Research

My research includes projects in both statistical methodology and applied statistics, with a goal of keeping the two fields connected. Methodologically, I develop methods to work with real-world data, including electronic health records (EHR), mobile apps, and wearables. I specifically focus in causal inference methods, including modern machine learning techniques for heterogeneous treatment effect estimation, data integration approaches, and target trial emulation. I apply these methods primarily in women’s health, mental health, and pediatric health, working with data from EHR systems at Duke, the PCORnet® network, and consumer platforms like Natural Cycles and Oura. I’ve published under both my current name, Carly L. Brantner, and my previous name, Carly Lupton-Smith.

Causal inference, data integration & real-world data methods

My dissertation and ongoing methodological work focus on combining datasets - randomized trials, EHRs, and other real-world sources - to estimate heterogeneous treatment effects: how well an intervention works for a given person, not just on average.

Brantner CL, Nguyen TQ, Parikh H, Zhao C, Hong H, Stuart EA. Precision mental health: predicting heterogeneous treatment effects for depression through data integration. Journal of the Royal Statistical Society Series C: Applied Statistics. 2025 Dec 12:qlaf068.

Not every depression treatment works equally well for every patient. This paper develops methods to combine randomized trial data with real-world electronic health records to better predict which treatments are likely to help a given patient - a step toward more personalized mental health care.

Brantner CL, Yu W, Zhao C, Jeon K, Ringlein GV, Wang Q, Lemoto E, Nguyen TQ, Gagliardi JP, Zandi PP, Goldstein BA, Stuart EA, Hong H. The challenges of integrating diverse data sources: A case study in major depression. Health Services and Outcomes Research Methodology. Oct 2025.

Combining data from multiple health systems promises larger, more representative studies — but merging real-world data sources brings real headaches: different coding systems, different populations, different definitions of the same outcome. Using a multi-site study of depression treatment as a case study, this paper catalogs those challenges and offers practical guidance for researchers attempting similar integration.

Brantner CL, Nguyen TQ, Tang T, Zhao C, Hong H, Stuart EA. Comparison of methods that combine multiple randomized trials to estimate heterogeneous treatment effects. Stat Med. 2024 Mar 30;43(7):1291-1314.

When several randomized trials test the same treatment, combining them can reveal how effects vary across patient subgroups, information no single trial has the power to detect on its own. This paper compares the leading statistical approaches for that kind of synthesis, helping researchers choose the right method for their data.

Brantner CL, Chang TH, Nguyen TQ, Hong H, Stefano LD, Stuart EA. Methods for Integrating Trials and Non-experimental Data to Examine Treatment Effect Heterogeneity. Stat Sci. 2023 Nov;38(4):640-654.

Randomized trials give us confidence about cause and effect but often lack the diversity of real-world patients; observational data has the opposite trade-off. This review lays out the statistical toolkit for combining the two, so researchers can get both the rigor of trials and the representativeness of real-world data when studying how treatments work differently across individuals.

More in this area
  • Hong H, Zhao C, Jeon K, Badillo Goicoechea E, Brantner CL, Ringlein GV, Zandi PP, Gagliardi JP, Goes FS, Goldstein BA, Stuart EA. Comparative effectiveness of antidepressants for depression using EHRs from two health systems. BMC Psychiatry. In press.
  • Stewart W, Brantner CL, Stuart EA, Thomas L. Weight a Minute: Understanding Variability in PATE Estimates Across Target Populations. arXiv preprint arXiv:2512.01157. 2025 Dec 1. (with mentee Will Stewart)
  • Nguyen TQ, Roberts Lavigne LC, Brantner CL, Kirk GD, Mehta SH, Linton SL. Estimation of place-based vulnerability scores for HIV viral non-suppression: an application leveraging data from a cohort of people with histories of using drugs. BMC Med Res Methodol. 2024 Jan 25;24(1):21.

