Respiratory health and air pollution: additive mixed model analyses.

We conduct a reanalysis of data from the Utah Valley respiratory health/air pollution study of Pope and co-workers (Pope et al., 1991) using additive mixed models. A relatively recent statistical development (e.g. Wang, 1998; Verbyla et al., 1999; Lin and Zhang, 1999), the methods allow for smooth functional relationships, subject-specific effects and time series error structure. All three of these are apparent in the Utah Valley data.

[1]  J. Goldsmith,et al.  AIR POLLUTION AND DAILY MORTALITY , 1961, The American journal of the medical sciences.

[2]  A S Whittemore,et al.  Methods for analyzing panel studies of acute health effects of air pollution. , 1979, Biometrics.

[3]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[4]  K. Liang,et al.  Asymptotic Properties of Maximum Likelihood Estimators and Likelihood Ratio Tests under Nonstandard Conditions , 1987 .

[5]  M. Tockman,et al.  Analysis of spirometric data from a national sample of healthy 6- to 24-year-olds (NHANES II). , 1988, The American review of respiratory disease.

[6]  Christine Waternaux,et al.  Methods for Analysis of Longitudinal Data: Blood-Lead Concentrations and Cognitive Development , 1989 .

[7]  G. Robinson.  [That BLUP is a Good Thing: The Estimation of Random Effects]: Rejoinder , 1991 .

[8]  J D Spengler,et al.  Respiratory health and PM10 pollution. A daily time series analysis. , 1991, The American review of respiratory disease.

[9]  D. Dockery,et al.  Daily diaries of respiratory symptoms and air pollution: methodological issues and results. , 1991, Environmental health perspectives.

[10]  G. Robinson.  That BLUP is a Good Thing: The Estimation of Random Effects , 1991 .

[11]  Sensitive subgroups and normal variation in pulmonary function response to air pollution episodes. , 1991, Environmental health perspectives.

[12]  J Schwartz,et al.  Air pollution and daily mortality in Birmingham, Alabama. , 1993, American journal of epidemiology.

[13]  Joel Schwartz,et al.  Nonparametric smoothing in the analysis of air pollution and respiratory illness , 1994 .

[14]  P. Diggle,et al.  Semiparametric models for longitudinal data with application to CD4 cell numbers in HIV seroconverters. , 1994, Biometrics.

[15]  S. T. Buckland,et al.  An Introduction to the Bootstrap. , 1994 .

[16]  J M Taylor,et al.  Inference for smooth curves in longitudinal data with application to an AIDS clinical trial. , 1995, Statistics in medicine.

[17]  N. Altman,et al.  Nonparametric Empirical Bayes Growth Curve Analysis , 1995 .

[18]  P. Diggle.  Analysis of Longitudinal Data , 1995 .

[19]  D. Ruppert,et al.  Measurement Error in Nonlinear Models , 1995 .

[20]  D. Dockery,et al.  The association of ambient air pollution with twice daily peak expiratory flow rate measurements in children. , 1995, American journal of epidemiology.

[21]  R H Jones,et al.  Smoothing splines for longitudinal data. , 1995, Statistics in medicine.

[22]  Paul H. C. Eilers,et al.  Flexible smoothing with B-splines and penalties , 1996 .

[23]  R A Betensky,et al.  Local estimation of smooth curves for longitudinal data. , 1997, Statistics in medicine.

[24]  J. Rice,et al.  Smoothing spline models for the analysis of nested and crossed samples of curves , 1998 .

[25]  Yuedong Wang.  Smoothing Spline Models with Correlated Random Errors , 1998 .

[26]  J. Raz,et al.  Semiparametric Stochastic Mixed Models for Longitudinal Data , 1998 .

[27]  M. Kenward,et al.  The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines , 1999 .

[28]  X. Lin,et al.  Inference in generalized additive mixed modelsby using smoothing splines , 1999 .

[29]  A. Bowman,et al.  Applied smoothing techniques for data analysis : the kernel approach with S-plus illustrations , 1999 .

[30]  Thomas S. Shively,et al.  Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior , 1999 .

[31]  V. Hasselblad,et al.  Assessment of human exposure to ambient particulate matter. , 1999, Journal of the Air & Waste Management Association.

[32]  S L Zeger,et al.  Exposure measurement error in time-series studies of air pollution: concepts and consequences. , 2000, Environmental health perspectives.

[33]  J. Sarnat,et al.  Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore, MD , 2000, Journal of the Air & Waste Management Association.

[34]  David Ruppert,et al.  Theory & Methods: Spatially‐adaptive Penalties for Spline Fitting , 2000 .

[35]  J. Schwartz,et al.  Patients with chronic obstructive pulmonary disease are at increased risk of death associated with urban particle air pollution: a case-crossover analysis. , 2000, American journal of epidemiology.

[36]  J. Vandenberg,et al.  Research priorities: airborne particulate matter , 2001 .

[37]  V. Carey,et al.  Mixed-Effects Models in S and S-Plus , 2001 .

[38]  M. Wand,et al.  Incorporation of historical controls using semiparametric mixed models , 2001 .

[39]  Karl J. Friston,et al.  Variance Components , 2003 .