An alternative approach for construction of strata using quantified sensitivity level

The study is investigated on an alternative method for the construction of strata using sensitivity level when the samples are selected with simple random sampling with replacement (SRSWR) and the data are collected by scrambled optional randomization technique on the sensitive characters. Thus, the optional randomized response model , where k is a random variable having value 1 if the response is scrambled and 0 otherwise, was considered for finding out Approximate Optimum Strata Boundaries by minimizing the variance of the estimator  . The cum.   was proposed for finding out Approximate Optimum Strata Boundary in Neyman allocation for the optional scrambled response. This is applicable for wider classes of sampling design and estimators in stratification. The proposed rule on optional scrambled randomized response is efficient and can be used effectively for the construction of optimum strata boundary via Rectangular, Right triangular and Exponential distribution. 

RRTCS: An R Package for Randomized Response Techniques in Complex Surveys

Randomized response (RR) techniques may be used to compile more reliable data, to protect the respondent's confidentiality, and to avoid an unacceptable rate of nonresponse when the information requested is sensitive (e.g., concerning racism, drug use, abortion, delinquency, AIDS, or academic cheating). Standard RR methods are used primarily in surveys that require a binary response to a sensitive question, and seek to estimate the proportion of people presenting a given (sensitive) characteristic. Nevertheless, some studies have addressed situations in which the response to a sensitive question results in a quantitative variable. RR methods are usually developed assuming that the sample is obtained using simple random sampling. However, in practice, most surveys are complex and involve stratification, clustering, and an unequal probability of selection of the sample. Data from complex survey designs require special consideration with regard to the estimation of finite population parameters and to the corresponding variance estimation procedures, due to the reality of significant departures from the simple random sampling assumption. In such a complex survey design, unbiased variance estimation is not easy to calculate, because of clustering and the involvement of (generally complex) second-order inclusion probabilities. In view of these considerations, a new computer program has been developed to provide a method for estimating the parameters of sensitive characteristics under a variety of complex sampling designs

Parameter estimation in the presence of auxiliary information

Dissertação para obtenção do Grau de Doutora em Estatística e Gestão de Risco, Especialidade em EstatísticaIn survey research, there are many situations when the primary variable of interest is sensitive. The sensitivity of some queries can give rise to a refusal to answer or to false answers given intentionally. Survey can be conducted in a variety of settings, in part dictated by the mode of data collection, and these settings can differ in how much privacy they offer the respondent. The estimates obtained from a direct survey on sensitive questions would be subject to high bias. A variety of techniques have been used to improve reporting by increasing the privacy of the respondents. The Randomized Response Technique (RRT), introduced byWarner in 1965, develops a random relation between the individual’s response and the question. This technique provides confidentiality to respondents and still allows the interviewers to estimate the characteristic of interest at an aggregate level. In this thesis we propose some estimators to improve the mean estimation of a sensitive variable based on a RRT by making use of available non-sensitive auxiliary information. In the first part of this thesis we present the ratio and the regression estimators as well as some generalizations in order to study the gain in the estimation over the ordinary RRT mean estimator. In chapters 4 and 5 we study the performance of some exponential type estimators, also based on a RRT. The final part of the thesis illustrates an approach to mean estimation in stratified sampling. This study confirms some previous results for a different sample design. An extensive simulation study and an application to a real dataset are done for all the study estimators to evaluate their performance. In the last chapter we present a general discussion referring to the main results and conclusions as well as showing an application to a real dataset which compares the performance of study estimators

Multiprocess parallel antithetic coupling for backward and forward Markov Chain Monte Carlo

