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Time-varying coefficient cumulative gap time models for intensive longitudinal ecological momentary assessment data with missingness

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Pages 498-521 | Received 04 Mar 2020, Accepted 21 Aug 2020, Published online: 03 Sep 2020

References

  • N. Benowitz, Nicotine addiction, N. Engl. J. Med. 362 (2010), pp. 2295–2203. doi: 10.1056/NEJMra0809890
  • B. Brumback and J.A. Rice, Smoothing spline models for the analysis of nested and crossed samples of curves, J. Am. Stat. Assoc. 93 (1998), pp. 961–994. doi: 10.1080/01621459.1998.10473755
  • Centers for Disease Control and Prevention, Prevalence of current cigarette smoking among adults and changes in prevalence of current and some day smoking-Uniteed States, 1996–2001, Morbidity Mortality Weekly Report 52 (2003), pp. 303–307.
  • Centers for Disease Control and Prevention, Behavioral risk factor surveillance system survey data. Atlanta, GA: U.S. Department of Health and Human Services. (2008a).
  • Centers for Disease Control and Prevention, Cigarette smoking among adults-United States, 2007, Morbidity Mortality Weekly Report 57 (2008b), pp. 1221–1226.
  • Centers for Disease Control and Prevention, Centers for disease control and prevention [Internet]. Behavioral risk factor surveillance system survey data. Atlanta: U.S. Department of Health and Human Services. (c2012). Available at http://apps.nccd.cdc.gov/brfss/.
  • L. Duchateau and P. Janssen, The Frailty Model, Springer, New York, 2008. pp. 30–31.
  • T. Hastie and R. Tibshirani, Varying-coefficients models, J. R. Stat. Soc. Ser. B 55 (1993), pp. 757–796.
  • D.R. Hoover, C.O. Wu, and L.P. Yang, Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data, Biometrika 85 (1998), pp. 809–822. doi: 10.1093/biomet/85.4.809
  • T.W. Kamarck, J.E. Schwartz, S. Shiffman, M.F. Muldoon, K. Sutton-Tyrrell, and D.L. Janicki, Psychosocial stress and cardiovascular risk: what is the role of daily experience? J. Personality 73 (2005), pp. 1749–1774. doi: 10.1111/j.0022-3506.2005.00365.x
  • H. Liang, H. Wu, and R.J. Carroll, The relationship between virologic and immunologic responses in AIDS clinical research using mixed-effects varying-coefficient semiparametric models with measurement error, Biostatistics 4 (2003), pp. 297–312. doi: 10.1093/biostatistics/4.2.297
  • J.A. Paty, J.D. Kassel, and S. Shiffman, Assessing stimulus control of smoking: the importance of base rates. In: De Vries H, editor. The Experience of Psychopathology. Cambridge: Cambridge University Press, 1992.
  • S.L. Rathbun, S. Shiffman, and C. Gwaltney, Modeling the effects of partially observed covariates on Poisson process intensity, Biometrika 94 (2007), pp. 153–165. doi: 10.1093/biomet/asm009
  • S. Shiffman, Ecological momentary assessment (EMA) in studies of substance abuse, Psychol. Assessment 21 (2009), pp. 486–497. doi: 10.1037/a0017074
  • S. Shiffman, M. Dunbar, X. Li, S. School, H. Tindle, S. Anderson, and S. Ferguson, Craving in intermittent and daily smokers during ad libitum smoking. Nicotine and Tobacco Res. 16 (2014), pp. 1063–1069. doi: 10.1093/ntr/ntu023
  • S. Shiffman, A.A. Stone, and M.R. Hufford, Ecological momentary assessment, Annu. Rev. Clin. Psychol. 4 (2008), pp. 1–32. doi: 10.1146/annurev.clinpsy.3.022806.091415
  • S. Shiffman, H. Tindle, X. Li, S. Scholl, M. Dunbar, and C. Mitchell-Miland, Characteristics and smoking patterns of intermittent smokers, Exp. Clin. Psychopharmacol. 20 (2012), pp. 264–277. doi: 10.1037/a0027546
  • A.A. Stone and S. Shiffman, Ecological momentary assessment (EMA) in behavioral medicine, Ann. Behav. Med. 16 (1994), pp. 199–202. doi: 10.1093/abm/16.3.199
  • Substance Abuse and Mental Health Services Administration, Substance abuse and mental health services administration [Internet]. Rockville (MD): Results from the 2012 National Survey on Drug Use and Health: National Findings. (c2013). Available at http://www.samhsa.gov/data/NSDUH/2012SummNatFindDetTables/DetTabs/NSDUH-DetTabsSect6peTabs1to54-2012.htm.
  • X. Tan, R. Li, Y. Li, and L. Dierker, A time-varying effect model for intensive longitudinal data, Psychol. Methods 17 (2012), pp. 61–77. doi: 10.1037/a0025814
  • M. West, P.J. Harrison, and H.S. Migon, Dynamic generalized linear models and Bayesian forecasing, J. Am. Stat. Assoc. 80 (1985), pp. 73–83. doi: 10.1080/01621459.1985.10477131
  • H. Wu and H. Liang, Backfitting random varying-coefficient models with time-dependent smoothing covariates, Scandinavian Statist. 31 (2004), pp. 3–19. doi: 10.1111/j.1467-9469.2004.00369.x
  • H. Wu and J. Zhang, Nonparametric Regression Methods for Longitudinal Data Analysis, Wiley-Interscience, Hoboken, NJ, 2006. pp. 300–302.

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