Selected Publications and Preprints

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

Methodology

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.” To appear in Statistical Methods in Medical Research. [link] [arXiv]

Spieker, A.J., Greevy, R., Nelson, L., and Mayberry, L. “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. [arXiv]

Spieker, A.J., Delaney, J.A.C, and McClelland, R.L. “Marginal estimation of biomarker age trends in longitudinal data with endogenous medication use.” Preprint: [arXiv]

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

Applications

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]

Software

uwIntroStats [CRAN]
endogenous [CRAN]