Women’s health & sport science

I work with data from menstrual tracking apps, wearables, and elite athlete cohorts to better understand female health and performance across the lifespan — often in collaboration with the US Soccer Federation’s Kang Women’s Institute and UNC’s Applied Physiology Laboratory.

Brantner CL, Koffman L, Stoms M, Goldsmith J, Freemas J. Making sense of the cycle: Statistical modeling techniques for menstrual health data. Women’s Reproductive Health. 11 Jul 2026; 1-19.

Menstrual tracking apps and wearables generate rich, day-to-day health data, but that data doesn’t fit the assumptions built into most standard statistical tools — it’s cyclical, irregular, and highly individual. This paper walks through modeling approaches suited to that structure, offering a practical guide for researchers working with this increasingly common data source.

More in this area
  • Moore SR, Cantú EI, Brantner CL, Britton ME, DelBiondo GM, Blue MNM, Bruinvels G, Hackney AC, Register-Mihalik JK, Smith-Ryan AE. Utilizing Machine Learning for Identification of Athlete Availability Predictors in a Multi-Sport Elite Female Athlete Cohort. Journal of Strength and Conditioning Research. Accepted 2026.
  • Donnelly GM, Coltman CE, Straker R, Wilkau HCVLU, Brantner CL, Moore IM. Pelvic compression garments alter running biomechanics, perceived support and fear of symptoms in postpartum women with pelvic floor dysfunction. Frontiers in Sports and Active Living, section Women in Sport. 8 Jan 2026;7.
  • McNulty KL, Taim BC, Freemas JA, Hassan A, Brantner CL, Oleka CT, Scott D, Howatson G, Moore IS, Yung KK, Hicks KM, Whalan M, Lovell R, Moore SR, Russell S, Smith-Ryan AE, Bruinvels G. Research across the female lifecycle: Reframing the narrative for health and performance in athletic females. Women in Sport and Physical Activity Journal. 2024 Sep 23;32(1).

Mental health & telehealth

Using electronic health records from a large academic health system, I study how depression care — including the shift to telepsychiatry — has changed over time and for whom.

Ettman CK, Brantner CL, Albert M, Goes FS, Mojtabai R, Spivak S, Stuart EA, Zandi PP. Trends in Telepsychiatry and In-Person Psychiatric Care for Depression in an Academic Health System, 2017-2022. Psychiatr Serv. 2024 Feb 1;75(2):178-181.

The shift to telehealth during the pandemic reshaped psychiatric care, but did it reach the patients who needed it most? This study tracks five years of depression care at a large academic health system to show how telepsychiatry and in-person visits shifted over time — and for whom.

More in this area
  • Ettman CK, Ringlein GV, Dohlman P, Straub J, Brantner CL, Chin ET, Sthapit S, Badillo Goicoechea E, Mojtabai R, Albert M, Spivak S, Iwashyna TJ, Goes FS, Stuart EA, Zandi PP. Trends in mental health care and telehealth use across area deprivation: An analysis of electronic health records from 2016-2024. PNAS Nexus. Feb 2025;4:pgaf016.
  • Ettman CK, Brantner CL, Badillo Goicoechea E, Dohlman P, Ringlein GV, Straub J, Sthapit S, Mojtabai R, Spivak S, Albert M, Goes FS, Stuart EA, Zandi PP. Gaps in psychiatric care before and after the COVID-19 pandemic among patients with depression using electronic health records. Psychiatry Research. 2025 Feb 1;344:116354.
  • Ettman CK, Jeon K, Dohlman P, Ringlein GV, Straub J, Brantner CL, Sthapit S, Haroz E, Badillo Goicoechea E, Iwashyna TJ, Goes F, Stuart EA, Zandi PP. Mental health services following suicide-related hospital visits: An analysis of electronic health records. Under review.
  • Lupton-Smith C, Stuart EA, McGinty EE, Dalcin AT, Jerome GJ, Wang NY, Daumit GL. Determining Predictors of Weight Loss in a Behavioral Intervention: A Case Study in the Use of Lasso Regression. Front Psychiatry. 2022 Feb 3;12:707707.

