@article {814,
	title = {Longitudinal scalar-on-functions regression with application to tractography data.},
	journal = {Biostatistics},
	volume = {14},
	year = {2013},
	month = {2013 Jul},
	pages = {447-61},
	abstract = {<p>We propose a class of estimation techniques for scalar-on-function regression where both outcomes and functional predictors may be observed at multiple visits. Our methods are motivated by a longitudinal brain diffusion tensor imaging tractography study. One of the study{\textquoteright}s primary goals is to evaluate the contemporaneous association between human function and brain imaging over time. The complexity of the study requires the development of methods that can simultaneously incorporate: (1) multiple functional (and scalar) regressors; (2) longitudinal outcome and predictor measurements per patient; (3) Gaussian or non-Gaussian outcomes; and (4) missing values within functional predictors. We propose two versions of a new method, longitudinal functional principal components regression (PCR). These methods extend the well-known functional PCR and allow for different effects of subject-specific trends in curves and of visit-specific deviations from that trend. The new methods are compared with existing approaches, and the most promising techniques are used for analyzing the tractography data.</p>},
	keywords = {Anisotropy, Biostatistics, Brain, Diffusion Tensor Imaging, Humans, Linear Models, Models, Statistical, Multiple Sclerosis, Principal Component Analysis, Regression Analysis},
	issn = {1468-4357},
	doi = {10.1093/biostatistics/kxs051},
	author = {Gertheiss, Jan and Goldsmith, Jeff and Crainiceanu, Ciprian and Greven, Sonja}
}
@article {708,
	title = {Arsenic exposure, diabetes prevalence, and diabetes control in the Strong Heart Study.},
	journal = {Am J Epidemiol},
	volume = {176},
	year = {2012},
	month = {2012 Nov 15},
	pages = {865-74},
	abstract = {<p>This study evaluated the association of arsenic exposure, as measured in urine, with diabetes prevalence, glycated hemoglobin, and insulin resistance in American Indian adults from Arizona, Oklahoma, and North and South Dakota (1989-1991). We studied 3,925 men and women 45-74 years of age with available urine arsenic measures. Diabetes was defined as a fasting glucose level of 126 mg/dL or higher, a 2-hour glucose level of 200 mg/dL or higher, a hemoglobin A1c (HbA1c) of 6.5\% or higher, or diabetes treatment. Median urine arsenic concentration was 14.1 {\textmu}g/L (interquartile range, 7.9-24.2). Diabetes prevalence was 49.4\%. After adjustment for sociodemographic factors, diabetes risk factors, and urine creatinine, the prevalence ratio of diabetes comparing the 75th versus 25th percentiles of total arsenic concentrations was 1.14 (95\% confidence interval: 1.08, 1.21). The association between arsenic and diabetes was restricted to participants with poor diabetes control (HbA1c >=8\%). Arsenic was positively associated with HbA1c levels in participants with diabetes. Arsenic was not associated with HbA1c or with insulin resistance (assessed by homeostatic model assessment to quantify insulin resistance) in participants without diabetes. Urine arsenic was associated with diabetes control in a population from rural communities in the United States with a high burden of diabetes. Prospective studies that evaluate the direction of the relation between poor diabetes control and arsenic exposure are needed.</p>},
	keywords = {Aged, Arizona, Arsenicals, Blood Glucose, Creatinine, Diabetes Mellitus, Environmental Exposure, Female, Hemoglobin A, Glycosylated, Humans, Indians, North American, Male, Middle Aged, North Dakota, Oklahoma, Poisson Distribution, Prevalence, Regression Analysis, Risk Factors, South Dakota},
	issn = {1476-6256},
	doi = {10.1093/aje/kws153},
	author = {Gribble, Matthew O and Howard, Barbara V and Umans, Jason G and Shara, Nawar M and Francesconi, Kevin A and Goessler, Walter and Crainiceanu, Ciprian M and Silbergeld, Ellen K and Guallar, Eliseo and Navas-Acien, Ana}
}
