Optical Parametric Amplification of Single Photon: Statistical Properties and Quantum Interference

NASA Astrophysics Data System (ADS)

Xu, Xue-Xiang; Yuan, Hong-Chun

2014-05-01

By using phase space method, we theoretically investigate the quantum statistical properties and quantum interference of optical parametric amplification of single photon. The statistical properties, such as the Wigner function (WF), average photon number, photon number distribution and parity, are derived analytically for the fields of the two output ports. The results indicate that the fields in the output ports are multiphoton states rather than single photon state due to the amplification of the optical parametric amplifiers (OPA). In addition, the phase sensitivity is also examined by using the detection scheme of parity measurement.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

PubMed

Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-06-01

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography

PubMed Central

Packham, B; Barnes, G; dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-01-01

Abstract Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity. PMID:27203477

A Nonparametric Geostatistical Method For Estimating Species Importance

Treesearch

Andrew J. Lister; Rachel Riemann; Michael Hoppus

2001-01-01

Parametric statistical methods are not always appropriate for conducting spatial analyses of forest inventory data. Parametric geostatistical methods such as variography and kriging are essentially averaging procedures, and thus can be affected by extreme values. Furthermore, non normal distributions violate the assumptions of analyses in which test statistics are...

Preliminary evidence for linkage to chromosome 1q31-32, 10q23.3, and 16p13.3 in a South African cohort with bipolar disorder.

PubMed

Savitz, Jonathan; Cupido, Cinda-Lee; Ramesar, Raj Kumar

2007-04-05

Although the genetic variants predisposing to the development of bipolar disorder (BPD) have yet to be conclusively identified, replicated reports of linkage to particular chromosomal regions have been encouraging. Here we carried out a non-parametric linkage analysis of nine of these candidate loci in a unique South African sample of 47 BPD pedigrees (N = 350). Three polymorphic markers per region of interest (3 x 9) were typed in a Caucasian cohort of Afrikaner and British origin. Statistically significant evidence for linkage was obtained at 1q31-32, 10q23.3, and 16p13.3 with maximum NPL scores of 2.52, 2.01, and 1.84, respectively. Our results add to the growing evidence that these chromosomal regions harbor genetic variants that play a role in the development of bipolar spectrum illness. Negative results were obtained for the remaining six candidate loci, possibly due to limited statistical power. (c) 2006 Wiley-Liss, Inc.

Daylight exposure and the other predictors of burnout among nurses in a University Hospital.

PubMed

Alimoglu, Mustafa Kemal; Donmez, Levent

2005-07-01

The purpose of the study was to investigate if daylight exposure in work setting could be placed among the predictors of job burnout. The sample was composed of 141 nurses who work in Akdeniz University Hospital in Antalya, Turkey. All participants were asked to complete a personal data collection form, the Maslach Burnout Inventory, the Work Related Strain Inventory and the Work Satisfaction Questionnaire to collect data about their burnout, work-related stress (WRS) and job satisfaction (JS) levels in addition to personal characteristics. Descriptive statistics, parametric and non-parametric tests and correlation analysis were used in statistical analyses. Daylight exposure showed no direct effect on burnout but it was indirectly effective via WRS and JS. Exposure to daylight at least 3h a day was found to cause less stress and higher satisfaction at work. Suffering from sleep disorders, younger age, job-related health problems and educational level were found to have total or partial direct effects on burnout. Night shifts may lead to burnout via work related strain and working in inpatient services and dissatisfaction with annual income may be effective via job dissatisfaction. This study confirmed some established predictors of burnout and provided data on an unexplored area. Daylight exposure may be effective on job burnout.

The chi-square test of independence.

PubMed

McHugh, Mary L

2013-01-01

The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. The Chi-square is a significance statistic, and should be followed with a strength statistic. The Cramer's V is the most common strength test used to test the data when a significant Chi-square result has been obtained. Advantages of the Chi-square include its robustness with respect to distribution of the data, its ease of computation, the detailed information that can be derived from the test, its use in studies for which parametric assumptions cannot be met, and its flexibility in handling data from both two group and multiple group studies. Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer's V to produce relative low correlation measures, even for highly significant results.

When the Single Matters more than the Group (II): Addressing the Problem of High False Positive Rates in Single Case Voxel Based Morphometry Using Non-parametric Statistics.

PubMed

Scarpazza, Cristina; Nichols, Thomas E; Seramondi, Donato; Maumet, Camille; Sartori, Giuseppe; Mechelli, Andrea

2016-01-01

In recent years, an increasing number of studies have used Voxel Based Morphometry (VBM) to compare a single patient with a psychiatric or neurological condition of interest against a group of healthy controls. However, the validity of this approach critically relies on the assumption that the single patient is drawn from a hypothetical population with a normal distribution and variance equal to that of the control group. In a previous investigation, we demonstrated that family-wise false positive error rate (i.e., the proportion of statistical comparisons yielding at least one false positive) in single case VBM are much higher than expected (Scarpazza et al., 2013). Here, we examine whether the use of non-parametric statistics, which does not rely on the assumptions of normal distribution and equal variance, would enable the investigation of single subjects with good control of false positive risk. We empirically estimated false positive rates (FPRs) in single case non-parametric VBM, by performing 400 statistical comparisons between a single disease-free individual and a group of 100 disease-free controls. The impact of smoothing (4, 8, and 12 mm) and type of pre-processing (Modulated, Unmodulated) was also examined, as these factors have been found to influence FPRs in previous investigations using parametric statistics. The 400 statistical comparisons were repeated using two independent, freely available data sets in order to maximize the generalizability of the results. We found that the family-wise error rate was 5% for increases and 3.6% for decreases in one data set; and 5.6% for increases and 6.3% for decreases in the other data set (5% nominal). Further, these results were not dependent on the level of smoothing and modulation. Therefore, the present study provides empirical evidence that single case VBM studies with non-parametric statistics are not susceptible to high false positive rates. The critical implication of this finding is that VBM can be used to characterize neuroanatomical alterations in individual subjects as long as non-parametric statistics are employed.

Investigation of the photon statistics of parametric fluorescence in a traveling-wave parametric amplifier by means of self-homodyne tomography.

PubMed

Vasilyev, M; Choi, S K; Kumar, P; D'Ariano, G M

1998-09-01

Photon-number distributions for parametric fluorescence from a nondegenerate optical parametric amplifier are measured with a novel self-homodyne technique. These distributions exhibit the thermal-state character predicted by theory. However, a difference between the fluorescence gain and the signal gain of the parametric amplifier is observed. We attribute this difference to a change in the signal-beam profile during the traveling-wave pulsed amplification process.

Association between sleep disorders, hyperacusis and tinnitus: evaluation with tinnitus questionnaires.

PubMed

Fioretti, Alessandra B; Fusetti, Marco; Eibenstein, Alberto

2013-01-01

Patients with tinnitus are heterogeneous and several factors influence the impact of this symptom on the quality of life. The aim of the study is to evaluate the relationship between age, gender, sleep disorders, hyperacusis and tinnitus annoyance and to demonstrate the utility of tinnitus questionnaires as screening tools for sleep disorders and hyperacusis in patients with tinnitus. 37 consecutive patients (18 males and 19 females) with subjective tinnitus lasting over 3 months were evaluated with a complete interview, otological examination, pure tone audiometry, Italian version of tinnitus sample case history (TSCH) and tinnitus handicap inventory (THI). Statistical analysis was performed with the Wilcoxon's rank sum test, the Spearman's rho non-parametric correlation and the logistic regression analysis. THI grades were slight (16%), mild (32%), moderate (30%), severe (19%) and catastrophic (3%). Based on the answers to TSCH 20 patients reported sleep disorders (54%) and 20 patients reported hyperacusis (54%). 11 patients (30%) reported sleep disorders and hyperacusis. No significant correlation was found between the severity of tinnitus and patients' age and gender. Significant correlation was found between sleep disorders (P = 0.0009) and tinnitus annoyance and between hyperacusis (P = 0.03) and tinnitus annoyance. TSCH and THI may be considered as screening tools in the clinical practice to evidence sleep disorders and hyperacusis in patients with tinnitus.

Applying Statistical Models and Parametric Distance Measures for Music Similarity Search

NASA Astrophysics Data System (ADS)

Lukashevich, Hanna; Dittmar, Christian; Bastuck, Christoph

Automatic deriving of similarity relations between music pieces is an inherent field of music information retrieval research. Due to the nearly unrestricted amount of musical data, the real-world similarity search algorithms have to be highly efficient and scalable. The possible solution is to represent each music excerpt with a statistical model (ex. Gaussian mixture model) and thus to reduce the computational costs by applying the parametric distance measures between the models. In this paper we discuss the combinations of applying different parametric modelling techniques and distance measures and weigh the benefits of each one against the others.

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

A pilot DTI analysis in patients with recent onset post-traumatic stress disorder

NASA Astrophysics Data System (ADS)

Liu, Yang; Li, Liang; Li, Baojuan; Zhang, Xi; Lu, Hongbing

2016-03-01

To explore the alteration in white matter between survivors with recent onset post-traumatic stress disorder (PTSD) and without PTSD, who survived from the same coal mine flood disaster, the diffusion tensor imaging (DTI) sequences were analyzed using DTI studio and statistical parametric mapping (SPM) packages in this paper. From DTI sequence, the fractional anisotropy (FA) value describes the degree of anisotropy of a diffusion process, while the apparent diffusion coefficient (ADC) value reflects the magnitude of water diffusion. The DTI analyses between PTSD and non-PTSD indicate lower FA values in the right caudate nucleus, right middle temporal gyrus, right fusiform gyrus, and right superior temporal gyrus, and higher ADC values in the right superior temporal gyrus and right corpus callosum of the subjects with PTSD. These results are partly in line with our previous volume and cortical thickness analyses, indicating the importance of multi-modality analysis for PTSD.

Evaluating the features of the brain waves to quantify ADHD improvement by neurofeedback.

PubMed

Dehghanpour, Peyman; Einalou, Zahra

2017-10-23

Attention-deficit/hyperactivity disorder (ADHD), as one of the most common neurological disorders in children and adolescents, is characterized by decentralization, slow learning, distraction and hyperactivity. Studies have shown that in addition to medication, neurofeedback training can also be used to partially control the brain activity of these patients. In this study, using the brain signals processing before and after the treatment in 10 children treated by neurofeedback, the changes were evaluated by non-parametric statistical analysis and impact of neurofeedback on brain frequency bands was investigated. Finally, the results were compared with the protocols introduced in this paper and before researches. The results of Kruskal-Wallis test showed an approximately significant increase in the relative power of gamma and an approximately significant reduction in the ratio of relative power of alpha/beta. It represents the emotional response, elicited by the successful learning and diminished ratio of slow learning to active learning respectively.

Sleep analysis for wearable devices applying autoregressive parametric models.

PubMed

Mendez, M O; Villantieri, O; Bianchi, A; Cerutti, S

2005-01-01

We applied time-variant and time-invariant parametric models in both healthy subjects and patients with sleep disorder recordings in order to assess the skills of those approaches to sleep disorders diagnosis in wearable devices. The recordings present the Obstructive Sleep Apnea (OSA) pathology which is characterized by fluctuations in the heart rate, bradycardia in apneonic phase and tachycardia at the recovery of ventilation. Data come from a web database in www.physionet.org. During OSA the spectral indexes obtained by time-variant lattice filters presented oscillations that correspond to the changes brady-tachycardia of the RR intervals and greater values than healthy ones. Multivariate autoregressive models showed an increment in very low frequency component (PVLF) at each apneic event. Also a rise in high frequency component (PHF) occurred over the breathing restore in the spectrum of both quadratic coherence and cross-spectrum in OSA. These autoregressive parametric approaches could help in the diagnosis of Sleep Disorder inside of the wearable devices.

Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder.

PubMed

Hassa, Thomas; Sebastian, Alexandra; Liepert, Joachim; Weiller, Cornelius; Schmidt, Roger; Tüscher, Oliver

2017-01-01

Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI) was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-)supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.

Experimental study of microwave photon statistics under parametric amplification from a single-mode thermal state in a cavity

NASA Astrophysics Data System (ADS)

Galeazzi, G.; Lombardi, A.; Ruoso, G.; Braggio, C.; Carugno, G.; Della Valle, F.; Zanello, D.; Dodonov, V. V.

2013-11-01

In this paper we present theoretical and experimental studies of the modifications of the thermal spectrum inside a microwave resonator due to a parametric amplification process. Both the degenerate and nondegenerate amplifiers are discussed. Theoretical calculations are compared with measurements performed with a microwave cavity parametric amplifier.

Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers

NASA Technical Reports Server (NTRS)

Walker, Eric L.; Starnes, B. Alden; Birch, Jeffery B.; Mays, James E.

2010-01-01

This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed by Mays, Birch, and Starnes, is shown to improve instrument calibration by reducing the reliance of the calibration on a predetermined parametric (e.g. polynomial, exponential, logarithmic) model. This is accomplished by allowing fits from the predetermined parametric model to be augmented by a certain portion of a fit to the residuals from the initial regression using a nonparametric (locally parametric) regression technique. The method is demonstrated for the absolute scale calibration of silicon-based pressure transducers.

Statistical testing and power analysis for brain-wide association study.

PubMed

Gong, Weikang; Wan, Lin; Lu, Wenlian; Ma, Liang; Cheng, Fan; Cheng, Wei; Grünewald, Stefan; Feng, Jianfeng

2018-04-05

The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS. Copyright © 2018 Elsevier B.V. All rights reserved.

A nonparametric spatial scan statistic for continuous data.

PubMed

Jung, Inkyung; Cho, Ho Jin

2015-10-20

Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.

Gain statistics of a fiber optical parametric amplifier with a temporally incoherent pump.

PubMed

Xu, Y Q; Murdoch, S G

2010-03-15

We present an investigation of the statistics of the gain fluctuations of a fiber optical parametric amplifier pumped with a temporally incoherent pump. We derive a simple expression for the probability distribution of the gain of the amplified optical signal. The gain statistics are shown to be a strong function of the signal detuning and allow the possibility of generating optical gain distributions with controllable long-tails. Very good agreement is found between this theory and the experimentally measured gain distributions of an incoherently pumped amplifier.

Minimum Uncertainty Coherent States Attached to Nondegenerate Parametric Amplifiers

NASA Astrophysics Data System (ADS)

Dehghani, A.; Mojaveri, B.

2015-06-01

Exact analytical solutions for the two-mode nondegenerate parametric amplifier have been obtained by using the transformation from the two-dimensional harmonic oscillator Hamiltonian. Some important physical properties such as quantum statistics and quadrature squeezing of the corresponding states are investigated. In addition, these states carry classical features such as Poissonian statistics and minimize the Heisenberg uncertainty relation of a pair of the coordinate and the momentum operators.

