Method Papers

Here I list my method papers under several topics, which are ordered alphabetically. For a complete and uncategorized list, see my Google Scholar.

Disparities research

Chang T-H, Nguyen TQ, Jackson JW. (2024). The importance of ethical value judgements and estimator-estimand alignment in measuring disparity and identifying targets to reduce disparity. American Journal of Epidemiology. 193(3):536-547. [journal]

Generalizability

Schmid I, Rudolph KE, Nguyen TQ, Hong H, Seamans MJ, Ackerman B, Stuart EA. (2022). Comparing the performance of statistical methods that generalize effect estimates from randomized controlled trials to much larger target populations. Communications in Statistics - Simulation and Computation. 51(8):4326–4348. [published]

Nguyen TQ, Ackerman A, Schmid I, Cole SR, Stuart EA. (2018). Sensitivity analyses for effect modifiers not observed in the target population when generalizing treatment effects from a randomized controlled trial: Assumptions, models, effect scales, data scenarios, and implementation details. PLoS ONE. 13(12):e0208795. [published] [arXiv] [supp1-5] (also listed under Sensitivity analysis)

Nguyen TQ, Ebnesajjad C, Cole SR, Stuart EA. (2017). Sensitivity analysis for an unobserved moderator in RCT-to-target-population generalization of treatment effects. Annals of Applied Statistics. 11(1):225-247. [published] [arXiv] (also listed under Sensitivity analysis)

Nguyen TQ, Stuart EA. (2020). Correction: Sensitivity analysis for an unobserved moderator in RCT-to-target-population generalization of treatment effects. Annals of Applied Statistics. 14(1):518-520. [published] (also listed under Sensitivity analysis)

Heterogeneous treatment effects

Brantner CL, Nguyen TQ, Teng T, Zhao, C, Hong H, Stuart EA. (2024). Comparing Machine Learning Methods for Estimating Heterogeneous Treatment Effects by Combining Data from Multiple Randomized Controlled Trials. Statistics in Medicine. [published] [arXiv]

Brantner CL, Chang T-H, Nguyen TQ, Hong H, Di Stefano L, Stuart EA. (2023). Methods for integrating trials and non-experimental data to examine treatment effect heterogeneity. Statistical Science. 38(4):640-654. [published] [arXiv]

Mediation analysis

Schuler MS, Coffman DL, Stuart EA, Nguyen TQ, Vegetabile B, McCaffrey DF. (Under review). Practical challenges in mediation analysis: A guide for applied researchers. [arXiv]

Coffman DL, Schuler MS, Nguyen TQ, McCaffrey DF. (2023). Weighting for causal mediation. In Hanbook of Weighting and Matching Adjustments for Causal Inference. Edited by Zubizaretta JR, Stuart EA, Small DS, Rosenbaum PR. Chapman & Hall/CRC Handbooks of Modern Statistical Methods. pp 373-412.

Nguyen TQ, Ogburn EL, Schmid I, Sarker EB, Greifer N, Koning IM, Stuart EA. (2023). Causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects. Statistics Surveys. 17:1-41. [journal] [pdf] [arXiv]

Nguyen TQ, Schmid I, Ogburn EL, Stuart EA. (2022). Clarifying causal mediation analysis: Effect identification via three assumptions and five potential outcomes. Journal of Causal Inference. 10:246-279. [journal] [pdf] [arXiv]

Nguyen TQ, Schmid I, Stuart EA. (2021). Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn. Psychological Methods. 26(2):255-271. [published] [arXiv]

Stuart EA, Schmid I, Nguyen TQ, Sarker EB, Pittman A, Benke K, Rudolph K, Badillo-Goicoechea E, Leoutsakos J- M. (2021). Assumptions not often assessed or satisfied in published mediation analyses in psychology and psychiatry. Epidemiologic Reviews. 43(1):48-52. [journal] [pdf]

Nguyen TQ, Webb-Vargas Y, Koning IH, Stuart EA. (2016). Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention. Structural Equation Modeling. 23(3):368-383. [journal] [pdf] [supplement]

Missing data and measurement error

Nguyen TQ, Carlson MC, Stuart EA. (Accepted). Identification of complier and noncomplier average causal effects in the presence of latent missing-at-random (LMAR) missing outcomes: a unifying view and choices of assumptions. Biostatistics. [arXiv] (also listed under Principal stratification)

Nguyen TQ, Stuart EA. (Accepted). Multiple imputation for propensity score analysis with covariates missing at random: some clarity on within and across methods. American Journal of Epidemiology. [arXiv] (also listed under Propensity score methods)

Nguyen TQ, Stuart EA. (2020). Propensity score analysis with latent covariates: Measurement error bias correction using the covariate’s posterior mean, aka the inclusive factor score. Journal of Educational and Behavioral Statistics. 45(5):598-636. [published] [arXiv] (also listed under Propensity score methods)

Principal stratification

Nguyen TQ, Stuart EA, Scharfstein DO, Ogburn EL. Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects. [arXiv] (also listed under Sensitivity analysis)

Propensity score methods

Chang T-H, Nguyen TQ, Lee Y, Jackson JW, Stuart EA. (2022). Flexible propensity score estimation strategies for clustered data in observational studies. Statistics in Medicine. [published]

Lee Y, Nguyen TQ, Stuart EA. (2021). Partially pooled propensity score models for average treatment effect estimation with multilevel data. Journal of the Royal Statistical Society: Series A. [published] [arXiv]

Dong N, Stuart EA, Lenis D, Nguyen TQ. (2020). Using propensity score analysis of survey data to estimate population average treatment effects: A case study comparing different methods. Evaluation Review. [published]

Lenis D, Nguyen TQ, Dong NB, Stuart EA. (2019). It’s all about balance: Propensity score matching in the context of complex survey data. Biostatistics. 20(1):147-163. [published]

Sensitivity analysis

Other

Nguyen TQ, Dafoe A, Ogburn EL. (2019). The magnitude and direction of collider bias for binary variables. Epidemiologic Methods. 8(1). [published] [arXiv]