Michael Escobar

Bio: Michael Escobar is an academic researcher from University of Toronto. The author has contributed to research in topics: Traumatic brain injury & Medicine. The author has an hindex of 34, co-authored 83 publications receiving 8488 citations. Previous affiliations of Michael Escobar include St. Michael's Hospital & Centre for Addiction and Mental Health.

Bayesian Density Estimation and Inference Using Mixtures

Abstract: We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dirichlet processes. These models provide natural settings for density estimation and are exemplified by special cases where data are modeled as a sample from mixtures of normal distributions. Efficient simulation methods are used to approximate various prior, posterior, and predictive distributions. This allows for direct inference on a variety of practical issues, including problems of local versus global smoothing, uncertainty about density estimates, assessment of modality, and the inference on the numbers of components. Also, convergence results are established for a general class of normal mixture models.

Prevalence of reading disability in boys and girls. Results of the Connecticut Longitudinal Study.

Abstract: We hypothesized that results of previous investigations indicating an increased prevalence of reading disability in boys compared with girls reflected a bias in subject selection. In an epidemiologic sample of 215 girls and 199 boys, we identified two groups of reading-disabled children: research identified and school identified. Results indicated no significant differences in the prevalence of reading disability in research-identified boys compared with research-identified girls in either second (17 [8.7%] of 196 boys; 15 [6.9%] of 216 girls) or third grade (18 [9.0%] of 199 boys; 13 [6.0%] of 215 girls). In contrast, school identification resulted in the classification of 27 (13.6%) of 198 boys and seven (3.2%) of 216 girls in second grade and 20 (10.0%) of 199 boys and nine (4.2%) of 215 girls in third grade. Our data indicate that school-identified samples are almost unavoidably subject to a referral bias and that reports of an increased prevalence of reading disability in boys may reflect this bias in ascertainment. These findings caution against relying solely on schools for identification of reading-disabled children. (JAMA. 1990;264:998-1002)

Evidence That Dyslexia May Represent the Lower Tail of a Normal Distribution of Reading Ability

Abstract: Background Dyslexia is now widely believed to be a biologically based disorder that is distinct from other, less specific reading problems. According to this view, reading ability is considered to follow a bimodal distribution, with dyslexia as the lower mode. We hypothesized that, instead, reading ability follows a normal distribution, with dyslexia at the lower end of the continuum. Methods and Results We used data from the Connecticut Longitudinal Study, a sample survey of 414 Connecticut children who entered kindergarten in 1983 and were followed as a longitudinal cohort. Dyslexia was defined in terms of a discrepancy score, which represents the difference between actual reading achievement and achievement predicted on the basis of measures of intelligence. Data were available from intelligence tests administered in grades 1, 3, and 5 and achievement tests administered yearly in grades 1 through 6. For each child there were 108 possible discrepancy scores ([3 × 3 years] × [2 × 6 years]) based...

Estimating Normal Means with a Dirichlet Process Prior

Abstract: In this article, the Dirichlet process prior is used to provide a nonparametric Bayesian estimate of a vector of normal means. In the past there have been computational difficulties with this model. This article solves the computational difficulties by developing a “Gibbs sampler” algorithm. The estimator developed in this article is then compared to parametric empirical Bayes estimators (PEB) and nonparametric empirical Bayes estimators (NPEB) in a Monte Carlo study. The Monte Carlo study demonstrates that in some conditions the PEB is better than the NPEB and in other conditions the NPEB is better than the PEB. The Monte Carlo study also shows that the estimator developed in this article produces estimates that are about as good as the PEB when the PEB is better and produces estimates that are as good as the NPEB estimator when that method is better.

Fourteen-Year Follow-up of Speech/Language-Impaired and Control Children: Psychiatric Outcome

Abstract: Objective To examine the association between early childhood speech and language disorders and young adult psychiatric disorders. Method In a longitudinal community study conducted in the Ottawa-Carleton region of Ontario, Canada, interviewers administered structured psychiatric interviews to age 19 participants who were originally identified as speech-impaired only, language-impaired, or nonimpaired at age 5. The first stage of the study took place in 1982 when participants were 5 years old, and the latest stage of the study took place between 1995 and 1997 when participants had a mean age of 19 years. This report examines the association between early childhood speech/language status and young adult psychiatric outcome. Results Children with early language impairment had significantly higher rates of anxiety disorder in young adulthood compared with nonimpaired children. The majority of participants with anxiety disorders had a diagnosis of social phobia. Trends were found toward associations between language impairment and overall and antisocial personality disorder rates. Males from the language-impaired group had significantly higher rates of antisocial personality disorder compared with males from the control group. Age of onset and comorbidity did not differ by speech/language status. The majority of participants with a disorder had more than one. Conclusions Results support the association between early childhood speech and language functioning and young adult psychiatric disorder over a 14-year period. This association underscores the importance of effective and early interventions.

Inference of population structure using multilocus genotype data

Abstract: We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci— e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.

Using Multivariate Statistics

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From Neurons to Neighborhoods: The Science of Early Childhood Development

Abstract: How we raise young children is one of today's most highly personalized and sharply politicized issues, in part because each of us can claim some level of "expertise." The debate has intensified as discoveries about our development-in the womb and in the first months and years-have reached the popular media. How can we use our burgeoning knowledge to assure the well-being of all young children, for their own sake as well as for the sake of our nation? Drawing from new findings, this book presents important conclusions about nature-versus-nurture, the impact of being born into a working family, the effect of politics on programs for children, the costs and benefits of intervention, and other issues. The committee issues a series of challenges to decision makers regarding the quality of child care, issues of racial and ethnic diversity, the integration of children's cognitive and emotional development, and more. Authoritative yet accessible, From Neurons to Neighborhoods presents the evidence about "brain wiring" and how kids learn to speak, think, and regulate their behavior. It examines the effect of the climate-family, child care, community-within which the child grows.

Model-Based Clustering, Discriminant Analysis, and Density Estimation

Abstract: Cluster analysis is the automated search for groups of related observations in a dataset. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures, and most clustering methods available in commercial software are also of this type. However, there is little systematic guidance associated with these methods for solving important practical questions that arise in cluster analysis, such as how many clusters are there, which clustering method should be used, and how should outliers be handled. We review a general methodology for model-based clustering that provides a principled statistical approach to these issues. We also show that this can be useful for other problems in multivariate analysis, such as discriminant analysis and multivariate density estimation. We give examples from medical diagnosis, minefield detection, cluster recovery from noisy data, and spatial density estimation. Finally, we mention limitations of the methodology and discuss recent development...

Handbook of positive psychology

Abstract: Psychology has long been enamored of the dark side of human existence, rarely exploring a more positive view of the mind. What has psychology contributed, for example, to our understanding of the various human virtues? Regrettably, not much. The last decade, however, has witnessed a growing movement to abandon the exclusive focus on the negative. Psychologists from several subdisciplines are now asking an intriguing question: "What strengths does a person employ to deal effectively with life?" The Handbook of Positive Psychology provides a forum for a more positive view of the human condition. In its pages, readers are treated to an analysis of what the foremost experts believe to be the fundamental strengths of humankind. Both seasoned professionals and students just entering the field are eager to grasp the power and vitality of the human spirit as it faces a multitude of life challenges. The Handbook is the first systematic attempt to bring together leading scholars to give voice to the emerging field of positive psychology.