A statistical approach to bioclimatic trend detection in the airborne pollen records of Catalonia (NE Spain)

NASA Astrophysics Data System (ADS)

Fernández-Llamazares, Álvaro; Belmonte, Jordina; Delgado, Rosario; De Linares, Concepción

2014-04-01

Airborne pollen records are a suitable indicator for the study of climate change. The present work focuses on the role of annual pollen indices for the detection of bioclimatic trends through the analysis of the aerobiological spectra of 11 taxa of great biogeographical relevance in Catalonia over an 18-year period (1994-2011), by means of different parametric and non-parametric statistical methods. Among others, two non-parametric rank-based statistical tests were performed for detecting monotonic trends in time series data of the selected airborne pollen types and we have observed that they have similar power in detecting trends. Except for those cases in which the pollen data can be well-modeled by a normal distribution, it is better to apply non-parametric statistical methods to aerobiological studies. Our results provide a reliable representation of the pollen trends in the region and suggest that greater pollen quantities are being liberated to the atmosphere in the last years, specially by Mediterranean taxa such as Pinus, Total Quercus and Evergreen Quercus, although the trends may differ geographically. Longer aerobiological monitoring periods are required to corroborate these results and survey the increasing levels of certain pollen types that could exert an impact in terms of public health.

Development of computer-assisted instruction application for statistical data analysis android platform as learning resource

NASA Astrophysics Data System (ADS)

Hendikawati, P.; Arifudin, R.; Zahid, M. Z.

2018-03-01

This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

PubMed

Broët, Philippe; Tsodikov, Alexander; De Rycke, Yann; Moreau, Thierry

2004-06-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

An investigation of the joint longitudinal trajectories of low body weight, binge eating, and purging in women with anorexia nervosa and bulimia nervosa

PubMed Central

Lavender, Jason M.; De Young, Kyle P.; Franko, Debra L.; Eddy, Kamryn T.; Kass, Andrea E.; Sears, Meredith S.; Herzog, David B.

2015-01-01

Objectives To describe the longitudinal course of three core eating disorder symptoms – low body weight, binge eating, and purging – in women with anorexia nervosa (AN) and bulimia nervosa (BN) using a novel statistical approach. Method Treatment-seeking women with AN (n=136) or BN (n=110) completed the Eating Disorders Longitudinal Interval Follow-Up Evaluation interview every six months, yielding weekly eating disorder symptom data for a five-year period. Semi-parametric mixture modeling was used to identify longitudinal trajectories for the three core symptoms. Results Four individual trajectories were identified for each eating disorder symptom. The number and general shape of the individual trajectories was similar across symptoms, with each model including trajectories depicting stable absence and stable presence of symptoms as well as one or more trajectories depicting the declining presence of symptoms. Unique trajectories were found for low body weight (fluctuating presence) and purging (increasing presence). Conjunction analyses yielded the following joint trajectories: low body weight and binge eating, low body weight and purging, and binge eating and purging. Conclusions The course of individual eating disorder symptoms among patients with AN and BN is highly variable. Future research identifying clinical predictors of trajectory membership may inform treatment and nosological research. PMID:22072404

The use of analysis of variance procedures in biological studies

USGS Publications Warehouse

Williams, B.K.

1987-01-01

The analysis of variance (ANOVA) is widely used in biological studies, yet there remains considerable confusion among researchers about the interpretation of hypotheses being tested. Ambiguities arise when statistical designs are unbalanced, and in particular when not all combinations of design factors are represented in the data. This paper clarifies the relationship among hypothesis testing, statistical modelling and computing procedures in ANOVA for unbalanced data. A simple two-factor fixed effects design is used to illustrate three common parametrizations for ANOVA models, and some associations among these parametrizations are developed. Biologically meaningful hypotheses for main effects and interactions are given in terms of each parametrization, and procedures for testing the hypotheses are described. The standard statistical computing procedures in ANOVA are given along with their corresponding hypotheses. Throughout the development unbalanced designs are assumed and attention is given to problems that arise with missing cells.

[The research protocol VI: How to choose the appropriate statistical test. Inferential statistics].

PubMed

Flores-Ruiz, Eric; Miranda-Novales, María Guadalupe; Villasís-Keever, Miguel Ángel

2017-01-01

The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

Two-Sample Statistics for Testing the Equality of Survival Functions Against Improper Semi-parametric Accelerated Failure Time Alternatives: An Application to the Analysis of a Breast Cancer Clinical Trial

PubMed Central

BROËT, PHILIPPE; TSODIKOV, ALEXANDER; DE RYCKE, YANN; MOREAU, THIERRY

2010-01-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests. PMID:15293627

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

PubMed

Chu, Annie; Cui, Jenny; Dinov, Ivo D

2009-03-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models.

Least Squares Procedures.

ERIC Educational Resources Information Center

Hester, Yvette

Least squares methods are sophisticated mathematical curve fitting procedures used in all classical parametric methods. The linear least squares approximation is most often associated with finding the "line of best fit" or the regression line. Since all statistical analyses are correlational and all classical parametric methods are least…

Effect of non-normality on test statistics for one-way independent groups designs.

PubMed

Cribbie, Robert A; Fiksenbaum, Lisa; Keselman, H J; Wilcox, Rand R

2012-02-01

The data obtained from one-way independent groups designs is typically non-normal in form and rarely equally variable across treatment populations (i.e., population variances are heterogeneous). Consequently, the classical test statistic that is used to assess statistical significance (i.e., the analysis of variance F test) typically provides invalid results (e.g., too many Type I errors, reduced power). For this reason, there has been considerable interest in finding a test statistic that is appropriate under conditions of non-normality and variance heterogeneity. Previously recommended procedures for analysing such data include the James test, the Welch test applied either to the usual least squares estimators of central tendency and variability, or the Welch test with robust estimators (i.e., trimmed means and Winsorized variances). A new statistic proposed by Krishnamoorthy, Lu, and Mathew, intended to deal with heterogeneous variances, though not non-normality, uses a parametric bootstrap procedure. In their investigation of the parametric bootstrap test, the authors examined its operating characteristics under limited conditions and did not compare it to the Welch test based on robust estimators. Thus, we investigated how the parametric bootstrap procedure and a modified parametric bootstrap procedure based on trimmed means perform relative to previously recommended procedures when data are non-normal and heterogeneous. The results indicated that the tests based on trimmed means offer the best Type I error control and power when variances are unequal and at least some of the distribution shapes are non-normal. © 2011 The British Psychological Society.

Simulation of parametric model towards the fixed covariate of right censored lung cancer data

NASA Astrophysics Data System (ADS)

Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Ridwan Olaniran, Oyebayo; Enera Amran, Syahila

2017-09-01

In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

PubMed Central

Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki

2018-01-01

Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473

Basal cerebral glucose distribution in long-term post-traumatic stress disorder.

PubMed

Molina, Mario Enrique; Isoardi, Roberto; Prado, Marcela Nathalie; Bentolila, Silvia

2010-03-01

The purpose of this investigation was to study basal cerebral glucose absorption patterns associated to long-term post-traumatic stress disorder. Fluorodeoxyglucose positron emission tomography (FDG-PET) and statistic parametric mapping (SPM) were used to compare regional cerebral glucose absorption between 15 war veterans (Hispanic men, aged 39-41 (M = 39.5, SD = 0.84)) diagnosed with post-traumatic stress disorder (PTSD) based on DSM-IV criteria, and a matching control group of six asymptomatic veterans. This study was conducted 20 years after the traumatic events. PTSD patients presented relatively diminished activity (P<0.005) in: cingulate gyri, precuneus, insula, hippocampus; frontal, pre-frontal and post-central regions; lingual, calcarine, occipital medial and superior gyri, and verbal and paraverbal areas. Relativeley augmented activity (P<0.005) was observed in PTSD patients in: fusiform, temporal superior, medial, and inferior gyri; occipital medial, inferior and lingual gyri; precuneus, and cerebellum. The amygdala and the thalamus showed normal metabolic activity. Various brain regions that showed diminished activity (limbic, frontal and prefrontal cortex, multimodal parieto-occipital areas and verbal and paraverbal areas) have evolved lately, and sub-serve highly complex cognitive and behavioural functions. Metabolic activity patterns are comparable to those observed in personality disorders of the borderline type.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

Perceptual switch rates with ambiguous structure-from-motion figures in bipolar disorder.

PubMed

Krug, Kristine; Brunskill, Emma; Scarna, Antonina; Goodwin, Guy M; Parker, Andrew J

2008-08-22

Slowing of the rate at which a rivalrous percept switches from one configuration to another has been suggested as a potential trait marker for bipolar disorder. We measured perceptual alternations for a bistable, rotating, structure-from-motion cylinder in bipolar and control participants. In a control task, binocular depth rendered the direction of cylinder rotation unambiguous to monitor participants' performance and attention during the experimental task. A particular direction of rotation was perceptually stable, on average, for 33.5s in participants without psychiatric diagnosis. Euthymic, bipolar participants showed a slightly slower rate of switching between the two percepts (percept duration 42.3s). Under a parametric analysis of the best-fitting model for individual participants, this difference was statistically significant. However, the variability within groups was high, so this difference in average switch rates was not big enough to serve as a trait marker for bipolar disorder. We also found that low-level visual capacities, such as stereo threshold, influence perceptual switch rates. We suggest that there is no single brain location responsible for perceptual switching in all different ambiguous figures and that perceptual switching is generated by the actions of local cortical circuitry.

Pooling sexes when assessing ground reaction forces during walking: Statistical Parametric Mapping versus traditional approach.

PubMed

Castro, Marcelo P; Pataky, Todd C; Sole, Gisela; Vilas-Boas, Joao Paulo

2015-07-16

Ground reaction force (GRF) data from men and women are commonly pooled for analyses. However, it may not be justifiable to pool sexes on the basis of discrete parameters extracted from continuous GRF gait waveforms because this can miss continuous effects. Forty healthy participants (20 men and 20 women) walked at a cadence of 100 steps per minute across two force plates, recording GRFs. Two statistical methods were used to test the null hypothesis of no mean GRF differences between sexes: (i) Statistical Parametric Mapping-using the entire three-component GRF waveform; and (ii) traditional approach-using the first and second vertical GRF peaks. Statistical Parametric Mapping results suggested large sex differences, which post-hoc analyses suggested were due predominantly to higher anterior-posterior and vertical GRFs in early stance in women compared to men. Statistically significant differences were observed for the first GRF peak and similar values for the second GRF peak. These contrasting results emphasise that different parts of the waveform have different signal strengths and thus that one may use the traditional approach to choose arbitrary metrics and make arbitrary conclusions. We suggest that researchers and clinicians consider both the entire gait waveforms and sex-specificity when analysing GRF data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal FWERs. Those rejected clusters were outlying values in the distribution of cluster size but cannot be distinguished from true positive findings without further analyses, including assessing whether fMRI signal in those regions correlates with other clinical, behavioral, or cognitive measures. Rejecting the large clusters, however, significantly reduced the statistical power of nonparametric methods in detecting true findings compared with parametric methods, which would have detected most true findings that are essential for making valid biological inferences in MRI data. Parametric analyses, in contrast, detected most true findings while generating relatively few false positives: on average, less than one of those very large clusters would be deemed a true finding in each brain-wide analysis. We therefore recommend the continued use of parametric methods that model nonstationary smoothness for cluster-level, familywise control of false positives, particularly when using a Cluster Defining Threshold of 2.5 or higher, and subsequently assessing rigorously the biological plausibility of the findings, even for large clusters. Finally, because nonparametric methods yielded a large reduction in statistical power to detect true positive findings, we conclude that the modest reduction in false positive findings that nonparametric analyses afford does not warrant a re-analysis of previously published fMRI studies using nonparametric techniques. Copyright © 2018 Elsevier Inc. All rights reserved.

Crash Lethality Model

DTIC Science & Technology

2012-06-06

Statistical Data ........................................................................................... 45 31 Parametric Model for Rotor Wing Debris...Area .............................................................. 46 32 Skid Distance Statistical Data...results. The curve that related the BC value to the probability of skull fracture resulted in a tight confidence interval and a two tailed statistical p

Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum

2011-01-01

Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…

EEG Correlates of Fluctuation in Cognitive Performance in an Air Traffic Control Task

DTIC Science & Technology

2014-11-01

using non-parametric statistical analysis to identify neurophysiological patterns due to the time-on-task effect. Significant changes in EEG power...EEG, Cognitive Performance, Power Spectral Analysis , Non-Parametric Analysis Document is available to the public through the Internet...3 Performance Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 EEG

Influence of depression and anxiety on circulating endothelial progenitor cells in patients with acute coronary syndromes.

PubMed

Felice, Francesca; Di Stefano, Rossella; Pini, Stefano; Mazzotta, Gianfranco; Bovenzi, Francesco M; Bertoli, Daniele; Abelli, Marianna; Borelli, Lucia; Cardini, Alessandra; Lari, Lisa; Gesi, Camilla; Michi, Paola; Morrone, Doralisa; Gnudi, Luigi; Balbarini, Alberto

2015-05-01

Circulating endothelial progenitor cells (EPCs) are related to endothelial function and progression of coronary artery disease. There is evidence of decreased numbers of circulating EPCs in patients with a current episode of major depression. We investigated the relationships between the level of circulating EPCs and depression and anxiety in patients with acute coronary syndrome (ACS). Patients with ACS admitted to three Cardiology Intensive Care Units were evaluated by the SCID-I to determine the presence of lifetime and/or current mood and anxiety disorders according to DSM-IV criteria. The EPCs were defined as CD133(+) CD34(+) KDR(+) and evaluated by flow cytometry. All patients underwent standardized cardiological and psychopathological evaluations. Parametric and nonparametric statistical tests were performed where appropriate. Out of 111 ACS patients, 57 were found to have a DSM-IV lifetime or current mood or anxiety disorder at the time of the inclusion in the study. The ACS group with mood or anxiety disorders showed a significant decrease in circulating EPC number compared with ACS patients without affective disorders. In addition, EPC levels correlated negatively with severity of depression and anxiety at index ACS episode. The current study indicates that EPCs circulate in decreased numbers in ACS patients with depression or anxiety and, therefore, contribute to explore new perspectives in the pathophysiology of the association between cardiovascular disorders and affective disorders. Copyright © 2015 John Wiley & Sons, Ltd.

Measured, modeled, and causal conceptions of fitness

PubMed Central

Abrams, Marshall

2012-01-01

This paper proposes partial answers to the following questions: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers. PMID:23112804

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

USGS Publications Warehouse

Lee, L.; Helsel, D.

2007-01-01

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Evaluating sufficient similarity for drinking-water disinfection by-product (DBP) mixtures with bootstrap hypothesis test procedures.

PubMed

Feder, Paul I; Ma, Zhenxu J; Bull, Richard J; Teuschler, Linda K; Rice, Glenn

2009-01-01

In chemical mixtures risk assessment, the use of dose-response data developed for one mixture to estimate risk posed by a second mixture depends on whether the two mixtures are sufficiently similar. While evaluations of similarity may be made using qualitative judgments, this article uses nonparametric statistical methods based on the "bootstrap" resampling technique to address the question of similarity among mixtures of chemical disinfectant by-products (DBP) in drinking water. The bootstrap resampling technique is a general-purpose, computer-intensive approach to statistical inference that substitutes empirical sampling for theoretically based parametric mathematical modeling. Nonparametric, bootstrap-based inference involves fewer assumptions than parametric normal theory based inference. The bootstrap procedure is appropriate, at least in an asymptotic sense, whether or not the parametric, distributional assumptions hold, even approximately. The statistical analysis procedures in this article are initially illustrated with data from 5 water treatment plants (Schenck et al., 2009), and then extended using data developed from a study of 35 drinking-water utilities (U.S. EPA/AMWA, 1989), which permits inclusion of a greater number of water constituents and increased structure in the statistical models.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Four modes of optical parametric operation for squeezed state generation

NASA Astrophysics Data System (ADS)

Andersen, U. L.; Buchler, B. C.; Lam, P. K.; Wu, J. W.; Gao, J. R.; Bachor, H.-A.