Pediatric & population health

A newer thread of my applied work: bringing real-world data methods to pediatric research through PCORnet®, including work on childhood constipation, autism, and inflammatory bowel disease.

Publications
  • Chumpitazi BP, Zelinski A, Marchesani N, Brantner CL, Tomaiuolo M, Kappelman MD. High Burden of Constipation among Autistic Youth - A Nationwide Query Powered by PCORnet®. The American Journal of Gastroenterology.

Open-source software

  • multicate — R package for combining multiple datasets to estimate conditional average treatment effects (with D. Obeng)
  • Predict_CATE — repository accompanying my heterogeneous treatment effect prediction work

Earlier work

COVID-19, aging & education research (2018–2023)
  • Lupton-Smith C, Goicoechea EB, Collins M, Lessler J, Grabowski MK, Stuart EA. Consistency between Household and County Measures of Onsite Schooling during the COVID-19 Pandemic. J Res Educ Eff. 2023;16(3):419-441. Code
  • Lupton-Smith C, Bentley JP, Roth DL. Subtypes of Transitions into a Family Caregiving Role: A Latent Class Analysis. J Appl Gerontol. 2024 Apr;43(4):374-385.
  • Olsen AA, Brantner CL, Dallaghan GLB, McLaughlin JE. A review of interprofessional education research: Disciplines, authorship practices, research design, and dissemination trends. Journal of Interprof Educ Prac. 2023 May 16;32:100653.
  • Lupton-Smith C, Badillo-Goicochea E, Chang TH, Maniates H, Riehm KE, Schmid I, Stuart EA. Factors associated with county-level mental health during the COVID-19 pandemic. J Community Psychol. 2022 Jul;50(5):2431-2442.
  • Riehm KE, Badillo-Goicoechea E, Wang FM, Kim E, Aldridge LR, Lupton-Smith C, Presskreischer R, Chang TH, LaRocca S, Kreuter F, Stuart EA. Association of Non-Pharmaceutical Interventions to Reduce the Spread of SARS-CoV-2 With Anxiety and Depressive Symptoms: A Multi-National Study of 43 Countries. Int J Public Health. 2022 Mar 3;67:1604430.
  • Fuller K, Lupton-Smith C, Hubal R, McLaughlin JE. Automated Analysis of Preceptor Comments: A Pilot Study Using Sentiment Analysis to Identify Potential Student Issues in Experiential Education. Am J Pharm Educ. 2023 Sep;87(9):100005.
  • Lessler J, Grabowski MK, Grantz KH, Badillo-Goicoechea E, Metcalf CJE, Lupton-Smith C, Azman AS, Stuart EA. Household COVID-19 risk and in-person schooling. Science. 2021 Jun 4;372(6546):1092-1097.
  • McLaughlin JE, Lyons K, Lupton-Smith C, Fuller K. An introduction to text analytics for educators. Curr Pharm Teach Learn. 2022 Oct;14(10):1319-1325.
  • Olsen AA, Lupton-Smith C, Rodgers PT, McLaughlin JE. Characterizing Research About Interprofessional Education Within Pharmacy. Am J Pharm Educ. 2021 Sep;85(8):8541.
  • Wolcott MD, Lupton-Smith C, Cox WC, McLaughlin JE. A Five-Minute Situational Judgment Test to Assess Empathy in First-Year Student Pharmacists. Am J Pharm Educ. 2019 Aug;83(6):6960.
  • McLaughlin JE, Lupton-Smith C, Wolcott MD. Text mining as a method for examining the alignment between educational outcomes and the workforce needs. Educ Health Prof. 2018 Jan;1(2):55-60.
  • Kitya D et al. Profile, Surgical Management, and Early Clinical Outcomes of Neural Tube Defects at Mbarara Regional Referral Hospital, Uganda. Under review.