Antithetic coupling is a general stratification strategy for reducing Monte Carlo variance without increasing the simulation size. The use of the antithetic principle in the Monte Carlo literature typically employs two strata via antithetic quantile coupling. We demonstrate here that further stratification, obtained by using k>2 (e.g., k=3-10) antithetically coupled variates, can offer substantial additional gain in Monte Carlo efficiency, in terms of both variance and bias. The reason for reduced bias is that antithetically coupled chains can provide a more dispersed search of the state space than multiple independent chains. The emerging area of perfect simulation provides a perfect setting for implementing the k-process parallel antithetic coupling for MCMC because, without antithetic coupling, this class of methods delivers genuine independent draws. Furthermore, antithetic backward coupling provides a very convenient theoretical tool for investigating antithetic forward coupling. However, the generation of k>2 antithetic variates that are negatively associated, that is, they preserve negative correlation under monotone transformations, and extremely antithetic, that is, they are as negatively correlated as possible, is more complicated compared to the case with k=2. In this paper, we establish a theoretical framework for investigating such issues. Among the generating methods that we compare, Latin hypercube sampling and its iterative extension appear to be general-purpose choices, making another direct link between Monte Carlo and quasi Monte Carlo.Comment: Published at http://dx.doi.org/10.1214/009053604000001075 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Serotonin transporter gene polymorphisms and brain function during emotional distraction from cognitive processing in posttraumatic stress disorder

BACKGROUND: Serotonergic system dysfunction has been implicated in posttraumatic stress disorder (PTSD). Genetic polymorphisms associated with serotonin signaling may predict differences in brain circuitry involved in emotion processing and deficits associated with PTSD. In healthy individuals, common functional polymorphisms in the serotonin transporter gene (SLC6A4) have been shown to modulate amygdala and prefrontal cortex (PFC) activity in response to salient emotional stimuli. Similar patterns of differential neural responses to emotional stimuli have been demonstrated in PTSD but genetic factors influencing these activations have yet to be examined. METHODS: We investigated whether SLC6A4 promoter polymorphisms (5-HTTLPR, rs25531) and several downstream single nucleotide polymorphisms (SNPs) modulated activity of brain regions involved in the cognitive control of emotion in post-9/11 veterans with PTSD. We used functional MRI to examine neural activity in a PTSD group (n = 22) and a trauma-exposed control group (n = 20) in response to trauma-related images presented as task-irrelevant distractors during the active maintenance period of a delayed-response working memory task. Regions of interest were derived by contrasting activation for the most distracting and least distracting conditions across participants. RESULTS: In patients with PTSD, when compared to trauma-exposed controls, rs16965628 (associated with serotonin transporter gene expression) modulated task-related ventrolateral PFC activation and 5-HTTLPR tended to modulate left amygdala activation. Subsequent to combat-related trauma, these SLC6A4 polymorphisms may bias serotonin signaling and the neural circuitry mediating cognitive control of emotion in patients with PTSD. CONCLUSIONS: The SLC6A4 SNP rs16965628 and 5-HTTLPR are associated with a bias in neural responses to traumatic reminders and cognitive control of emotions in patients with PTSD. Functional MRI may help identify intermediate phenotypes and dimensions of PTSD that clarify the functional link between genes and disease phenotype, and also highlight features of PTSD that show more proximal influence of susceptibility genes compared to current clinical categorizations

ARTSCENE: A Neural System for Natural Scene Classification

How do humans rapidly recognize a scene? How can neural models capture this biological competence to achieve state-of-the-art scene classification? The ARTSCENE neural system classifies natural scene photographs by using multiple spatial scales to efficiently accumulate evidence for gist and texture. ARTSCENE embodies a coarse-to-fine Texture Size Ranking Principle whereby spatial attention processes multiple scales of scenic information, ranging from global gist to local properties of textures. The model can incrementally learn and predict scene identity by gist information alone and can improve performance through selective attention to scenic textures of progressively smaller size. ARTSCENE discriminates 4 landscape scene categories (coast, forest, mountain and countryside) with up to 91.58% correct on a test set, outperforms alternative models in the literature which use biologically implausible computations, and outperforms component systems that use either gist or texture information alone. Model simulations also show that adjacent textures form higher-order features that are also informative for scene recognition.National Science Foundation (NSF SBE-0354378); Office of Naval Research (N00014-01-1-0624

Advances in estimation by the item sum technique using auxiliary information in complex surveys