2003-11-01

We report a versatile instrument, based on a monolithic optical parametric amplifier, which reliably generates four different types of squeezed light. We obtained vacuum squeezing, low power amplitude squeezing, phase squeezing and bright amplitude squeezing. We show a complete analysis of this light, including a full quantum state tomography. In addition we demonstrate the direct detection of the squeezed state statistics without the aid of a spectrum analyser. This technique makes the nonclassical properties directly visible and allows complete measurement of the statistical moments of the squeezed quadrature.

CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions

EPA Pesticide Factsheets

Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.

Parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method of ledre profile attributes

NASA Astrophysics Data System (ADS)

Hastuti, S.; Harijono; Murtini, E. S.; Fibrianto, K.

2018-03-01

This current study is aimed to investigate the use of parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method. Ledre as Bojonegoro unique local food product was used as point of interest, in which 319 panelists were involved in the study. The result showed that ledre is characterized as easy-crushed texture, sticky in mouth, stingy sensation and easy to swallow. It has also strong banana flavour with brown in colour. Compared to eggroll and semprong, ledre has more variances in terms of taste as well the roll length. As RATA questionnaire is designed to collect categorical data, non-parametric approach is the common statistical procedure. However, similar results were also obtained as parametric approach, regardless the fact of non-normal distributed data. Thus, it suggests that parametric approach can be applicable for consumer study with large number of respondents, even though it may not satisfy the assumption of ANOVA (Analysis of Variances).

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

A Note on the Assumption of Identical Distributions for Nonparametric Tests of Location

ERIC Educational Resources Information Center

Nordstokke, David W.; Colp, S. Mitchell

2018-01-01

Often, when testing for shift in location, researchers will utilize nonparametric statistical tests in place of their parametric counterparts when there is evidence or belief that the assumptions of the parametric test are not met (i.e., normally distributed dependent variables). An underlying and often unattended to assumption of nonparametric…

Linkage analysis of chromosome 22q12-13 in a United Kingdom/Icelandic sample of 23 multiplex schizophrenia families

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalsi, G.; Read, T.; Butler, R.

A possible linkage to a genetic subtype of schizophrenia and related disorders has been reported on the long arm of chromosome 22 at q12-13. However formal statistical tests in a combined sample could not reject homogeneity and prove that there was linked subgroup of families. We have studied 23 schizophrenia pedigrees to test whether some multiplex schizophrenia families may be linked to the microsatellite markers D22S274 and D22S283 which span the 22q12-13 region. Two point followed by multipoint lod and non-parametric linkage analyses under the assumption of heterogeneity provided no evidence for linkage over the relevant region. 16 refs., 4more » tabs.« less

Social Referencing Gaze Behavior During a Videogame Task: Eye Tracking Evidence from Children With and Without ASD.

PubMed

Finke, Erinn H; Wilkinson, Krista M; Hickerson, Benjamin D

2017-02-01

The purpose of this study was to understand the social referencing behaviors of children with and without autism spectrum disorder (ASD) while visually attending to a videogame stimulus depicting both the face of the videogame player and the videogame play action. Videogames appear to offer a uniquely well-suited environment for the emergence of friendships, but it is not known if children with and without ASD attend to and play videogames similarly. Eyetracking technology was used to investigate visual attention of participants matched based on chronological age. Parametric and nonparametric statistical analyses were used and results indicated the groups did not differ on percentage of time spent visually attending to any of the areas of interest, with one possible exception.

Progressive neurostructural changes in adolescent and adult patients with bipolar disorder.

PubMed

Lisy, Megan E; Jarvis, Kelly B; DelBello, Melissa P; Mills, Neil P; Weber, Wade A; Fleck, David; Strakowski, Stephen M; Adler, Caleb M

2011-06-01

Several lines of evidence suggest that bipolar disorder is associated with progressive changes in gray matter volume (GMV), particularly in brain structures involved in emotional regulation and expression. The majority of these studies however, have been cross-sectional in nature. In this study we compared baseline and follow-up scans in groups of bipolar disorder and healthy subjects. We hypothesized bipolar disorder subjects would demonstrate significant GMV changes over time. A total of 58 bipolar disorder and 48 healthy subjects participated in structural magnetic resonance imaging (MRI). Subjects were rescanned 3-34 months after their baseline MRI. MRI images were segmented, normalized to standard stereotactic space, and compared voxel-by-voxel using statistical parametrical mapping software (SPM2). A model was developed to investigate differences in GMV at baseline, and associated with time and episodes, as well as in comparison to healthy subjects. We observed increases in GMV in bipolar disorder subjects across several brain regions at baseline and over time, including portions of the prefrontal cortex as well as limbic and subcortical structures. Time-related changes differed to some degree between adolescent and adult bipolar disorder subjects. The interval between scans positively correlated with GMV increases in bipolar disorder subjects in portions of the prefrontal cortex, and both illness duration and number of depressive episodes were associated with increased GMV in subcortical and limbic structures. Our findings support suggestions that widely observed progressive neurofunctional changes in bipolar disorder patients may be related to structural brain abnormalities in anterior limbic structures. Abnormalities largely involve regions previously noted to be integral to emotional expression and regulation, and appear to vary by age. © 2011 John Wiley and Sons A/S.

SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

Chu, Annie; Cui, Jenny; Dinov, Ivo D.

2011-01-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models. PMID:21546994

Statistical methods used in articles published by the Journal of Periodontal and Implant Science.

PubMed

Choi, Eunsil; Lyu, Jiyoung; Park, Jinyoung; Kim, Hae-Young

2014-12-01

The purposes of this study were to assess the trend of use of statistical methods including parametric and nonparametric methods and to evaluate the use of complex statistical methodology in recent periodontal studies. This study analyzed 123 articles published in the Journal of Periodontal & Implant Science (JPIS) between 2010 and 2014. Frequencies and percentages were calculated according to the number of statistical methods used, the type of statistical method applied, and the type of statistical software used. Most of the published articles considered (64.4%) used statistical methods. Since 2011, the percentage of JPIS articles using statistics has increased. On the basis of multiple counting, we found that the percentage of studies in JPIS using parametric methods was 61.1%. Further, complex statistical methods were applied in only 6 of the published studies (5.0%), and nonparametric statistical methods were applied in 77 of the published studies (38.9% of a total of 198 studies considered). We found an increasing trend towards the application of statistical methods and nonparametric methods in recent periodontal studies and thus, concluded that increased use of complex statistical methodology might be preferred by the researchers in the fields of study covered by JPIS.

Are the Nonparametric Person-Fit Statistics More Powerful than Their Parametric Counterparts? Revisiting the Simulations in Karabatsos (2003)

ERIC Educational Resources Information Center

Sinharay, Sandip

2017-01-01

Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…

Fuzzy interval Finite Element/Statistical Energy Analysis for mid-frequency analysis of built-up systems with mixed fuzzy and interval parameters

NASA Astrophysics Data System (ADS)

Yin, Hui; Yu, Dejie; Yin, Shengwen; Xia, Baizhan

2016-10-01

This paper introduces mixed fuzzy and interval parametric uncertainties into the FE components of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) model for mid-frequency analysis of built-up systems, thus an uncertain ensemble combining non-parametric with mixed fuzzy and interval parametric uncertainties comes into being. A fuzzy interval Finite Element/Statistical Energy Analysis (FIFE/SEA) framework is proposed to obtain the uncertain responses of built-up systems, which are described as intervals with fuzzy bounds, termed as fuzzy-bounded intervals (FBIs) in this paper. Based on the level-cut technique, a first-order fuzzy interval perturbation FE/SEA (FFIPFE/SEA) and a second-order fuzzy interval perturbation FE/SEA method (SFIPFE/SEA) are developed to handle the mixed parametric uncertainties efficiently. FFIPFE/SEA approximates the response functions by the first-order Taylor series, while SFIPFE/SEA improves the accuracy by considering the second-order items of Taylor series, in which all the mixed second-order items are neglected. To further improve the accuracy, a Chebyshev fuzzy interval method (CFIM) is proposed, in which the Chebyshev polynomials is used to approximate the response functions. The FBIs are eventually reconstructed by assembling the extrema solutions at all cut levels. Numerical results on two built-up systems verify the effectiveness of the proposed methods.

A question of separation: disentangling tracer bias and gravitational non-linearity with counts-in-cells statistics

NASA Astrophysics Data System (ADS)

Uhlemann, C.; Feix, M.; Codis, S.; Pichon, C.; Bernardeau, F.; L'Huillier, B.; Kim, J.; Hong, S. E.; Laigle, C.; Park, C.; Shin, J.; Pogosyan, D.

2018-02-01

Starting from a very accurate model for density-in-cells statistics of dark matter based on large deviation theory, a bias model for the tracer density in spheres is formulated. It adopts a mean bias relation based on a quadratic bias model to relate the log-densities of dark matter to those of mass-weighted dark haloes in real and redshift space. The validity of the parametrized bias model is established using a parametrization-independent extraction of the bias function. This average bias model is then combined with the dark matter PDF, neglecting any scatter around it: it nevertheless yields an excellent model for densities-in-cells statistics of mass tracers that is parametrized in terms of the underlying dark matter variance and three bias parameters. The procedure is validated on measurements of both the one- and two-point statistics of subhalo densities in the state-of-the-art Horizon Run 4 simulation showing excellent agreement for measured dark matter variance and bias parameters. Finally, it is demonstrated that this formalism allows for a joint estimation of the non-linear dark matter variance and the bias parameters using solely the statistics of subhaloes. Having verified that galaxy counts in hydrodynamical simulations sampled on a scale of 10 Mpc h-1 closely resemble those of subhaloes, this work provides important steps towards making theoretical predictions for density-in-cells statistics applicable to upcoming galaxy surveys like Euclid or WFIRST.

An appraisal of statistical procedures used in derivation of reference intervals.

PubMed

Ichihara, Kiyoshi; Boyd, James C

2010-11-01

When conducting studies to derive reference intervals (RIs), various statistical procedures are commonly applied at each step, from the planning stages to final computation of RIs. Determination of the necessary sample size is an important consideration, and evaluation of at least 400 individuals in each subgroup has been recommended to establish reliable common RIs in multicenter studies. Multiple regression analysis allows identification of the most important factors contributing to variation in test results, while accounting for possible confounding relationships among these factors. Of the various approaches proposed for judging the necessity of partitioning reference values, nested analysis of variance (ANOVA) is the likely method of choice owing to its ability to handle multiple groups and being able to adjust for multiple factors. Box-Cox power transformation often has been used to transform data to a Gaussian distribution for parametric computation of RIs. However, this transformation occasionally fails. Therefore, the non-parametric method based on determination of the 2.5 and 97.5 percentiles following sorting of the data, has been recommended for general use. The performance of the Box-Cox transformation can be improved by introducing an additional parameter representing the origin of transformation. In simulations, the confidence intervals (CIs) of reference limits (RLs) calculated by the parametric method were narrower than those calculated by the non-parametric approach. However, the margin of difference was rather small owing to additional variability in parametrically-determined RLs introduced by estimation of parameters for the Box-Cox transformation. The parametric calculation method may have an advantage over the non-parametric method in allowing identification and exclusion of extreme values during RI computation.

Statistical strategies to quantify respiratory sinus arrhythmia: Are commonly used metrics equivalent?

PubMed Central

Lewis, Gregory F.; Furman, Senta A.; McCool, Martha F.; Porges, Stephen W.

2011-01-01

Three frequently used RSA metrics are investigated to document violations of assumptions for parametric analyses, moderation by respiration, influences of nonstationarity, and sensitivity to vagal blockade. Although all metrics are highly correlated, new findings illustrate that the metrics are noticeably different on the above dimensions. Only one method conforms to the assumptions for parametric analyses, is not moderated by respiration, is not influenced by nonstationarity, and reliably generates stronger effect sizes. Moreover, this method is also the most sensitive to vagal blockade. Specific features of this method may provide insights into improving the statistical characteristics of other commonly used RSA metrics. These data provide the evidence to question, based on statistical grounds, published reports using particular metrics of RSA. PMID:22138367

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

Statistical Aspects of Tropical Cyclone Activity in the North Atlantic Basin, 1945-2010

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2012-01-01

Examined are statistical aspects of the 715 tropical cyclones that formed in the North Atlantic basin during the interval 1945-2010. These 715 tropical cyclones include 306 storms that attained only tropical storm strength, 409 hurricanes, 179 major or intense hurricanes, and 108 storms that struck the US coastline as hurricanes. Comparisons made using 10-year moving average (10-yma) values between tropical cyclone parametric values and surface air and ENSO-related parametric values indicate strong correlations to exist, in particular, against the Armagh Observatory (Northern Ireland) surface air temperature, the Atlantic Multi-decadal Oscillation (AMO) index, the Atlantic Meridional Mode (AMM) index, and the North Atlantic Oscillation (NAO) index, in addition to the Oceanic Ni o index (ONI) and Quasi-Biennial Oscillation (QBO) indices. Also examined are the decadal variations of the tropical cyclone parametric values and a look ahead towards the 2012 hurricane season and beyond.

Hoarding with and without excessive buying: results of a pilot study.

PubMed

Möllenkamp, Maike; de Zwaan, Martina; Müller, Astrid

2015-01-01

Previous research demonstrated a close relationship between hoarding disorder (compulsive hoarding, CH) and compulsive buying (CB). Hoarding disorder was included in the 5th version of the Diagnostic and Statistical Manual of Mental Disorders (APA, 2013) with excessive acquisition as a specifier. This pilot study aimed to investigate whether individuals with both hoarding and buying symptoms (CBCH group) will present with the highest severity levels of hoarding as well as buying psychopathology compared to the respective group exhibiting only one syndrome (CH group: only hoarding, CB group: only buying). The three groups (CH: n = 40, CBCH: n = 60, CB: n = 35) completed the Saving Inventory-Revised, the Compulsive Acquisition Scale und the Compulsive Buying Scale. Data were analysed using non-parametric tests. The CBCH group did not differ from the CH group with regard to the severity of key hoarding symptoms such as clutter, difficulty discarding possessions, and the acquisition of free things, but showed a higher severity of CB than the CB group. While the findings indicate remarkable overlap in primary features of CH in compulsive hoarders with and without excessive buying, they suggest more severe CB in individuals with both hoarding and buying symptoms compared to individuals with only CB. Future studies should address the question whether both disorders are part of a larger construct. © 2014 S. Karger AG, Basel.

[Using fairy tales and narrative strategies with the help of a sandpit with children suffering from conduct disorders].

PubMed

Konz, M

2006-01-01

Our research, focussed on art therapy with primary school children, guided us to the footsteps of women pioneers in the research about children's psyche, like Anna Freud, Melanie Klein, Margaret Loewenfeld, Dora Kalff. We have been inspired by their very personal but nevertheless somehow similar type of research, to work with the children in a blue sand pit, where they could construct and play their personal fairy tales. Thus they share with us their momentary preoccupations, without being forced to talk about them. They are revealing their internal structures, and are integrating, by narration and projection on those figurines in action, their deficient defense mechanisms as well as their negative tendencies. Based on this approach, we expect that there will by an amelioration of their social skills, an enhancement of their intrinsic motivation, and a diminution of their conduct disorders. The analyze will be done by questionnaires and rating scales constructed especially for this research, as well as by sociograms, with the help of descriptive non parametric statistics.

