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   https://doi.org/10.1073/pnas.1708282114  

   Schuemie, Martijn J. ; Hripcsak, George ; Ryan, Patrick B. ; Madigan, David ; Suchard, Marc A. ( March 2018 , Proceedings of the National Academy of Sciences)
2. Bayesian calibration of a hybrid nuclear collision model using p−Pb and Pb-Pb data at energies available at the CERN Large Hadron Collider

   https://doi.org/10.1103/PhysRevC.101.024911  

   Moreland, J. Scott ; Bernhard, Jonah E. ; Bass, Steffen A. ( February 2020 , Physical Review C)
3. A calibration approach to transportability and data‐fusion with observational data

   https://doi.org/10.1002/sim.9523  

   Josey, Kevin P. ; Yang, Fan ; Ghosh, Debashis ; Raghavan, Sridharan ( July 2022 , Statistics in Medicine)

   Two important considerations in clinical research studies are proper evaluations of internal and external validity. While randomized clinical trials can overcome several threats to internal validity, they may be prone to poor external validity. Conversely, large prospective observational studies sampled from a broadly generalizable population may be externally valid, yet susceptible to threats to internal validity, particularly confounding. Thus, methods that address confounding and enhance transportability of study results across populations are essential for internally and externally valid causal inference, respectively. These issues persist for another problem closely related to transportability known as data‐fusion. We develop a calibration method to generate balancing weights that address confounding and sampling bias, thereby enabling valid estimation of the target population average treatment effect. We compare the calibration approach to two additional doubly robust methods that estimate the effect of an intervention on an outcome within a second, possibly unrelated target population. The proposed methodologies can be extended to resolve data‐fusion problems that seek to evaluate the effects of an intervention using data from two related studies sampled from different populations. A simulation study is conducted to demonstrate the advantages and similarities of the different techniques. We also test the performance of the calibration approach in a motivating real data example comparing whether the effect of biguanides vs sulfonylureas—the two most common oral diabetes medication classes for initial treatment—on all‐cause mortality described in a historical cohort applies to a contemporary cohort of US Veterans with diabetes.

    

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4. Are p -values under attack? Contribution to the discussion of ‘A critical evaluation of the current “ p -value controversy” ’: Are p -value under attack?

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   Piegorsch, Walter W. ( September 2017 , Biometrical Journal)
5. A nuclear physics example of statistical bootstrap is used on the MARATHON nucleon structure function ratio data in the quark momentum fraction regions xB → 0 and xB → 1. The extrapolated F2 ratio as quark momentum fraction xB → 1 is Fn 2 F p 2 → 0.4 ± 0.05 and this value is compared to theoretical predictions. The extrapolated ratio when xB → 0 favors the simple model of isospin symmetry with the complete dominance of sea quarks at low momentum fraction. At high-xB, the proton quark distribution function ratio d/u is derived from the F2 ratio and found to be d/u → 1/6. Our extrapolated values for both the Fn 2 F p 2 ratio and the d/u parton distribution function ratio are within uncertainties of perturbative QCD values from quark counting, helicity conservation arguments, and a Dyson-Schwinger equation with a contact interaction model. In addition, it is possible to match the statistical bootstrap value to theoretical predictions by allowing two compatible models to act simultaneously in the nucleon wave function. One such example is nucleon wave functions composed of a linear combination of a quark-diquark state and a three-valence quark correlated state with coefficients that combine to give the extrapolated F2 ratio at xB = 1.

   https://doi.org/10.1103/PhysRevC.107.065203  

   Valenty, Hannah ; West, Jennifer Rittenhouse ; Benmokhtar, Fatiha ; Higinbotham, Douglas W. ; Parker, Asia ; Seroka, Erin ( June 2023 , Physical Review C)

   A nuclear physics example of statistical bootstrap is used on the MARATHON nucleon structure function ratio data in the quark momentum fraction regions xB → 0 and xB → 1. The extrapolated F2 ratio as quark momentum fraction xB → 1 is Fn 2 F p 2 → 0.4 ± 0.05 and this value is compared to theoretical predictions. The extrapolated ratio when xB → 0 favors the simple model of isospin symmetry with the complete dominance of sea quarks at low momentum fraction. At high-xB, the proton quark distribution function ratio d/u is derived from the F2 ratio and found to be d/u → 1/6. Our extrapolated values for both the Fn 2 F p 2 ratio and the d/u parton distribution function ratio are within uncertainties of perturbative QCD values from quark counting, helicity conservation arguments, and a Dyson-Schwinger equation with a contact interaction model. In addition, it is possible to match the statistical bootstrap value to theoretical predictions by allowing two compatible models to act simultaneously in the nucleon wave function. One such example is nucleon wave functions composed of a linear combination of a quark-diquark state and a three-valence quark correlated state with coefficients that combine to give the extrapolated F2 ratio at xB = 1. 

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