Selected Publications and Preprints

Below is a list of selected publications and preprints. For a complete list, please see my full CV [link].


Spieker, A.J., Delaney, J.A.C., and McClelland,R.L. (2015). “Evaluating the treatment effects model for estimation of cross-sectional associations between risk factors and cardiovascular biomarkers influenced by medication use.” Pharmacoepidemiology and Drug Safety, 24(12), 1286-1296. [link]

Spieker, A.J. and Huang, Y. (2017). “A method to address between-subject heterogeneity for identification of principal surrogate markers in repeated low-dose challenge HIV vaccine studies.” Statistics in Medicine, 36(26), 4167-4181. [link]

Spieker, A.J., Roy, J.A., and Mitra, N. (2018). “Analyzing medical costs with time-dependent treatment: The nested g-formula.” Health Economics, 27(7), 1063-1073. [link]

Spieker, A.J., Delaney, J.A.C., and McClelland,R.L. (2018). “A method to account for covariate- specific treatment effects when estimating biomarker associations in the presence of endogenous medication use.” Statistical Methods in Medical Research, 27(8), 2279-2293. [link]

Spieker, A.J., Ko, E., Roy, J.A., and Mitra, N. (2020). “Nested g-computation: a causal approach to analysis of censored medical costs in the presence of time-varying treatment.” Journal of the Royal Statistical Society, Series C, 69(5), 1189-1208. [link] [arXiv]

Spieker, A.J., Illenberger, N., Roy, J., Mitra, N. (2021). “Net benefit separation and the determination curve: a probabilistic framework for cost-effectiveness estimation.” Statistical Methods in Medical Research, 30(5), 1306-1319. [link] [arXiv]

Spieker, A.J., Delaney, J.A.C, and McClelland, R.L. (2021) “Semi-parametric estimation of biomarker age trends with endogenous medication use in longitudinal data.” Observational Studies, 7, 127-147. [link] [arXiv]

Spieker, A.J., Greevy, R., Nelson, L., and Mayberry, L. (2021) “Bounding the local average treatment effect in an instrumental variable analysis of engagement with a mobile intervention.” To appear in The Annals of Applied Statistics. Preprint: [arXiv]

Illenberger, N., Mitra, N., and Spieker, A.J. “A regression framework for a probabilistic measure of cost-effectiveness.” Preprint: [arXiv]

Illenberger, N., Spieker, A.J., and Mitra, N. “Identifying optimally cost-effective dynamic treatment regimes with a Q-learning approach.” Preprint: [arXiv]


Wang, L., Spieker, A.J., Li, J., and Rutkove, S.B. (2011). “Electrical impedance myography for monitoring motor neuron loss in the SOD1 G93A amyotrophic lateral sclerosis rat.” Clinical Neurophysiology 122(12), 2505-2511. [PubMed]

Spieker, A.J., Narayanaswami, P., Fleming, L., Keel, J.C., Muzin, S.C., and Rutkove, S.B. (2013). “Electrical impedance myography in the diagnosis of radiculopathy.” Muscle and Nerve 48(5), 800-805. [PubMed]

Hsi, R.S., Spieker, A.J., Stoller, M.L., Jacobs, D.R., Jr., Reiner, A.P., McClelland, R.L., Kahn, A.J., Chi, T., Szklo, M., and Sorensen, M.D. (2015). “Coronary artery calcium score and association with recurrent nephrolithiasis: the Multi-Ethnic Study of Atherosclerosis.” Journal of Urology 195(4), 971-976. [PubMed]

Nelson, L.A., Spieker A.J., Greevy, R., LeStourgeon, L.M., Wallston, K.A., and Mayberry, L.S. (2020). “User engagement remains high among diverse adults during a 12-month text message-delivered diabetes support intervention.” JMIR mHealth and uHealth, 8(7), e17534. [PubMed]

Invited commentaries

Spieker, A.J. “Comment on `Penalized Spline of Propensity Methods for Treatment Comparison’ by Zhou, Elliott, and Little.” (2019). Journal of the American Statistical Association. 114(S25), 20-23. [link]


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