Effects of ageing on orofacial fine force control and its relationship with parallel change in sensory perception.

PubMed

Etter, Nicole M; Mckeon, Patrick O; Dressler, Emily V; Andreatta, Richard D

2017-05-03

Current theoretical models suggest the importance of a bidirectional relationship between sensation and production in the vocal tract to maintain lifelong speech skills. The purpose of this study was to assess age-related changes in orofacial skilled force production and to begin defining the orofacial perception-action relationship in healthy adults. Low-level orofacial force control measures (reaction time, rise time, peak force, mean hold force (N) and force hold SD) were collected from 60 adults (19-84 years). Non-parametric Kruskal Wallis tests were performed to identify statistical differences between force and group demographics. Non-parametric Spearman's rank correlations were completed to compare force measures against previously published sensory data from the same cohort of participants. Significant group differences in force control were found for age, sex, speech usage and smoking status. Significant correlational relationships were identified between labial vibrotactile thresholds and several low-level force control measures collected during step and ramp-and-hold conditions. These findings demonstrate age-related alterations in orofacial force production. Furthermore, correlational analysis suggests as vibrotactile detection thresholds increase, the ability to maintain low-level force control accuracy decreases. Possible clinical applications and treatment consequences of these findings for speech disorders in the ageing population are provided.

Conversion from bipolar disorder not otherwise specified (BP-NOS) to bipolar I or II in youth with family history as a predictor of conversion.

PubMed

Martinez, Molly S; Fristad, Mary A

2013-06-01

Bipolar disorder-not otherwise specified (BD-NOS) is an imprecise, heterogeneous diagnosis that is unstable in youth. This study reports rates of conversion from BD-NOS to BD-I or II in children aged 8-12, and investigates the impact of family history of bipolar disorder and depression on conversion. As part of the Multi-Family Psychoeducational Psychotherapy (MF-PEP) study, 27 children (6-12 years of age) diagnosed with BD-NOS at baseline were reassessed every 6 months over an 18-month period. Family history of bipolar disorder and depression was assessed at baseline. One-third of the sample converted from BD-NOS to BD-I or II over 18-months. Having a first-degree relative with symptoms of bipolar disorder and having a loaded pedigree for diagnosis of depression each were associated with conversion from BD-NOS to BD-I or II (odds ratio range: 1.09-3.14; relative risk range: 1.06-2.34). This study had very low power (range: 10-45) given the small sample size, precluding statistical significance of non-parametric Fisher's Exact test findings. This study replicates the previous finding of a high rate of conversion from BD-NOS to BD-I or II among youth, and suggests conversion is related to symptoms of bipolar disorder or depression diagnoses in the family history. Additional research is warranted in a larger sample with a longer follow-up period. Copyright © 2012 Elsevier B.V. All rights reserved.

Non-parametric wall model and methods of identifying boundary conditions for moments in gas flow equations

NASA Astrophysics Data System (ADS)

Liao, Meng; To, Quy-Dong; Léonard, Céline; Monchiet, Vincent

2018-03-01

In this paper, we use the molecular dynamics simulation method to study gas-wall boundary conditions. Discrete scattering information of gas molecules at the wall surface is obtained from collision simulations. The collision data can be used to identify the accommodation coefficients for parametric wall models such as Maxwell and Cercignani-Lampis scattering kernels. Since these scattering kernels are based on a limited number of accommodation coefficients, we adopt non-parametric statistical methods to construct the kernel to overcome these issues. Different from parametric kernels, the non-parametric kernels require no parameter (i.e. accommodation coefficients) and no predefined distribution. We also propose approaches to derive directly the Navier friction and Kapitza thermal resistance coefficients as well as other interface coefficients associated with moment equations from the non-parametric kernels. The methods are applied successfully to systems composed of CH4 or CO2 and graphite, which are of interest to the petroleum industry.

Parametric resonance in tunable superconducting cavities

NASA Astrophysics Data System (ADS)

Wustmann, Waltraut; Shumeiko, Vitaly

2013-05-01

We develop a theory of parametric resonance in tunable superconducting cavities. The nonlinearity introduced by the superconducting quantum interference device (SQUID) attached to the cavity and damping due to connection of the cavity to a transmission line are taken into consideration. We study in detail the nonlinear classical dynamics of the cavity field below and above the parametric threshold for the degenerate parametric resonance, featuring regimes of multistability and parametric radiation. We investigate the phase-sensitive amplification of external signals on resonance, as well as amplification of detuned signals, and relate the amplifier performance to that of linear parametric amplifiers. We also discuss applications of the device for dispersive qubit readout. Beyond the classical response of the cavity, we investigate small quantum fluctuations around the amplified classical signals. We evaluate the noise power spectrum both for the internal field in the cavity and the output field. Other quantum-statistical properties of the noise are addressed such as squeezing spectra, second-order coherence, and two-mode entanglement.

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tak, Sungho; Jang, Kwang Eun; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong; Ye, Jong Chul

2008-02-01

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

Imaging predictors of poststroke depression: methodological factors in voxel-based analysis

PubMed Central

Gozzi, Sophia A; Wood, Amanda G; Chen, Jian; Vaddadi, Krishnarao; Phan, Thanh G

2014-01-01

Objective The purpose of this study was to explore the relationship between lesion location and poststroke depression using statistical parametric mapping. Methods First episode patients with stroke were assessed within 12 days and at 1-month poststroke. Patients with an a priori defined cut-off score of 11 on the Hospital Anxiety and Depression Scale (HADS) at follow-up were further assessed using the Mini-International Neuropsychiatric Interview (MINI) to confirm a clinical diagnosis of major or minor depression in accordance with Diagnostic and Statistical Manual-IV (DSM-IV) inclusion criteria. Participants were included if they were aged 18–85 years, proficient in English and eligible for MRI. Patients were excluded if they had a confounding diagnosis such as major depressive disorder at the time of admission, a neurodegenerative disease, epilepsy or an imminently life-threatening comorbid illness, subarachnoid or subdural stroke, a second episode of stroke before follow-up and/or a serious impairment of consciousness or language. Infarcts observed on MRI scans were manually segmented into binary images, linearly registered into a common stereotaxic coordinate space. Using statistical parametric mapping, we compared infarct patterns in patients with stroke with and without depression. Results 27% (15/55 patients) met criteria for depression at follow-up. Mean infarct volume was 19±53 mL and National Institute of Health Stroke Scale (NIHSS) at Time 1 (within 12 days of stroke) was 4±4, indicating a sample of mild strokes. No voxels or clusters were significant after a multiple comparison correction was applied (p>0.05). Examination of infarct maps showed that there was minimal overlap of infarct location between patients, thus invalidating the voxel comparison analysis. Conclusions This study provided inconclusive evidence for the association between infarcts in a specific region and poststroke depression. PMID:25001395

Tomographic measurement of joint photon statistics of the twin-beam quantum state

PubMed

Vasilyev; Choi; Kumar; D'Ariano

2000-03-13

We report the first measurement of the joint photon-number probability distribution for a two-mode quantum state created by a nondegenerate optical parametric amplifier. The measured distributions exhibit up to 1.9 dB of quantum correlation between the signal and idler photon numbers, whereas the marginal distributions are thermal as expected for parametric fluorescence.

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Quantum Treatment of Two Coupled Oscillators in Interaction with a Two-Level Atom:

NASA Astrophysics Data System (ADS)

Khalil, E. M.; Abdalla, M. Sebawe; Obada, A. S.-F.

In this communication we handle a modified model representing the interaction between a two-level atom and two modes of the electromagnetic field in a cavity. The interaction between the modes is assumed to be of a parametric amplifier type. The model consists of two different systems, one represents the Jaynes-Cummings model (atom-field interaction) and the other represents the two mode parametric amplifier model (field-field interaction). After some canonical transformations the constants of the motion have been obtained and used to derive the time evolution operator. The wave function in the Schrödinger picture is constructed and employed to discuss some statistical properties related to the system. Further discussion related to the statistical properties of some physical quantities is given where we have taken into account an initial correlated pair-coherent state for the modes. We concentrate in our examination on the system behavior that occurred as a result of the variation of the parametric amplifier coupling parameter as well as the detuning parameter. It has been shown that the interaction of the parametric amplifier term increases the revival period and consequently longer period of strong interaction between the atom and the fields.

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

PubMed

Seo, Seongho; Kim, Su Jin; Lee, Dong Soo; Lee, Jae Sung

2014-10-01

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

One-dimensional statistical parametric mapping in Python.

PubMed

Pataky, Todd C

2012-01-01

Statistical parametric mapping (SPM) is a topological methodology for detecting field changes in smooth n-dimensional continua. Many classes of biomechanical data are smooth and contained within discrete bounds and as such are well suited to SPM analyses. The current paper accompanies release of 'SPM1D', a free and open-source Python package for conducting SPM analyses on a set of registered 1D curves. Three example applications are presented: (i) kinematics, (ii) ground reaction forces and (iii) contact pressure distribution in probabilistic finite element modelling. In addition to offering a high-level interface to a variety of common statistical tests like t tests, regression and ANOVA, SPM1D also emphasises fundamental concepts of SPM theory through stand-alone example scripts. Source code and documentation are available at: www.tpataky.net/spm1d/.

A Methodology for the Parametric Reconstruction of Non-Steady and Noisy Meteorological Time Series

NASA Astrophysics Data System (ADS)

Rovira, F.; Palau, J. L.; Millán, M.

2009-09-01

Climatic and meteorological time series often show some persistence (in time) in the variability of certain features. One could regard annual, seasonal and diurnal time variability as trivial persistence in the variability of some meteorological magnitudes (as, e.g., global radiation, air temperature above surface, etc.). In these cases, the traditional Fourier transform into frequency space will show the principal harmonics as the components with the largest amplitude. Nevertheless, meteorological measurements often show other non-steady (in time) variability. Some fluctuations in measurements (at different time scales) are driven by processes that prevail on some days (or months) of the year but disappear on others. By decomposing a time series into time-frequency space through the continuous wavelet transformation, one is able to determine both the dominant modes of variability and how those modes vary in time. This study is based on a numerical methodology to analyse non-steady principal harmonics in noisy meteorological time series. This methodology combines both the continuous wavelet transform and the development of a parametric model that includes the time evolution of the principal and the most statistically significant harmonics of the original time series. The parameterisation scheme proposed in this study consists of reproducing the original time series by means of a statistically significant finite sum of sinusoidal signals (waves), each defined by using the three usual parameters: amplitude, frequency and phase. To ensure the statistical significance of the parametric reconstruction of the original signal, we propose a standard statistical t-student analysis of the confidence level of the amplitude in the parametric spectrum for the different wave components. Once we have assured the level of significance of the different waves composing the parametric model, we can obtain the statistically significant principal harmonics (in time) of the original time series by using the Fourier transform of the modelled signal. Acknowledgements The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (València, Spain). This study has been partially funded by the European Commission (FP VI, Integrated Project CIRCE - No. 036961) and by the Ministerio de Ciencia e Innovación, research projects "TRANSREG” (CGL2007-65359/CLI) and "GRACCIE” (CSD2007-00067, Program CONSOLIDER-INGENIO 2010).

Normality Tests for Statistical Analysis: A Guide for Non-Statisticians

PubMed Central

Ghasemi, Asghar; Zahediasl, Saleh

2012-01-01

Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS. PMID:23843808

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease. PMID:26023913

Clinical application of 3D arterial spin-labeled brain perfusion imaging for Alzheimer disease: comparison with brain perfusion SPECT.

PubMed

Takahashi, H; Ishii, K; Hosokawa, C; Hyodo, T; Kashiwagi, N; Matsuki, M; Ashikaga, R; Murakami, T

2014-05-01

Alzheimer disease is the most common neurodegenerative disorder with dementia, and a practical and economic biomarker for diagnosis of Alzheimer disease is needed. Three-dimensional arterial spin-labeling, with its high signal-to-noise ratio, enables measurement of cerebral blood flow precisely without any extrinsic tracers. We evaluated the performance of 3D arterial spin-labeling compared with SPECT, and demonstrated the 3D arterial spin-labeled imaging characteristics in the diagnosis of Alzheimer disease. This study included 68 patients with clinically suspected Alzheimer disease who underwent both 3D arterial spin-labeling and SPECT imaging. Two readers independently assessed both images. Kendall W coefficients of concordance (K) were computed, and receiver operating characteristic analyses were performed for each reader. The differences between the images in regional perfusion distribution were evaluated by means of statistical parametric mapping, and the incidence of hypoperfusion of the cerebral watershed area, referred to as "borderzone sign" in the 3D arterial spin-labeled images, was determined. Readers showed K = 0.82/0.73 for SPECT/3D arterial spin-labeled imaging, and the respective areas under the receiver operating characteristic curve were 0.82/0.69 for reader 1 and 0.80/0.69 for reader 2. Statistical parametric mapping showed that the perisylvian and medial parieto-occipital perfusion in the arterial spin-labeled images was significantly higher than that in the SPECT images. Borderzone sign was observed on 3D arterial spin-labeling in 70% of patients misdiagnosed with Alzheimer disease. The diagnostic performance of 3D arterial spin-labeling and SPECT for Alzheimer disease was almost equivalent. Three-dimensional arterial spin-labeled imaging was more influenced by hemodynamic factors than was SPECT imaging. © 2014 by American Journal of Neuroradiology.

Statistical parametric mapping for analyzing interictal magnetoencephalography in patients with left frontal lobe epilepsy.

PubMed

Zhu, Haitao; Zhu, Jinlong; Bao, Forrest Sheng; Liu, Hongyi; Zhu, Xuchuang; Wu, Ting; Yang, Lu; Zou, Yuanjie; Zhang, Rui; Zheng, Gang

2016-01-01

Frontal lobe epilepsy is a common epileptic disorder and is characterized by recurring seizures that arise in the frontal lobes. The purpose of this study is to identify the epileptogenic regions and other abnormal regions in patients with left frontal lobe epilepsy (LFLE) based on the magnetoencephalogram (MEG), and to understand the effects of clinical variables on brain activities in patients with LFLE. Fifteen patients with LFLE (23.20 ± 8.68 years, 6 female and 9 male) and 16 healthy controls (23.13 ± 7.66 years, 6 female and 10 male) were included in resting-stage MEG examinations. Epileptogenic regions of LFLE patients were confirmed by surgery. Regional brain activations were quantified using statistical parametric mapping (SPM). The correlation between the activations of the abnormal brain regions and the clinical seizure parameters were computed for LFLE patients. Brain activations of LFLE patients were significantly elevated in left superior/middle/inferior frontal gyri, postcentral gyrus, inferior temporal gyrus, insula, parahippocampal gyrus and amygdala, including the epileptogenic regions. Remarkable decreased activations were found mainly in the left parietal gyrus and precuneus. There is a positive correlation between the duration of the epilepsy (in month) and activations of the abnormal regions, while no relation was found between age of seizure onset (year), seizure frequency and the regions of the abnormal activity of the epileptic patients. Our findings suggest that the aberrant brain activities of LFLE patients were not restricted to the epileptogenic zones. Long duration of epilepsy might induce further functional damage in patients with LFLE. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The application of statistical parametric mapping to 123I-FP-CIT SPECT in dementia with Lewy bodies, Alzheimer's disease and Parkinson's disease.

