Efficiency and Consistency for Regularization Parameter Selection in Penalized Regression: Asymptotics and Finite-Sample Corrections

This paper studies the asymptotic and nite-sample performance of penalized regression methods when different selectors of the regularization parameter are used under the assumption that the true model is, or is not, included among the candidate model. In the latter setting, we relax assumptions in the existing theory to show that several classical information criteria are asymptotically efficient selectors of the regularization parameter. In both settings, we assess the nite-sample performance of these as well as other common selectors and demonstrate that their performance can suffer due to sensitivity to the number of variables that are included in the full model. As alternatives, we propose two corrected information criteria which are shown to outperform the existing procedures while still maintaining the desired asymptotic properties. In the non-true model world, we relax the assumption made in the literature that the true error variance is known or that a consistent estimator is available to prove that Akaike's information criterion (AIC), Cp and Generalized cross-validation (GCV) themselves are asymptotically efficient selectors of the regularization parameter and we study their performance in nite samples. In classical regression, AIC tends to select overly complex models when the dimension of the maximum candidate model is large relative to the sample size. Simulation studies suggest that AIC suffers from the same shortcomings when used in penalized regression. We therefore propose the use of the classical AICc as an alternative. In the true model world, a similar investigation into the nite sample properties of BIC reveals analogous overfitting tendencies and leads us to further propose the use of a corrected BIC (BICc). In their respective settings (whether the true model is, or is not, among the candidate models), BICc and AICc have the desired asymptotic properties and we use simulations to assess their performance, as well as that of other selectors, in nite samples for penalized regressions fit using the Smoothly clipped absolute deviation (SCAD) and Least absolute shrinkage and selection operator (Lasso) penalty functions. We nd that AICc and 10-fold cross-validation outperform the other selectors in terms of squared error loss, and BICc avoids the tendency of BIC to select overly complex models when the dimension of the maximum candidate model is large relative to the sample size.NYU Stern School of BusinessStatistics Working Papers Serie

Measles vaccination and antibody response in autism spectrum disorder

OBJECTIVE: To test the hypothesis that measles vaccination was involved in the pathogenesis of autism spectrum disorders (ASD) as evidenced by signs of a persistent measles infection or abnormally persistent immune response shown by circulating measles virus or raised antibody titres in children with ASD who had been vaccinated against measles, mumps and rubella (MMR) compared with controls. DESIGN: Case-control study, community based. METHODS: A community sample of vaccinated children aged 10-12 years in the UK with ASD (n = 98) and two control groups of similar age, one with special educational needs but no ASD (n = 52) and one typically developing group (n = 90), were tested for measles virus and antibody response to measles in the serum. RESULTS: No difference was found between cases and controls for measles antibody response. There was no dose-response relationship between autism symptoms and antibody concentrations. Measles virus nucleic acid was amplified by reverse transcriptase-PCR in peripheral blood mononuclear cells from one patient with autism and two typically developing children. There was no evidence of a differential response to measles virus or the measles component of the MMR in children with ASD, with or without regression, and controls who had either one or two doses of MMR. Only one child from the control group had clinical symptoms of possible enterocolitis. CONCLUSION: No association between measles vaccination and ASD was shown

Influence of Substrates on the Long-Range Order of Photoelectrodeposited Se-Te Nanostructures

The long-range order of anisotropic phototropic Se–Te films grown electrochemically at room temperature under uniform-intensity, polarized, incoherent, near-IR illumination has been investigated using crystalline (111)-oriented Si substrates doped degenerately with either p- or n-type dopants. Fourier-transform (FT) analysis was performed on large-area images obtained with a scanning electron microscope, and peak shapes in the FT spectra were used to determine the pattern fidelity in the deposited Se–Te films. Under nominally identical illumination conditions, phototropic films grown on p^+-Si(111) exhibited a higher degree of anisotropy and a more well-defined pattern period than phototropic films grown on n+-Si(111). Similar differences in the phototropic Se–Te deposit morphology and pattern fidelity on p^+-Si versus n^+-Si were observed when the deposition rate and current densities were controlled for by adjusting the deposition parameters and illumination conditions. The doping-related effects of the Si substrate on the pattern fidelity of the phototropic Se–Te deposits are ascribable to an electrical effect produced by the different interfacial junction energetics between Se–Te and p^+-Si versus n^+-Si that influences the dynamic behavior during phototropic growth at the Se–Te/Si interface

Child educational progress in Born in Bradford pregnancies affected by gestational diabetes and also exposed to maternal common mental disorders

Abstract Gestational diabetes and the maternal mental disorders of anxiety and depression have been implicated in adverse offspring neuro-behavioural outcomes but these exposures have only been studied in isolation. 1051 children whose mothers were diagnosed with gestational diabetes in UK’s Born in Bradford cohort had linkage to maternal primary care records, providing diagnostic and treatment codes for depression and anxiety. Education record linkage provided results of the Early Years Foundation Stage Profile from the first year of school, aged five. Risk of not attaining a ‘Good level of development’ was analysed using multivariable Poisson regression within a generalised estimating equation framework. Multiple imputation was implemented for missing data. There was limited evidence of increased risk of failure to attain a ‘good level of development’ in those additionally exposed to maternal mental disorders (adjusted RR 1.21; 95% CI 0.94, 1.55). However, there was more evidence in children of Pakistani maternal ethnicity (adjusted RR 1.36; 95% CI 1.04, 1.77) than White British; this may have been driven by English not being the primary language spoken in the home. Therefore there may be groups with GDM in whom it is particularly important to optimise both maternal physical and mental health to improve child outcomes

Comparaison des sections efficaces des réactions (p, n) et (p, pn) induites sur le thorium par des protons de 30 à 150 MeV

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Clinical predictors of antipsychotic use in children and adolescents with autism spectrum disorders: a historical open cohort study using electronic health records.

JOURNAL ARTICLEThe final publication is available at Springer via http://dx.doi.org/ 10.1007/s00787-015-0780-7Children with autism spectrum disorders (ASD) are more likely to receive antipsychotics than any other psychopharmacological medication, yet the psychiatric disorders and symptoms associated with treatment are unclear. We aimed to determine the predictors of antipsychotic use in children with ASD receiving psychiatric care. The sample consisted of 3482 children aged 3-17 with an ICD-10 diagnosis of ASD referred to mental health services between 2008 and 2013. Antipsychotic use outcome, comorbid diagnoses, and other clinical covariates, including challenging behaviours were extracted from anonymised patient records. Of the 3482 children (79 % male) with ASD, 348 (10 %) received antipsychotic medication. The fully adjusted model indicated that comorbid diagnoses including hyperkinetic (OR 1.44, 95 %CI 1.01-2.06), psychotic (5.71, 3.3-10.6), depressive (2.36, 1.37-4.09), obsessive-compulsive (2.31, 1.16-4.61) and tic disorders (2.76, 1.09-6.95) were associated with antipsychotic use. In addition, clinician-rated levels of aggression, self-injurious behaviours, reduced adaptive function, and overall parental concern for their child's presenting symptoms were significant risk factors for later antipsychotic use. In ASD, a number of comorbid psychiatric disorders are independent predictors for antipsychotic treatment, even after adjustment for familial, socio-demographic and individual factors. As current trial evidence excludes children with comorbidity, more pragmatic randomised controlled trials with long-term drug monitoring are needed.NIHRBiomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and King’s College LondonGuy’s and St. Thomas’ CharityMaudsley CharityMR