To collect sensitive data, survey statisticians have designed many strategies to reduce nonresponse rates and social desirability response bias. In recent years, the item count technique (ICT) has gained considerable popularity and credibility as an alternative mode of indirect questioning survey, and several variants of this technique have been proposed as new needs and challenges arise. The item sum technique (IST), which was introduced by Chaudhuri and Christofides (2013) and Trappmann et al. (2014), is one such variant, used to estimate the mean of a sensitive quantitative variable. In this approach, sampled units are asked to respond to a two-list of items containing a sensitive question related to the study variable and various innocuous, nonsensitive, questions. To the best of our knowledge, very few theoretical and applied papers have addressed the IST. In this article, therefore, we present certain methodological advances as a contribution to appraising the use of the IST in real-world surveys. In particular, we employ a generic sampling design to examine the problem of how to improve the estimates of the sensitive mean when auxiliary information on the population under study is available and is used at the design and estimation stages. A Horvitz-Thompson type estimator and a calibration type estimator are proposed and their efficiency is evaluated by means of an extensive simulation study. Using simulation experiments, we show that estimates obtained by the IST are nearly equivalent to those obtained using “true data” and that in general they outperform the estimates provided by a competitive randomized response method. Moreover, the variance estimation may be considered satisfactory. These results open up new perspectives for academics, researchers and survey practitioners, and could justify the use of the IST as a valid alternative to traditional direct questioning survey modes.Ministerio de Economía y Competitividad of SpainMinisterio de Educacion, Cultura y Deporteproject PRIN-SURWE

Functional diversity of brain networks supports consciousness and verbal intelligence

© 2018, The Author(s). How are the myriad stimuli arriving at our senses transformed into conscious thought? To address this question, in a series of studies, we asked whether a common mechanism underlies loss of information processing in unconscious states across different conditions, which could shed light on the brain mechanisms of conscious cognition. With a novel approach, we brought together for the first time, data from the same paradigm—a highly engaging auditory-only narrative—in three independent domains: anesthesia-induced unconsciousness, unconsciousness after brain injury, and individual differences in intellectual abilities during conscious cognition. During external stimulation in the unconscious state, the functional differentiation between the auditory and fronto-parietal systems decreased significantly relatively to the conscious state. Conversely, we found that stronger functional differentiation between these systems in response to external stimulation predicted higher intellectual abilities during conscious cognition, in particular higher verbal acuity scores in independent cognitive testing battery. These convergent findings suggest that the responsivity of sensory and higher-order brain systems to external stimulation, especially through the diversification of their functional responses is an essential feature of conscious cognition and verbal intelligence

Electrophysiological and cellular analysis of filamin-C mutations causing cardiomyopathy using human iPSC-derived cardiomyocytes

Background: Arrhythmogenic Cardiomyopathy (AC) is a genetic cardiac disease resulting from different mutations within proteins constituting the intercalated disc, including desmosomal and nondesmosomal proteins. Recent studies have revealed that mutations in filamin-C (FLNC) may lead to AC. The arrhythmogenesis and electrophysiological effects of FLNC-related AC are incompletely understood. Therefore, the aim of this study is to assess the potential electrophysiological consequences of FLNC loss as occurs in AC in human induced pluripotent stem cell-derived cardiomyocytes (hiPSCCMs). Specifically, I aimed to characterise abnormal electrical activity and the expression and function of key proteins in cardiac electrical activity such as gap junction protein connexin 43 (Cx43).// Methods: hiPSC-CMs were differentiated and observed by immunofluorescence microscopy. Small interfering RNA (siRNA) transfection was utilised to knockdown the expression of FLNC in hiPSC-CMs. Protein analysis was performed using western blotting to confirm the knockdown efficiency. Electrophysiological properties were recorded using a multielectrode array and manual patch clamping. Optical recording of membrane potential and calcium activity from hiPSC-CMs were also carried out using parameter sensitive dyes.// Results: Silencing of FLNC led to markedly decreased immunofluorescence signals of FLNC, Cx43, desmoplakin, and junctional plakoglobin. No significant reductions were noted in the immunofluorescence signals of voltage-gated sodium channel (Nav1.5) and plakophilin-2 compared with control hiPSC-CMs. Western blotting showed the reduction of FLNC and Cx43 expression following silencing of FLNC. Knockdown of FLNC resulted in disturbances to the recorded action and field potential signals of hiPSC-CMs and arrhythmic likeevents. Transfected hiPSC-CMs with siRNA-FLNC were associated with prolongation of calcium transient durations, optical action potential duration, and action potentials measured with patch clamping.// Conclusion: The current findings indicated that loss of FLNC resulted in a complex arrhythmogenic phenotype in hiPSC-CM