PubMed

Colloby, Sean J; O'Brien, John T; Fenwick, John D; Firbank, Michael J; Burn, David J; McKeith, Ian G; Williams, E David

2004-11-01

Dopaminergic loss can be visualised using (123)I-FP-CIT single photon emission computed tomography (SPECT) in several disorders including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Most previous SPECT studies have adopted region of interest (ROI) methods for analysis, which are subjective and operator-dependent. The purpose of this study was to investigate differences in striatal binding of (123)I-FP-CIT SPECT using the automated technique of statistical parametric mapping (SPM99) in subjects with DLB, Alzheimer's disease (AD), PD and healthy age-matched controls. This involved spatial normalisation of each subject's image to a customised template, followed by smoothing and intensity normalisation of each image to its corresponding mean occipital count per voxel. Group differences were assessed using a two-sample t test. Applying a height threshold of P

Normal Distribution of CD8+ T-Cell-Derived ELISPOT Counts within Replicates Justifies the Reliance on Parametric Statistics for Identifying Positive Responses.

PubMed

Karulin, Alexey Y; Caspell, Richard; Dittrich, Marcus; Lehmann, Paul V

2015-03-02

Accurate assessment of positive ELISPOT responses for low frequencies of antigen-specific T-cells is controversial. In particular, it is still unknown whether ELISPOT counts within replicate wells follow a theoretical distribution function, and thus whether high power parametric statistics can be used to discriminate between positive and negative wells. We studied experimental distributions of spot counts for up to 120 replicate wells of IFN-γ production by CD8+ T-cell responding to EBV LMP2A (426 - 434) peptide in human PBMC. The cells were tested in serial dilutions covering a wide range of average spot counts per condition, from just a few to hundreds of spots per well. Statistical analysis of the data using diagnostic Q-Q plots and the Shapiro-Wilk normality test showed that in the entire dynamic range of ELISPOT spot counts within replicate wells followed a normal distribution. This result implies that the Student t-Test and ANOVA are suited to identify positive responses. We also show experimentally that borderline responses can be reliably detected by involving more replicate wells, plating higher numbers of PBMC, addition of IL-7, or a combination of these. Furthermore, we have experimentally verified that the number of replicates needed for detection of weak responses can be calculated using parametric statistics.

Facilitating the Transition from Bright to Dim Environments

DTIC Science & Technology

2016-03-04

For the parametric data, a multivariate ANOVA was used in determining the systematic presence of any statistically significant performance differences...performed. All significance levels were p < 0.05, and statistical analyses were performed with the Statistical Package for Social Sciences ( SPSS ...1950. Age changes in rate and level of visual dark adaptation. Journal of Applied Physiology, 2, 407–411. Field, A. 2009. Discovering statistics

Ince-Strutt stability charts for ship parametric roll resonance in irregular waves

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Yang, He-zhen; Xiao, Fei; Xu, Pei-ji

2017-08-01

Ince-Strutt stability chart of ship parametric roll resonance in irregular waves is conducted and utilized for the exploration of the parametric roll resonance in irregular waves. Ship parametric roll resonance will lead to large amplitude roll motion and even wreck. Firstly, the equation describing the parametric roll resonance in irregular waves is derived according to Grim's effective theory and the corresponding Ince-Strutt stability charts are obtained. Secondly, the differences of stability charts for the parametric roll resonance in irregular and regular waves are compared. Thirdly, wave phases and peak periods are taken into consideration to obtain a more realistic sea condition. The influence of random wave phases should be taken into consideration when the analyzed points are located near the instability boundary. Stability charts for different wave peak periods are various. Stability charts are helpful for the parameter determination in design stage to better adapt to sailing condition. Last, ship variables are analyzed according to stability charts by a statistical approach. The increase of the metacentric height will help improve ship stability.

The Neural Correlates of Anomalous Habituation to Negative Emotional Pictures in Borderline and Avoidant Personality Disorder Patients

PubMed Central

Koenigsberg, Harold W.; Denny, Bryan T.; Fan, Jin; Liu, Xun; Guerreri, Stephanie; Jo Mayson, Sarah; Rimsky, Liza; New, Antonia S.; Goodman, Marianne; Siever, Larry J

2013-01-01

Objective Extreme emotional reactivity is a defining feature of borderline personality disorder, yet the neural-behavioral mechanisms underlying this affective instability are poorly understood. One possible contributor would be diminished ability to engage the mechanism of emotional habituation. We tested this hypothesis by examining behavioral and neural correlates of habituation in borderline patients, healthy controls, and a psychopathological control group of avoidant personality disorder patients. Method During fMRI scan acquisition, borderline patients, healthy controls and avoidant personality disorder patients viewed novel and repeated pictures, providing valence ratings at each presentation. Statistical parametric maps of the contrasts of activation during repeat versus novel negative picture viewing were compared between groups. Psychophysiological interaction analysis was employed to examine functional connectivity differences between groups. Results Unlike healthy controls, neither borderline nor avoidant personality disorder participants showed increased activity in dorsal anterior cingulate cortex when viewing repeat versus novel pictures. This failure to increase dorsal anterior cingulate activity was associated with greater affective instability in borderline participants. In addition, borderline and avoidant participants showed smaller insula-amygdala connectivity increases than healthy participants and did not show habituation in ratings of the emotional intensity of the images as did healthy participants. Borderline patients differed from avoidant patients in insula-ventral anterior cingulate connectivity during habituation. Conclusions Borderline patients fail to habituate to negative pictures as do healthy participants and differ from both healthy controls and avoidant patients in neural activity during habituation. A failure to effectively engage emotional habituation processes may contribute to affective instability in borderline patients. PMID:24275960

Abnormal regional cerebral blood flow in systemic lupus erythematosus patients with psychiatric symptoms.

PubMed

Oda, Kenji; Matsushima, Eisuke; Okubo, Yoshiro; Ohta, Katsuya; Murata, Yuji; Koike, Ryuji; Miyasaka, Nobuyuki; Kato, Motoichiro

2005-07-01

Single-photon emission computed tomography (SPECT) studies have demonstrated decreased regional cerebral blood flow (rCBF) in systemic lupus erythematosus (SLE) patients. However, no study has done voxel-based analysis using statistical parametric mapping (SPM) that can evaluate rCBF objectively, and the relationship between rCBF and psychiatric symptoms has not been well investigated. Using L,L-ethyl cysteinate dimer (99mTc ECD) SPECT and SPM, we aimed to clarify the association of rCBF changes with psychiatric symptoms in SLE patients whose magnetic resonance imaging (MRI) showed no morphological abnormalities. Twenty SLE patients and 19 healthy volunteers underwent 99mTc ECD SPECT. Data were collected from August 2000 to March 2003. SLE was diagnosed according to American College of Rheumatology criteria, and psychiatric symptoms were diagnosed according to ICD-10 criteria. On the basis of the modified Carbotte, Denburg, and Denburg method, the patients were classified into 3 groups: a group with major psychiatric symptoms (hallucinosis, delusional disorder, and mood disorder), a group with minor psychiatric symptoms (anxiety disorder, dissociative disorder, and emotionally labile disorder), and a group without psychiatric symptoms. Gross organic lesions were ruled out by brain MRI. Group comparisons of rCBF were performed with analysis using SPM99. SLE patients without MRI lesions showed decreased rCBF in the posterior cingulate gyrus and thalamus. The reduction in rCBF was overt in patients with major psychiatric symptoms. Our study indicated that SLE patients may have dysfunction in the posterior cingulate gyrus and thalamus and that this may be associated with the severity of psychiatric symptoms.

Autism Spectrum and Obsessive–Compulsive Disorders: OC Behaviors, Phenotypes and Genetics

PubMed Central

Jacob, Suma; Landeros-Weisenberger, Angeli; Leckman, James F.

2014-01-01

Autism spectrum disorders (ASDs) are a phenotypically and etiologically heterogeneous set of disorders that include obsessive–compulsive behaviors (OCB) that partially overlap with symptoms associated with obsessive–compulsive disorder (OCD). The OCB seen in ASD vary depending on the individual’s mental and chronological age as well as the etiology of their ASD. Although progress has been made in the measurement of the OCB associated with ASD, more work is needed including the potential identification of heritable endophenotypes. Likewise, important progress toward the understanding of genetic influences in ASD has been made by greater refinement of relevant phenotypes using a broad range of study designs, including twin and family-genetic studies, parametric and nonparametric linkage analyses, as well as candidate gene studies and the study of rare genetic variants. These genetic analyses could lead to the refinement of the OCB phenotypes as larger samples are studied and specific associations are replicated. Like ASD, OCB are likely to prove to be multidimensional and polygenic. Some of the vulnerability genes may prove to be generalist genes influencing the phenotypic expression of both ASD and OCD while others will be specific to subcomponents of the ASD phenotype. In order to discover molecular and genetic mechanisms, collaborative approaches need to generate shared samples, resources, novel genomic technologies, as well as more refined phenotypes and innovative statistical approaches. There is a growing need to identify the range of molecular pathways involved in OCB related to ASD in order to develop novel treatment interventions. PMID:20029829

Convergent linkage evidence from two Latin-American population isolates supports the presence of a susceptibility locus for bipolar disorder in 5q31-34.

PubMed

Herzberg, Ibi; Jasinska, Anna; García, Jenny; Jawaheer, Damini; Service, Susan; Kremeyer, Barbara; Duque, Constanza; Parra, María V; Vega, Jorge; Ortiz, Daniel; Carvajal, Luis; Polanco, Guadalupe; Restrepo, Gabriel J; López, Carlos; Palacio, Carlos; Levinson, Matthew; Aldana, Ileana; Mathews, Carol; Davanzo, Pablo; Molina, Julio; Fournier, Eduardo; Bejarano, Julio; Ramírez, Magui; Ortiz, Carmen Araya; Araya, Xinia; Sabatti, Chiara; Reus, Victor; Macaya, Gabriel; Bedoya, Gabriel; Ospina, Jorge; Freimer, Nelson; Ruiz-Linares, Andrés

2006-11-01

We performed a whole genome microsatellite marker scan in six multiplex families with bipolar (BP) mood disorder ascertained in Antioquia, a historically isolated population from North West Colombia. These families were characterized clinically using the approach employed in independent ongoing studies of BP in the closely related population of the Central Valley of Costa Rica. The most consistent linkage results from parametric and non-parametric analyses of the Colombian scan involved markers on 5q31-33, a region implicated by the previous studies of BP in Costa Rica. Because of these concordant results, a follow-up study with additional markers was undertaken in an expanded set of Colombian and Costa Rican families; this provided a genome-wide significant evidence of linkage of BPI to a candidate region of approximately 10 cM in 5q31-33 (maximum non-parametric linkage score=4.395, P<0.00004). Interestingly, this region has been implicated in several previous genetic studies of schizophrenia and psychosis, including disease association with variants of the enthoprotin and gamma-aminobutyric acid receptor genes.

Topics in Statistical Calibration

DTIC Science & Technology

2014-03-27

on a parametric bootstrap where, instead of sampling directly from the residuals , samples are drawn from a normal distribution. This procedure will...addition to centering them (Davison and Hinkley, 1997). When there are outliers in the residuals , the bootstrap distribution of x̂0 can become skewed or...based and inversion methods using the linear mixed-effects model. Then, a simple parametric bootstrap algorithm is proposed that can be used to either

A note on the correlation between circular and linear variables with an application to wind direction and air temperature data in a Mediterranean climate

NASA Astrophysics Data System (ADS)

Lototzis, M.; Papadopoulos, G. K.; Droulia, F.; Tseliou, A.; Tsiros, I. X.

2018-04-01

There are several cases where a circular variable is associated with a linear one. A typical example is wind direction that is often associated with linear quantities such as air temperature and air humidity. The analysis of a statistical relationship of this kind can be tested by the use of parametric and non-parametric methods, each of which has its own advantages and drawbacks. This work deals with correlation analysis using both the parametric and the non-parametric procedure on a small set of meteorological data of air temperature and wind direction during a summer period in a Mediterranean climate. Correlations were examined between hourly, daily and maximum-prevailing values, under typical and non-typical meteorological conditions. Both tests indicated a strong correlation between mean hourly wind directions and mean hourly air temperature, whereas mean daily wind direction and mean daily air temperature do not seem to be correlated. In some cases, however, the two procedures were found to give quite dissimilar levels of significance on the rejection or not of the null hypothesis of no correlation. The simple statistical analysis presented in this study, appropriately extended in large sets of meteorological data, may be a useful tool for estimating effects of wind on local climate studies.

Parametric analyses of summative scores may lead to conflicting inferences when comparing groups: A simulation study.

PubMed

Khan, Asaduzzaman; Chien, Chi-Wen; Bagraith, Karl S

2015-04-01

To investigate whether using a parametric statistic in comparing groups leads to different conclusions when using summative scores from rating scales compared with using their corresponding Rasch-based measures. A Monte Carlo simulation study was designed to examine between-group differences in the change scores derived from summative scores from rating scales, and those derived from their corresponding Rasch-based measures, using 1-way analysis of variance. The degree of inconsistency between the 2 scoring approaches (i.e. summative and Rasch-based) was examined, using varying sample sizes, scale difficulties and person ability conditions. This simulation study revealed scaling artefacts that could arise from using summative scores rather than Rasch-based measures for determining the changes between groups. The group differences in the change scores were statistically significant for summative scores under all test conditions and sample size scenarios. However, none of the group differences in the change scores were significant when using the corresponding Rasch-based measures. This study raises questions about the validity of the inference on group differences of summative score changes in parametric analyses. Moreover, it provides a rationale for the use of Rasch-based measures, which can allow valid parametric analyses of rating scale data.

kruX: matrix-based non-parametric eQTL discovery.

PubMed

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

Identification of trends in rainfall, rainy days and 24 h maximum rainfall over subtropical Assam in Northeast India

NASA Astrophysics Data System (ADS)

Jhajharia, Deepak; Yadav, Brijesh K.; Maske, Sunil; Chattopadhyay, Surajit; Kar, Anil K.

2012-01-01

Trends in rainfall, rainy days and 24 h maximum rainfall are investigated using the Mann-Kendall non-parametric test at twenty-four sites of subtropical Assam located in the northeastern region of India. The trends are statistically confirmed by both the parametric and non-parametric methods and the magnitudes of significant trends are obtained through the linear regression test. In Assam, the average monsoon rainfall (rainy days) during the monsoon months of June to September is about 1606 mm (70), which accounts for about 70% (64%) of the annual rainfall (rainy days). On monthly time scales, sixteen and seventeen sites (twenty-one sites each) witnessed decreasing trends in the total rainfall (rainy days), out of which one and three trends (seven trends each) were found to be statistically significant in June and July, respectively. On the other hand, seventeen sites witnessed increasing trends in rainfall in the month of September, but none were statistically significant. In December (February), eighteen (twenty-two) sites witnessed decreasing (increasing) trends in total rainfall, out of which five (three) trends were statistically significant. For the rainy days during the months of November to January, twenty-two or more sites witnessed decreasing trends in Assam, but for nine (November), twelve (January) and eighteen (December) sites, these trends were statistically significant. These observed changes in rainfall, although most time series are not convincing as they show predominantly no significance, along with the well-reported climatic warming in monsoon and post-monsoon seasons may have implications for human health and water resources management over bio-diversity rich Northeast India.

Single-arm phase II trial design under parametric cure models.

