐pregnant counterparts. Pregnant people often seek …
View article: Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling
Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling Open
Studies designed to estimate the effect of an action in a randomized or observational setting often do not represent a random sample of the desired target population. Instead, estimates from that study can be transported to the target popu…
View article: Accounting for nonmonotone missing data using inverse probability weighting
Accounting for nonmonotone missing data using inverse probability weighting Open
Inverse probability weighting can be used to correct for missing data. New estimators for the weights in the nonmonotone setting were introduced in 2018. These estimators are the unconstrained maximum likelihood estimator (UMLE) and the co…
View article: Accounting for nonmonotone missing data using inverse probability weighting
Accounting for nonmonotone missing data using inverse probability weighting Open
Inverse probability weighting can be used to correct for missing data. New estimators for the weights in the nonmonotone setting were introduced in 2018. These estimators are the unconstrained maximum likelihood estimator (UMLE) and the co…
View article: Reducing Bias in Estimates of Per Protocol Treatment Effects
Reducing Bias in Estimates of Per Protocol Treatment Effects Open
This secondary analysis of a randomized clinical trial evaluates ways of reducing bias in estimates of per protocol treatment effects.