In a prospective birth cohort study of 5295 girls from the UK-based Avon Longitudinal Study of Parents and Children (ALSPAC), we examined the association between biological father absence in childhood and age at menarche whilst adjusting for antenatal indicators of socioeconomic disadvantage and maternal characteristics. We also examined whether exposure to maternal depression and financial pro...

BACKGROUND Cognitive theories of depression suggest that beliefs of low self-worth and the tendency to attribute negative events to causes that are global (widespread rather than specific) and stable (will persist rather than change in the future) are associated with the development of depressed mood. Such theories are supported by evidence from prospective studies and have guided the developme...

Quantitative analysis of MR images is becoming increasingly important as a surrogate marker in clinical trials in multiple sclerosis (MS). This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel MR images. The method simultaneously corrects for MR eld inhomogeneities, estimates tissue class distribution parameters and classiies the image voxel...

Consider a set of 6 points in R × {0, 1}: {(−1, 1), (−1, 1), (−2, 1), (−3, 0), (−3, 0), (−3, 0)}, and suppose we are interested in Prec@1. Note that the optimum model that maximizes prec@1 on these points has a positive sign. We will now show that the model w∗ ∈ R that maximizes the above structural SVM surrogate on these points has a negative sign. On the contrary, let us assume that w∗ has a ...

Fourier surrogate data are artificially generated time series, that — based on a resampling scheme — share the linear properties with an observed time series. In this paper we study a statistical surrogate hypothesis test to detect deviations from a linear Gaussian process with respect to asymmetry in time (Q-statistic). We apply this test to a Fourier representable function and obtain a repres...

This article describes model-based methods for global optimization. After introducing the global optimization framework, modeling approaches for stochastic algorithms are presented. We differentiate between models that use a distribution and models that use an explicit surrogate model. Fundamental aspects of and recent advances in surrogate-model based optimization are discussed. Strategies for...

When carrying out design searches, traditional variable screening techniques can find it extremely difficult to distinguish between important and unimportant variables. This is particularly true when only a small number of simulations is combined with a parameterization which results in a large number of variables of seemingly equal importance. Here the authors present a variable reduction tech...

| The technique of surrogate data provides has been used to test for membership of particular classes of linear systems. Existing algorithms provide non-parametric methods to generate surrogates similar to the data and consistent with a given hypothesis. These non-parametric methods allow a wide range of test statistics to be utilized. We suggest an obvious extension of this to classes of nonli...