PubMed

Wu, Jianrong

2015-01-01

The current practice of designing single-arm phase II survival trials is limited under the exponential model. Trial design under the exponential model may not be appropriate when a portion of patients are cured. There is no literature available for designing single-arm phase II trials under the parametric cure model. In this paper, a test statistic is proposed, and a sample size formula is derived for designing single-arm phase II trials under a class of parametric cure models. Extensive simulations showed that the proposed test and sample size formula perform very well under different scenarios. Copyright © 2015 John Wiley & Sons, Ltd.

Appraisal of within- and between-laboratory reproducibility of non-radioisotopic local lymph node assay using flow cytometry, LLNA:BrdU-FCM: comparison of OECD TG429 performance standard and statistical evaluation.

PubMed

Yang, Hyeri; Na, Jihye; Jang, Won-Hee; Jung, Mi-Sook; Jeon, Jun-Young; Heo, Yong; Yeo, Kyung-Wook; Jo, Ji-Hoon; Lim, Kyung-Min; Bae, SeungJin

2015-05-05

Mouse local lymph node assay (LLNA, OECD TG429) is an alternative test replacing conventional guinea pig tests (OECD TG406) for the skin sensitization test but the use of a radioisotopic agent, (3)H-thymidine, deters its active dissemination. New non-radioisotopic LLNA, LLNA:BrdU-FCM employs a non-radioisotopic analog, 5-bromo-2'-deoxyuridine (BrdU) and flow cytometry. For an analogous method, OECD TG429 performance standard (PS) advises that two reference compounds be tested repeatedly and ECt(threshold) values obtained must fall within acceptable ranges to prove within- and between-laboratory reproducibility. However, this criteria is somewhat arbitrary and sample size of ECt is less than 5, raising concerns about insufficient reliability. Here, we explored various statistical methods to evaluate the reproducibility of LLNA:BrdU-FCM with stimulation index (SI), the raw data for ECt calculation, produced from 3 laboratories. Descriptive statistics along with graphical representation of SI was presented. For inferential statistics, parametric and non-parametric methods were applied to test the reproducibility of SI of a concurrent positive control and the robustness of results were investigated. Descriptive statistics and graphical representation of SI alone could illustrate the within- and between-laboratory reproducibility. Inferential statistics employing parametric and nonparametric methods drew similar conclusion. While all labs passed within- and between-laboratory reproducibility criteria given by OECD TG429 PS based on ECt values, statistical evaluation based on SI values showed that only two labs succeeded in achieving within-laboratory reproducibility. For those two labs that satisfied the within-lab reproducibility, between-laboratory reproducibility could be also attained based on inferential as well as descriptive statistics. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

It's all relative: ranking the diversity of aquatic bacterial communities.

PubMed

Shaw, Allison K; Halpern, Aaron L; Beeson, Karen; Tran, Bao; Venter, J Craig; Martiny, Jennifer B H

2008-09-01

The study of microbial diversity patterns is hampered by the enormous diversity of microbial communities and the lack of resources to sample them exhaustively. For many questions about richness and evenness, however, one only needs to know the relative order of diversity among samples rather than total diversity. We used 16S libraries from the Global Ocean Survey to investigate the ability of 10 diversity statistics (including rarefaction, non-parametric, parametric, curve extrapolation and diversity indices) to assess the relative diversity of six aquatic bacterial communities. Overall, we found that the statistics yielded remarkably similar rankings of the samples for a given sequence similarity cut-off. This correspondence, despite the different underlying assumptions of the statistics, suggests that diversity statistics are a useful tool for ranking samples of microbial diversity. In addition, sequence similarity cut-off influenced the diversity ranking of the samples, demonstrating that diversity statistics can also be used to detect differences in phylogenetic structure among microbial communities. Finally, a subsampling analysis suggests that further sequencing from these particular clone libraries would not have substantially changed the richness rankings of the samples.

A unified framework for weighted parametric multiple test procedures.

PubMed

Xi, Dong; Glimm, Ekkehard; Maurer, Willi; Bretz, Frank

2017-09-01

We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex study objectives and include many procedures in the literature as special cases. The proposed weighted parametric tests bridge the gap between rejection rules using either adjusted significance levels or adjusted p-values. This connection is made by allowing intersection hypotheses of the underlying closed test procedure to be tested at level smaller than α. This may be also necessary to take certain study situations into account. For such cases we introduce a subclass of exact α-level parametric tests that satisfy the consonance property. When the correlation is known only for certain subsets of the test statistics, a new procedure is proposed to fully utilize this knowledge within each subset. We illustrate the proposed weighted parametric tests using a clinical trial example and conduct a simulation study to investigate its operating characteristics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of a Rocket Based Combined Cycle Engine during Rocket Only Operation

NASA Technical Reports Server (NTRS)

Smith, T. D.; Steffen, C. J., Jr.; Yungster, S.; Keller, D. J.

1998-01-01

The all rocket mode of operation is a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. However, outside of performing experiments or a full three dimensional analysis, there are no first order parametric models to estimate performance. As a result, an axisymmetric RBCC engine was used to analytically determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and statistical regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, percent of injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inject diameter ratio. A perfect gas computational fluid dynamics analysis was performed to obtain values of vacuum specific impulse. Statistical regression analysis was performed based on both full flow and gas generator engine cycles. Results were also found to be dependent upon the entire cycle assumptions. The statistical regression analysis determined that there were five significant linear effects, six interactions, and one second-order effect. Two parametric models were created to provide performance assessments of an RBCC engine in the all rocket mode of operation.

Parametric study of the swimming performance of a fish robot propelled by a flexible caudal fin.

PubMed

Low, K H; Chong, C W

2010-12-01

In this paper, we aim to study the swimming performance of fish robots by using a statistical approach. A fish robot employing a carangiform swimming mode had been used as an experimental platform for the performance study. The experiments conducted aim to investigate the effect of various design parameters on the thrust capability of the fish robot with a flexible caudal fin. The controllable parameters associated with the fin include frequency, amplitude of oscillation, aspect ratio and the rigidity of the caudal fin. The significance of these parameters was determined in the first set of experiments by using a statistical approach. A more detailed parametric experimental study was then conducted with only those significant parameters. As a result, the parametric study could be completed with a reduced number of experiments and time spent. With the obtained experimental result, we were able to understand the relationship between various parameters and a possible adjustment of parameters to obtain a higher thrust. The proposed statistical method for experimentation provides an objective and thorough analysis of the effects of individual or combinations of parameters on the swimming performance. Such an efficient experimental design helps to optimize the process and determine factors that influence variability.

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

PubMed

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

Regional cerebral blood flow changes in female to male gender identity disorder.

PubMed

Nawata, Hideyuki; Ogomori, Koji; Tanaka, Mariko; Nishimura, Ryoji; Urashima, Hajime; Yano, Rika; Takano, Koichi; Kuwabara, Yasuo

2010-04-01

Despite a range of research on gender identity disorder (GID), at present there is no scientific consensus on whether the etiology of GID is mental or physical. In particular recent advances in the technology of neuroimaging research have led to an increased understanding of the biological basis of various mental disorders. GID also should be evaluated from this perspective. The aim of the present study was therefore to do the first trial to examine the regional cerebral blood flow (rCBF) in GID. Persons considered biologically male fulfilling the GID criteria are termed male to female (MTF) and, conversely, persons considered biological female are termed female to male (FTM). We compared 11 FTM subjects and nine age- and handedness-matched female control subjects. None of the subjects was regularly taking medication and none had any kind of physical or psychiatric comorbidity. To evaluate rCBF in GID subjects and control subjects, statistical parametric mapping analysis of (99m)Tc-ethyl-cysteinate dimer single-photon emission computed tomography was used. GID subjects had a significant decrease in rCBF in the left anterior cingulate cortex (ACC) and a significant increase in the right insula compared to control subjects. The ACC and insula are regions that have been noted as being related to human sexual behavior and consciousness. From these findings, useful insights into the biological basis of GID were suggested.

Parametric disordering of meta-atoms and nonlinear topological transitions in liquid metacrystals

NASA Astrophysics Data System (ADS)

Zharov, Alexander A.; Zharova, Nina A.; Zharov, Alexander A.

2017-09-01

We show that amplitude-modulated electromagnetic wave incident onto a liquid metacrystal may cause parametric instability of meta-atoms resulting in isotropization of the medium that can be treated in terms of effective temperature. It makes possible to switch the sign of certain components of dielectric permittivity and/or magnetic permeability tensors that, in turn, modifies the topology of isofrequency surface. At the same time it leads to the changes of the conditions of electromagnetic wave propagation appearing in the form of focusing or defocusing nonlinearity.

Dynamic whole body PET parametric imaging: II. Task-oriented statistical estimation

PubMed Central

Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15–20cm) of a single bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical FDG patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection. PMID:24080994

Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.

PubMed

Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical (18)F-deoxyglucose patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30 min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole-body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection.

Emulsified omega-3 fatty-acids modulate the symptoms of depressive disorder in children and adolescents: a pilot study.

PubMed

Trebatická, Jana; Hradečná, Zuzana; Böhmer, František; Vaváková, Magdaléna; Waczulíková, Iveta; Garaiova, Iveta; Luha, Ján; Škodáček, Igor; Šuba, Ján; Ďuračková, Zdeňka

2017-01-01

The prevalence of mood disorders in children is a growing global concern. Omega-3 fatty acids (FA) are emerging as a promising adjuvant therapy for depressive disorder (DD) in paediatric patients. The primary objective of this pilot, single-centre, randomized, double-blind controlled study was to compare the efficacy of an Omega-3 FA fish oil emulsion with a control oil emulsion alongside standard treatment for depressive symptoms in children and adolescents suffering from depressive disorder (DD) and mixed anxiety depressive disorder (MADD). 38 children (12 patients were treated and diagnosed for at least 1 month before enrolment, 26 patients were first-time diagnosed as DD) aged 11-17 years were randomised 1:1 to the intervention (Omega-3 FA, 19 patients) or active comparator (Omega-6 FA, 19 patients) groups. Children's depression inventory (CDI) ratings were performed at baseline, every 2 weeks for a 12-week intervention period and at 4-week post-intervention. 35 patients (17 in Omega-3 and 18 in Omega-6 groups) who completed the whole intervention period were evaluated. Patients from Omega-3 group were stratified according to diagnosis into two subgroups (DD-10/17 and mixed anxiety depressive disorder (MADD)-7/17 patients) and in the Omega-6 group into DD-10/18 and MADD-8/18 patients. Groups were evaluated separately. Differences between-groups were tested with the Student´s t test or non-parametric Mann-Whitney U test. Two-way ANOVA with repeated measures and Friedman test were used to analyse the Treatment effect for response in CDI score. p < 0.05 was considered significant in all statistical analyses. Significant reductions in CDI scores in 35 analysed patients who completed 12 weeks intervention were observed after 12 weeks of intervention only in the Omega-3 group (p = 0.034). After stratification to depressive disorder and mixed anxiety depressive disorder subgroups, the DD subgroup receiving the Omega-3 FA fish oil showed statistically greater improvement (score reduction after 8 week treatment of -9.1 CDI, p = 0.0001) when compared to the MADD subgroup (score reduction after 8 week treatment -4.24 CDI, p = 0.271). CDI scores were reduced in the Omega-3 group and the depression subgroup had greater improvement than the mixed depressive/anxiety group. An Omega-3 fatty acid rich fish oil emulsion may be an effective adjuvant supplement during the treatment of depressive disorders in children. Trial registration ISRCTN81655012.

Learning from Friends: Measuring Influence in a Dyadic Computer Instructional Setting

ERIC Educational Resources Information Center

DeLay, Dawn; Hartl, Amy C.; Laursen, Brett; Denner, Jill; Werner, Linda; Campe, Shannon; Ortiz, Eloy

2014-01-01

Data collected from partners in a dyadic instructional setting are, by definition, not statistically independent. As a consequence, conventional parametric statistical analyses of change and influence carry considerable risk of bias. In this article, we illustrate a strategy to overcome this obstacle: the longitudinal actor-partner interdependence…

Application of Transformations in Parametric Inference

ERIC Educational Resources Information Center

Brownstein, Naomi; Pensky, Marianna

2008-01-01

The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Covariate analysis of bivariate survival data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methodsmore » have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.« less

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

NASA Astrophysics Data System (ADS)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Electrical Evaluation of RCA MWS5001D Random Access Memory, Volume 4, Appendix C

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. Statistical analysis data is supplied along with write pulse width, read cycle time, write cycle time, and chip enable time data.

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

kruX: matrix-based non-parametric eQTL discovery

PubMed Central

2014-01-01

Background The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. Results We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. Conclusion kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com. PMID:24423115

[Linkage analysis of susceptibility loci in 2 target chromosomes in pedigrees with paranoid schizophrenia and undifferentiated schizophrenia].

PubMed

Zeng, Li-ping; Hu, Zheng-mao; Mu, Li-li; Mei, Gui-sen; Lu, Xiu-ling; Zheng, Yong-jun; Li, Pei-jian; Zhang, Ying-xue; Pan, Qian; Long, Zhi-gao; Dai, He-ping; Zhang, Zhuo-hua; Xia, Jia-hui; Zhao, Jing-ping; Xia, Kun

2011-06-01

To investigate the relationship of susceptibility loci in chromosomes 1q21-25 and 6p21-25 and schizophrenia subtypes in Chinese population. A genomic scan and parametric and non-parametric analyses were performed on 242 individuals from 36 schizophrenia pedigrees, including 19 paranoid schizophrenia and 17 undifferentiated schizophrenia pedigrees, from Henan province of China using 5 microsatellite markers in the chromosome region 1q21-25 and 8 microsatellite markers in the chromosome region 6p21-25, which were the candidates of previous studies. All affected subjects were diagnosed and typed according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revised (DSM-IV-TR; American Psychiatric Association, 2000). All subjects signed informed consent. In chromosome 1, parametric analysis under the dominant inheritance mode of all 36 pedigrees showed that the maximum multi-point heterogeneity Log of odds score method (HLOD) score was 1.33 (α = 0.38). The non-parametric analysis and the single point and multi-point nonparametric linkage (NPL) scores suggested linkage at D1S484, D1S2878, and D1S196. In the 19 paranoid schizophrenias pedigrees, linkage was not observed for any of the 5 markers. In the 17 undifferentiated schizophrenia pedigrees, the multi-point NPL score was 1.60 (P= 0.0367) at D1S484. The single point NPL score was 1.95(P= 0.0145) and the multi-point NPL score was 2.39 (P= 0.0041) at D1S2878. Additionally, the multi-point NPL score was 1.74 (P= 0.0255) at D1S196. These same three loci showed suggestive linkage during the integrative analysis of all 36 pedigrees. In chromosome 6, parametric linkage analysis under the dominant and recessive inheritance and the non-parametric linkage analysis of all 36 pedigrees and the 17 undifferentiated schizophrenia pedigrees, linkage was not observed for any of the 8 markers. In the 19 paranoid schizophrenias pedigrees, parametric analysis showed that under recessive inheritance mode the maximum single-point HLOD score was 1.26 (α = 0.40) and the multi-point HLOD was 1.12 (α = 0.38) at D6S289 in the chromosome 6p23. In nonparametric analysis, the single-point NPL score was 1.52 (P= 0.0402) and the multi-point NPL score was 1.92 (P= 0.0206) at D6S289. Susceptibility genes correlated with undifferentiated schizophrenia pedigrees from D1S484, D1S2878, D1S196 loci, and those correlated with paranoid schizophrenia pedigrees from D6S289 locus are likely present in chromosome regions 1q23.3 and 1q24.2, and chromosome region 6p23, respectively.

