Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it - an improved and generalized version of Bayesian Blocks (Scargle 1998) - that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multi-variate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by (Arias-Castro, Donoho and Huo 2003). In the spirit of Reproducible Research (Donoho et al. 2008) all of the code and data necessary to reproduce all of the figures in this paper are included as auxiliary material.Comment: Added some missing script files and updated other ancillary data (code and data files). To be submitted to the Astophysical Journa

Pre-validation and inference in microarrays

In microarray studies, an important problem is to compare a predictor of disease outcome derived from gene expression levels to standard clinical predictors. Comparing them on the same dataset that was used to derive the microarray predictor can lead to results strongly biased in favor of the microarray predictor. We propose a new technique called ``pre-validation'' for making a fairer comparison between the two sets of predictors. We study the method analytically and explore its application in a recent study on breast cancer.

A Survey of Complex Object Technologies for Digital Libraries

Many early web-based digital libraries (DLs) had implicit assumptions reflected in their architecture that the unit of focus in the DL (frequently "reports" or "e-prints") would only be manifested in a single, or at most a few, common file formats such as PDF or PostScript. DLs have now matured to the point where their contents are commonly no longer simple files. Complex objects in DLs have emerged in response to various requirements, including: simple aggregation of formats and supporting files, bundling additional information to aid digital preservation, creating opaque digital objects for e-commerce applications, and the incorporation of dynamic services with the traditional data files. We examine a representative (but not necessarily exhaustive) number of current and recent historical web-based complex object technologies and projects that are applicable to DLs: Aurora, Buckets, ComMentor, Cryptolopes, Digibox, Document Management Alliance, FEDORA, Kahn-Wilensky Framework Digital Objects, Metadata Encoding & Transmission Standard, Multivalent Documents, Open eBooks, VERS Encapsulated Objects, and the Warwick Framework

Association between autism symptoms and family functioning in children with attention-deficit/hyperactivity disorder: a community-based study

Autism spectrum disorder (ASD) symptoms are elevated in populations of children with attention-deficit/hyperactivity disorder (ADHD). This study examined cross-sectional associations between ASD symptoms and family functioning in children with and without ADHD. Participants were recruited to a longitudinal cohort study, aged 6-10 years (164 ADHD; 198 controls). ADHD cases were ascertained using community-based screening and diagnostic confirmation from a diagnostic interview. ASD symptoms were measured using the Social Communication Questionnaire. Outcome variables were parent mental health, family quality of life (FQoL), couple conflict and support, and parenting behaviours. After adjustment for a range of child and family factors (including other mental health comorbidities), higher ASD symptoms were associated with poorer FQoL across all three domains; emotional impact (p = 0.008), family impact (p = 0.001) and time impact (p = 0.003). In adjusted analyses by subgroup, parents of children with ADHD+ASD had poorer parent self-efficacy (p = 0.01), poorer FQoL (p ≤ 0.05), with weak evidence of an association for less couple support (p = 0.06), compared to parents of children with ADHD only. Inspection of covariates in the adjusted analyses indicated that the association between ASD symptoms and most family functioning measures was accounted forby child internalising and externalising disorders, ADHD severity, and socioeconomic status; however, ASD symptoms appear to be independently associated with poorer FQoL in children with ADHD. The presence of ASD symptoms in children with ADHD may signal the need for enhanced family support

Trauma exposure in children with and without ADHD: prevalence and functional impairment in a community-based study of 6–8-year-old Australian children

Both ADHD and trauma exposure are common childhood problems, but there are few empirical data regarding the association between the two conditions. The aims of this study were to compare lifetime prevalence of trauma exposure in children with and without ADHD, and to explore the association between trauma exposure and outcomes in children with ADHD. Children aged 6-8 years with ADHD (n = 179) and controls (n = 212) recruited from 43 schools were assessed for ADHD, trauma exposure and comorbid mental health disorders using the Diagnostic Interview Schedule for Children IV. Outcome data were collected by direct child assessment, parent report and teacher-report, and included ADHD symptom severity, internalizing and externalizing problems, quality of life, and academic functioning. Logistic and linear regression models were used to examine differences adjusted for child and family socio-demographics. Children with ADHD were more likely than controls to have ever experienced a traumatic event (27 vs 16%; OR: 1.99; 95% CI 1.21, 3.27). This difference remained significant in the adjusted model (OR: 1.76, 95% CI 1.03, 3.01) accounting for child factors (age and gender) and family socio-demographic factors (parent age, parent high school completion and single parent status). Among those with ADHD, trauma-exposed children had higher parent-reported ADHD severity and more externalizing problems than non-exposed children, however, this effect attenuated in adjusted model. Children with ADHD were more likely to have experienced a traumatic event than controls. The high prevalence of trauma exposure in our sample suggests that clinicians should evaluate for trauma histories in children presenting with ADHD