Structural covariance of neostriatal and limbic regions in patients with obsessive-compulsive disorder.

PubMed

Subirà, Marta; Cano, Marta; de Wit, Stella J; Alonso, Pino; Cardoner, Narcís; Hoexter, Marcelo Q; Kwon, Jun Soo; Nakamae, Takashi; Lochner, Christine; Sato, João R; Jung, Wi Hoon; Narumoto, Jin; Stein, Dan J; Pujol, Jesus; Mataix-Cols, David; Veltman, Dick J; Menchón, José M; van den Heuvel, Odile A; Soriano-Mas, Carles

2016-03-01

Frontostriatal and frontoamygdalar connectivity alterations in patients with obsessive-compulsive disorder (OCD) have been typically described in functional neuroimaging studies. However, structural covariance, or volumetric correlations across distant brain regions, also provides network-level information. Altered structural covariance has been described in patients with different psychiatric disorders, including OCD, but to our knowledge, alterations within frontostriatal and frontoamygdalar circuits have not been explored. We performed a mega-analysis pooling structural MRI scans from the Obsessive-compulsive Brain Imaging Consortium and assessed whole-brain voxel-wise structural covariance of 4 striatal regions (dorsal and ventral caudate nucleus, and dorsal-caudal and ventral-rostral putamen) and 2 amygdalar nuclei (basolateral and centromedial-superficial). Images were preprocessed with the standard pipeline of voxel-based morphometry studies using Statistical Parametric Mapping software. Our analyses involved 329 patients with OCD and 316 healthy controls. Patients showed increased structural covariance between the left ventral-rostral putamen and the left inferior frontal gyrus/frontal operculum region. This finding had a significant interaction with age; the association held only in the subgroup of older participants. Patients with OCD also showed increased structural covariance between the right centromedial-superficial amygdala and the ventromedial prefrontal cortex. This was a cross-sectional study. Because this is a multisite data set analysis, participant recruitment and image acquisition were performed in different centres. Most patients were taking medication, and treatment protocols differed across centres. Our results provide evidence for structural network-level alterations in patients with OCD involving 2 frontosubcortical circuits of relevance for the disorder and indicate that structural covariance contributes to fully characterizing brain alterations in patients with psychiatric disorders.

Synchronization of chaotic and nonchaotic oscillators: Application to bipolar disorder

NASA Astrophysics Data System (ADS)

Nono Dueyou Buckjohn, C.; Siewe Siewe, M.; Tchawoua, C.; Kofane, T. C.

2010-08-01

In this Letter, we use a synchronization scheme on two bipolar disorder models consisting of a strong nonlinear system with multiplicative excitation and a nonlinear oscillator without parametric harmonic forcing. The stability condition following our control function is analytically demonstrated using the Lyapunov theory and Routh-Hurwitz criteria, we then have the condition for the existence of a feedback gain matrix. A convenient demonstration of the accuracy of the method is complemented by the numerical simulations from which we illustrate the synchronized dynamics between the two non-identical bipolar disorder patients.

Two-photon Anderson localization in a disordered quadratic waveguide array

NASA Astrophysics Data System (ADS)

Bai, Y. F.; Xu, P.; Lu, L. L.; Zhong, M. L.; Zhu, S. N.

2016-05-01

We theoretically investigate two-photon Anderson localization in a χ (2) waveguide array with off-diagonal disorder. The nonlinear parametric down-conversion process would enhance both the single-photon and the two-photon Anderson localization. In the strong disorder regime, the two-photon position correlation exhibits a bunching distribution around the pumped waveguides, which is independent of pumping conditions and geometrical structures of waveguide arrays. Quadratic nonlinearity can be supplied as a new ingredient for Anderson localization. Also, our results pave the way for engineering quantum states through nonlinear quantum walks.

Genetic Algorithm Based Framework for Automation of Stochastic Modeling of Multi-Season Streamflows

NASA Astrophysics Data System (ADS)

Srivastav, R. K.; Srinivasan, K.; Sudheer, K.

2009-05-01

Synthetic streamflow data generation involves the synthesis of likely streamflow patterns that are statistically indistinguishable from the observed streamflow data. The various kinds of stochastic models adopted for multi-season streamflow generation in hydrology are: i) parametric models which hypothesize the form of the periodic dependence structure and the distributional form a priori (examples are PAR, PARMA); disaggregation models that aim to preserve the correlation structure at the periodic level and the aggregated annual level; ii) Nonparametric models (examples are bootstrap/kernel based methods), which characterize the laws of chance, describing the stream flow process, without recourse to prior assumptions as to the form or structure of these laws; (k-nearest neighbor (k-NN), matched block bootstrap (MABB)); non-parametric disaggregation model. iii) Hybrid models which blend both parametric and non-parametric models advantageously to model the streamflows effectively. Despite many of these developments that have taken place in the field of stochastic modeling of streamflows over the last four decades, accurate prediction of the storage and the critical drought characteristics has been posing a persistent challenge to the stochastic modeler. This is partly because, usually, the stochastic streamflow model parameters are estimated by minimizing a statistically based objective function (such as maximum likelihood (MLE) or least squares (LS) estimation) and subsequently the efficacy of the models is being validated based on the accuracy of prediction of the estimates of the water-use characteristics, which requires large number of trial simulations and inspection of many plots and tables. Still accurate prediction of the storage and the critical drought characteristics may not be ensured. In this study a multi-objective optimization framework is proposed to find the optimal hybrid model (blend of a simple parametric model, PAR(1) model and matched block bootstrap (MABB) ) based on the explicit objective functions of minimizing the relative bias and relative root mean square error in estimating the storage capacity of the reservoir. The optimal parameter set of the hybrid model is obtained based on the search over a multi- dimensional parameter space (involving simultaneous exploration of the parametric (PAR(1)) as well as the non-parametric (MABB) components). This is achieved using the efficient evolutionary search based optimization tool namely, non-dominated sorting genetic algorithm - II (NSGA-II). This approach helps in reducing the drudgery involved in the process of manual selection of the hybrid model, in addition to predicting the basic summary statistics dependence structure, marginal distribution and water-use characteristics accurately. The proposed optimization framework is used to model the multi-season streamflows of River Beaver and River Weber of USA. In case of both the rivers, the proposed GA-based hybrid model yields a much better prediction of the storage capacity (where simultaneous exploration of both parametric and non-parametric components is done) when compared with the MLE-based hybrid models (where the hybrid model selection is done in two stages, thus probably resulting in a sub-optimal model). This framework can be further extended to include different linear/non-linear hybrid stochastic models at other temporal and spatial scales as well.

Nonparametric predictive inference for combining diagnostic tests with parametric copula

NASA Astrophysics Data System (ADS)

Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

2017-09-01

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

Statistical parametric mapping of LORETA using high density EEG and individual MRI: application to mismatch negativities in schizophrenia.

PubMed

Park, Hae-Jeong; Kwon, Jun Soo; Youn, Tak; Pae, Ji Soo; Kim, Jae-Jin; Kim, Myung-Sun; Ha, Kyoo-Seob

2002-11-01

We describe a method for the statistical parametric mapping of low resolution electromagnetic tomography (LORETA) using high-density electroencephalography (EEG) and individual magnetic resonance images (MRI) to investigate the characteristics of the mismatch negativity (MMN) generators in schizophrenia. LORETA, using a realistic head model of the boundary element method derived from the individual anatomy, estimated the current density maps from the scalp topography of the 128-channel EEG. From the current density maps that covered the whole cortical gray matter (up to 20,000 points), volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the confounding effect of subject specific global activity. After transforming each image into a standard stereotaxic space, we carried out statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1,600 trials) under the standard tone of 1,000 Hz, 80 dB binaural stimuli with 300 msec of inter-stimulus interval, were measured in 14 right-handed schizophrenic subjects and 14 age-, gender-, and handedness-matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (P < 0. 0005). This study is the first voxel-by-voxel statistical mapping of current density using individual MRI and high-density EEG. Copyright 2002 Wiley-Liss, Inc.

Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images.

PubMed

Nillesen, Maartje M; Lopata, Richard G P; Gerrits, Inge H; Kapusta, Livia; Thijssen, Johan M; de Korte, Chris L

2008-04-01

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 x 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (sigma(2)/mu) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images.

Modeling and replicating statistical topology and evidence for CMB nonhomogeneity

PubMed Central

Agami, Sarit

2017-01-01

Under the banner of “big data,” the detection and classification of structure in extremely large, high-dimensional, data sets are two of the central statistical challenges of our times. Among the most intriguing new approaches to this challenge is “TDA,” or “topological data analysis,” one of the primary aims of which is providing nonmetric, but topologically informative, preanalyses of data which make later, more quantitative, analyses feasible. While TDA rests on strong mathematical foundations from topology, in applications, it has faced challenges due to difficulties in handling issues of statistical reliability and robustness, often leading to an inability to make scientific claims with verifiable levels of statistical confidence. We propose a methodology for the parametric representation, estimation, and replication of persistence diagrams, the main diagnostic tool of TDA. The power of the methodology lies in the fact that even if only one persistence diagram is available for analysis—the typical case for big data applications—the replications permit conventional statistical hypothesis testing. The methodology is conceptually simple and computationally practical, and provides a broadly effective statistical framework for persistence diagram TDA analysis. We demonstrate the basic ideas on a toy example, and the power of the parametric approach to TDA modeling in an analysis of cosmic microwave background (CMB) nonhomogeneity. PMID:29078301

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Parametric interactions in presence of different size colloids in semiconductor quantum plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanshpal, R., E-mail: ravivanshpal@gmail.com; Sharma, Uttam; Dubey, Swati

2015-07-31

Present work is an attempt to investigate the effect of different size colloids on parametric interaction in semiconductor quantum plasma. Inclusion of quantum effect is being done in this analysis through quantum correction term in classical hydrodynamic model of homogeneous semiconductor plasma. The effect is associated with purely quantum origin using quantum Bohm potential and quantum statistics. Colloidal size and quantum correction term modify the parametric dispersion characteristics of ion implanted semiconductor plasma medium. It is found that quantum effect on colloids is inversely proportional to their size. Moreover critical size of implanted colloids for the effective quantum correction ismore » determined which is found to be equal to the lattice spacing of the crystal.« less

Bifurcation analysis of parametrically excited bipolar disorder model

NASA Astrophysics Data System (ADS)

Nana, Laurent

2009-02-01

Bipolar II disorder is characterized by alternating hypomanic and major depressive episode. We model the periodic mood variations of a bipolar II patient with a negatively damped harmonic oscillator. The medications administrated to the patient are modeled via a forcing function that is capable of stabilizing the mood variations and of varying their amplitude. We analyze analytically, using perturbation method, the amplitude and stability of limit cycles and check this analysis with numerical simulations.

CuBe: parametric modeling of 3D foveal shape using cubic Bézier

PubMed Central

Yadav, Sunil Kumar; Motamedi, Seyedamirhosein; Oberwahrenbrock, Timm; Oertel, Frederike Cosima; Polthier, Konrad; Paul, Friedemann; Kadas, Ella Maria; Brandt, Alexander U.

2017-01-01

Optical coherence tomography (OCT) allows three-dimensional (3D) imaging of the retina, and is commonly used for assessing pathological changes of fovea and macula in many diseases. Many neuroinflammatory conditions are known to cause modifications to the fovea shape. In this paper, we propose a method for parametric modeling of the foveal shape. Our method exploits invariant features of the macula from OCT data and applies a cubic Bézier polynomial along with a least square optimization to produce a best fit parametric model of the fovea. Additionally, we provide several parameters of the foveal shape based on the proposed 3D parametric modeling. Our quantitative and visual results show that the proposed model is not only able to reconstruct important features from the foveal shape, but also produces less error compared to the state-of-the-art methods. Finally, we apply the model in a comparison of healthy control eyes and eyes from patients with neuroinflammatory central nervous system disorders and optic neuritis, and show that several derived model parameters show significant differences between the two groups. PMID:28966857

Statistical detection of systematic election irregularities

PubMed Central

Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan

2012-01-01

Democratic societies are built around the principle of free and fair elections, and that each citizen’s vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons. PMID:23010929

Statistical detection of systematic election irregularities.

PubMed

Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan

2012-10-09

Democratic societies are built around the principle of free and fair elections, and that each citizen's vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons.

Rank-based permutation approaches for non-parametric factorial designs.

PubMed

Umlauft, Maria; Konietschke, Frank; Pauly, Markus

2017-11-01

Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

Key statistical and analytical issues for evaluating treatment effects in periodontal research.

PubMed

Tu, Yu-Kang; Gilthorpe, Mark S

2012-06-01

Statistics is an indispensible tool for evaluating treatment effects in clinical research. Due to the complexities of periodontal disease progression and data collection, statistical analyses for periodontal research have been a great challenge for both clinicians and statisticians. The aim of this article is to provide an overview of several basic, but important, statistical issues related to the evaluation of treatment effects and to clarify some common statistical misconceptions. Some of these issues are general, concerning many disciplines, and some are unique to periodontal research. We first discuss several statistical concepts that have sometimes been overlooked or misunderstood by periodontal researchers. For instance, decisions about whether to use the t-test or analysis of covariance, or whether to use parametric tests such as the t-test or its non-parametric counterpart, the Mann-Whitney U-test, have perplexed many periodontal researchers. We also describe more advanced methodological issues that have sometimes been overlooked by researchers. For instance, the phenomenon of regression to the mean is a fundamental issue to be considered when evaluating treatment effects, and collinearity amongst covariates is a conundrum that must be resolved when explaining and predicting treatment effects. Quick and easy solutions to these methodological and analytical issues are not always available in the literature, and careful statistical thinking is paramount when conducting useful and meaningful research. © 2012 John Wiley & Sons A/S.

Comparison of thawing and freezing dark energy parametrizations

NASA Astrophysics Data System (ADS)

Pantazis, G.; Nesseris, S.; Perivolaropoulos, L.

2016-05-01

Dark energy equation of state w (z ) parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not both simultaneously. Fitting a data set based on a freezing model with an unsuitable (concave when increasing) w (z ) parametrization [like Chevallier-Polarski-Linder (CPL)] can lead to significant misleading features like crossing of the phantom divide line, incorrect w (z =0 ), incorrect slope, etc., that are not present in the underlying cosmological model. To demonstrate this fact we generate scattered cosmological data at both the level of w (z ) and the luminosity distance DL(z ) based on either thawing or freezing quintessence models and fit them using parametrizations of convex and of concave type. We then compare statistically significant features of the best fit w (z ) with actual features of the underlying model. We thus verify that the use of unsuitable parametrizations can lead to misleading conclusions. In order to avoid these problems it is important to either use both convex and concave parametrizations and select the one with the best χ2 or use principal component analysis thus splitting the redshift range into independent bins. In the latter case, however, significant information about the slope of w (z ) at high redshifts is lost. Finally, we propose a new family of parametrizations w (z )=w0+wa(z/1 +z )n which generalizes the CPL and interpolates between thawing and freezing parametrizations as the parameter n increases to values larger than 1.

Bootstrap versus Statistical Effect Size Corrections: A Comparison with Data from the Finding Embedded Figures Test.

ERIC Educational Resources Information Center

Thompson, Bruce; Melancon, Janet G.

Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific…

Practical application of cure mixture model for long-term censored survivor data from a withdrawal clinical trial of patients with major depressive disorder.

PubMed

Arano, Ichiro; Sugimoto, Tomoyuki; Hamasaki, Toshimitsu; Ohno, Yuko

2010-04-23

Survival analysis methods such as the Kaplan-Meier method, log-rank test, and Cox proportional hazards regression (Cox regression) are commonly used to analyze data from randomized withdrawal studies in patients with major depressive disorder. However, unfortunately, such common methods may be inappropriate when a long-term censored relapse-free time appears in data as the methods assume that if complete follow-up were possible for all individuals, each would eventually experience the event of interest. In this paper, to analyse data including such a long-term censored relapse-free time, we discuss a semi-parametric cure regression (Cox cure regression), which combines a logistic formulation for the probability of occurrence of an event with a Cox proportional hazards specification for the time of occurrence of the event. In specifying the treatment's effect on disease-free survival, we consider the fraction of long-term survivors and the risks associated with a relapse of the disease. In addition, we develop a tree-based method for the time to event data to identify groups of patients with differing prognoses (cure survival CART). Although analysis methods typically adapt the log-rank statistic for recursive partitioning procedures, the method applied here used a likelihood ratio (LR) test statistic from a fitting of cure survival regression assuming exponential and Weibull distributions for the latency time of relapse. The method is illustrated using data from a sertraline randomized withdrawal study in patients with major depressive disorder. We concluded that Cox cure regression reveals facts on who may be cured, and how the treatment and other factors effect on the cured incidence and on the relapse time of uncured patients, and that cure survival CART output provides easily understandable and interpretable information, useful both in identifying groups of patients with differing prognoses and in utilizing Cox cure regression models leading to meaningful interpretations.

A Pilot Study Evaluating the Stigma and Public Perception about the Causes of Depression and Schizophrenia.

PubMed

Khan, Tm; Hassali, Ma; Tahir, H; Khan, A

2011-01-01

To evaluate public perceptions towards the causes of depression and schizophrenia and identifications of factors resulting stigma towards mental ill. A cross-sectional study was conducted among the inhabitants of Pulau-Pinang, Malaysia in March, 2009. A 24-item questionnaire was used to obtain respondent views. A non-probability (i.e convenient sampling method) was used to approach the potential respondents. Data analysis was conducted using SPSS version 13 ®, non-parametric statistics (Chi-square) was applied to determine the association. Alpha value less than 0.05 were considered significant. One hundred respondents showed their willingness to participate in the study; overall response of the study was 40.0%. Majority 69% of the respondents were Malays, followed by Chinese and Indians. Public recognition toward depression was higher than schizophrenia. Lack of social support (X(2)= 4.832, P= 0.049), chemical imbalance in Brian (X(2)=6.132, P= 0.013*) and believes in supernatural factors (X(2)= 6.700, P= 0.050) were the commonly shared reasons for the mental disorders. Evaluation in terms of stigma revealed that majority 61 (55.0%). Individuals with mental disorders were not friendly (X(2)= 1.008, P= 0.050). Furthermore, one third of the population believe that they are moody, dangerous and unpredictable, it is better to avoid them. Overall findings revealed that Malaysians believe in supernatural reasons for the prevalence of mental disorders. Similarly the level of stigma towards mentally ill was higher among the respondents.

Parent-Of-Origin Effects in Autism Identified through Genome-Wide Linkage Analysis of 16,000 SNPs

PubMed Central

Fradin, Delphine; Cheslack-Postava, Keely; Ladd-Acosta, Christine; Newschaffer, Craig; Chakravarti, Aravinda; Arking, Dan E.; Feinberg, Andrew; Fallin, M. Daniele

2010-01-01

Background Autism is a common heritable neurodevelopmental disorder with complex etiology. Several genome-wide linkage and association scans have been carried out to identify regions harboring genes related to autism or autism spectrum disorders, with mixed results. Given the overlap in autism features with genetic abnormalities known to be associated with imprinting, one possible reason for lack of consistency would be the influence of parent-of-origin effects that may mask the ability to detect linkage and association. Methods and Findings We have performed a genome-wide linkage scan that accounts for potential parent-of-origin effects using 16,311 SNPs among families from the Autism Genetic Resource Exchange (AGRE) and the National Institute of Mental Health (NIMH) autism repository. We report parametric (GH, Genehunter) and allele-sharing linkage (Aspex) results using a broad spectrum disorder case definition. Paternal-origin genome-wide statistically significant linkage was observed on chromosomes 4 (LODGH = 3.79, empirical p<0.005 and LODAspex = 2.96, p = 0.008), 15 (LODGH = 3.09, empirical p<0.005 and LODAspex = 3.62, empirical p = 0.003) and 20 (LODGH = 3.36, empirical p<0.005 and LODAspex = 3.38, empirical p = 0.006). Conclusions These regions may harbor imprinted sites associated with the development of autism and offer fruitful domains for molecular investigation into the role of epigenetic mechanisms in autism. PMID:20824079

A model to characterize psychopathological features in adults with Prader-Willi syndrome.

PubMed

Thuilleaux, Denise; Laurier, Virginie; Copet, Pierre; Tricot, Julie; Demeer, Geneviève; Mourre, Fabien; Tauber, Maithé; Jauregi, Joseba

2018-01-01

High prevalence of behavioral and psychiatric disorders in adults with Prader-Willi Syndrome (PWS) has been reported in last few years. However, data are confusing and often contradictory. In this article, we propose a model to achieve a better understanding of the psychopathological features in adults with PWS. The study is based on clinical observations of 150 adult inpatients, males and females. Non-parametric statistics were performed to analyse the association of psychopathological profiles with genotype, gender and age. We propose a model of psychiatric disorders in adults with PWS based on cognitive, emotional and behavioural issues. This model defines four psychopathological profiles: Basic, Impulsive, Compulsive, and Psychotic. The Basic profile is defined by traits and symptoms that are present in varying degrees in all persons with PWS. In our cohort, this Basic profile corresponds to 55% of the patients. The rest show, in addition to these characteristics, salient features of impulsivity (Impulsive profile, 19%), compulsivity (Compulsive profile, 7%), or psychosis (Psychotic profile, 19%). The analysis of factors associated with different profiles reveals an effect of genotype on Basic and Psychotic profiles (Deletion: 70% Basic, 9% Psychotic; Non-deletion: 23% Basic, 43% Psychotic) and a positive correlation between male sex and impulsivity, unmediated by sex hormone treatment. This is a clinical study, based on observation proposing an original model to understand the psychiatric and behavioural disorders in adults with PWS. Further studies are needed in order to test the validity of this model. © 2017 Wiley Periodicals, Inc.

Trans-dimensional inversion of microtremor array dispersion data with hierarchical autoregressive error models

NASA Astrophysics Data System (ADS)

Dettmer, Jan; Molnar, Sheri; Steininger, Gavin; Dosso, Stan E.; Cassidy, John F.

2012-02-01

This paper applies a general trans-dimensional Bayesian inference methodology and hierarchical autoregressive data-error models to the inversion of microtremor array dispersion data for shear wave velocity (vs) structure. This approach accounts for the limited knowledge of the optimal earth model parametrization (e.g. the number of layers in the vs profile) and of the data-error statistics in the resulting vs parameter uncertainty estimates. The assumed earth model parametrization influences estimates of parameter values and uncertainties due to different parametrizations leading to different ranges of data predictions. The support of the data for a particular model is often non-unique and several parametrizations may be supported. A trans-dimensional formulation accounts for this non-uniqueness by including a model-indexing parameter as an unknown so that groups of models (identified by the indexing parameter) are considered in the results. The earth model is parametrized in terms of a partition model with interfaces given over a depth-range of interest. In this work, the number of interfaces (layers) in the partition model represents the trans-dimensional model indexing. In addition, serial data-error correlations are addressed by augmenting the geophysical forward model with a hierarchical autoregressive error model that can account for a wide range of error processes with a small number of parameters. Hence, the limited knowledge about the true statistical distribution of data errors is also accounted for in the earth model parameter estimates, resulting in more realistic uncertainties and parameter values. Hierarchical autoregressive error models do not rely on point estimates of the model vector to estimate data-error statistics, and have no requirement for computing the inverse or determinant of a data-error covariance matrix. This approach is particularly useful for trans-dimensional inverse problems, as point estimates may not be representative of the state space that spans multiple subspaces of different dimensionalities. The order of the autoregressive process required to fit the data is determined here by posterior residual-sample examination and statistical tests. Inference for earth model parameters is carried out on the trans-dimensional posterior probability distribution by considering ensembles of parameter vectors. In particular, vs uncertainty estimates are obtained by marginalizing the trans-dimensional posterior distribution in terms of vs-profile marginal distributions. The methodology is applied to microtremor array dispersion data collected at two sites with significantly different geology in British Columbia, Canada. At both sites, results show excellent agreement with estimates from invasive measurements.

Linkage mapping of beta 2 EEG waves via non-parametric regression.

PubMed

Ghosh, Saurabh; Begleiter, Henri; Porjesz, Bernice; Chorlian, David B; Edenberg, Howard J; Foroud, Tatiana; Goate, Alison; Reich, Theodore

2003-04-01

Parametric linkage methods for analyzing quantitative trait loci are sensitive to violations in trait distributional assumptions. Non-parametric methods are relatively more robust. In this article, we modify the non-parametric regression procedure proposed by Ghosh and Majumder [2000: Am J Hum Genet 66:1046-1061] to map Beta 2 EEG waves using genome-wide data generated in the COGA project. Significant linkage findings are obtained on chromosomes 1, 4, 5, and 15 with findings at multiple regions on chromosomes 4 and 15. We analyze the data both with and without incorporating alcoholism as a covariate. We also test for epistatic interactions between regions of the genome exhibiting significant linkage with the EEG phenotypes and find evidence of epistatic interactions between a region each on chromosome 1 and chromosome 4 with one region on chromosome 15. While regressing out the effect of alcoholism does not affect the linkage findings, the epistatic interactions become statistically insignificant. Copyright 2003 Wiley-Liss, Inc.

Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat

PubMed Central

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-01-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

PubMed

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Low regional cerebral blood flow in burning mouth syndrome patients with depression.

PubMed

Liu, B-L; Yao, H; Zheng, X-J; Du, G-H; Shen, X-M; Zhou, Y-M; Tang, G-Y

2015-07-01

The main aims of this study were to (i) investigate the emotional disorder status of patients with burning mouth syndrome (BMS) and (ii) detect regional cerebral blood flow in BMS patients with the application of combined single-photon emission computed tomography and computed tomography (SPECT/CT). The degree of pain was measured using the visual analysis scale, and emotional disorder with the self-rating anxiety scale, self-rating depression scale, and Hamilton depression rating scale in 29 patients with BMS and 10 healthy controls. SPECT/CT was performed in 29 patients with BMS and 10 healthy controls, and statistical parametric mapping method was used for between-group analyses. The incidence rate of depression in patients with BMS was 31.0%. Compared to the control group, patients with BMS displayed significantly different depression and anxiety scales (P < 0.05). Significantly lower regional cerebral blood flow in the left parietal and left temporal lobes was recorded for BMS patients with depression (P < 0.05). Patients with BMS experience more depression and anxious emotion. Moreover, depression in patients with BMS may be associated with lower regional cerebral blood flow in the left temporal and left parietal lobes. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The role of sexual abuse on functional neuroimaging markers associated with major depressive disorder.

PubMed

Skokauskas, Norbert; Carballedo, Angela; Fagan, Andrew; Frodl, Thomas

2015-10-01

Victims of child sexual abuse can develop depression and other mental health conditions that follow them well into adulthood. This study aimed to clarify the role of sexual abuse (SA) on functional imaging markers associated with MDD. Thirty-seven patients with MDD only; and 13 patients with both MDD and SA and 43 healthy controls performed emotional attention shifting tasks during fMRI session. Clinical diagnoses were made by consultant psychiatrists based on the DSM-IV-TR criteria and diagnoses were confirmed using SCID-I. Magnetic resonance images were obtained with a Philips Achieva 3 Tesla MRI scanner. Short form childhood trauma questionnaire, Hamilton Rating Scale for Depression and Beck's Depression Inventory were also employed. Data were analysed with Statistical Parametric Mapping 8 (SPM8). Using the contrast judgment of emotion minus judgment of geometry following emotional neutral stimuli, patients with MDD showed significantly reduced activation in comparison to healthy controls in the area of the right fusiform gyrus. With the contrast judgment of emotion minus judgment of geometry following emotional negative stimuli, participants with MDD and SA showed significantly higher activation in the area of the left inferior parietal lobe in comparison to participants with MDD without SA. The history of sexual abuse affects functional neuroimaging markers associated with major depressive disorder.

Weibull mixture regression for marginal inference in zero-heavy continuous outcomes.

PubMed

Gebregziabher, Mulugeta; Voronca, Delia; Teklehaimanot, Abeba; Santa Ana, Elizabeth J

2017-06-01

Continuous outcomes with preponderance of zero values are ubiquitous in data that arise from biomedical studies, for example studies of addictive disorders. This is known to lead to violation of standard assumptions in parametric inference and enhances the risk of misleading conclusions unless managed properly. Two-part models are commonly used to deal with this problem. However, standard two-part models have limitations with respect to obtaining parameter estimates that have marginal interpretation of covariate effects which are important in many biomedical applications. Recently marginalized two-part models are proposed but their development is limited to log-normal and log-skew-normal distributions. Thus, in this paper, we propose a finite mixture approach, with Weibull mixture regression as a special case, to deal with the problem. We use extensive simulation study to assess the performance of the proposed model in finite samples and to make comparisons with other family of models via statistical information and mean squared error criteria. We demonstrate its application on real data from a randomized controlled trial of addictive disorders. Our results show that a two-component Weibull mixture model is preferred for modeling zero-heavy continuous data when the non-zero part are simulated from Weibull or similar distributions such as Gamma or truncated Gauss.

Neural basis of anxiolytic effects of cannabidiol (CBD) in generalized social anxiety disorder: a preliminary report.

PubMed

Crippa, José Alexandre S; Derenusson, Guilherme Nogueira; Ferrari, Thiago Borduqui; Wichert-Ana, Lauro; Duran, Fábio L S; Martin-Santos, Rocio; Simões, Marcus Vinícius; Bhattacharyya, Sagnik; Fusar-Poli, Paolo; Atakan, Zerrin; Santos Filho, Alaor; Freitas-Ferrari, Maria Cecília; McGuire, Philip K; Zuardi, Antonio Waldo; Busatto, Geraldo F; Hallak, Jaime Eduardo Cecílio

2011-01-01

Animal and human studies indicate that cannabidiol (CBD), a major constituent of cannabis, has anxiolytic properties. However, no study to date has investigated the effects of this compound on human pathological anxiety and its underlying brain mechanisms. The aim of the present study was to investigate this in patients with generalized social anxiety disorder (SAD) using functional neuroimaging. Regional cerebral blood flow (rCBF) at rest was measured twice using (99m)Tc-ECD SPECT in 10 treatment-naïve patients with SAD. In the first session, subjects were given an oral dose of CBD (400 mg) or placebo, in a double-blind procedure. In the second session, the same procedure was performed using the drug that had not been administered in the previous session. Within-subject between-condition rCBF comparisons were performed using statistical parametric mapping. Relative to placebo, CBD was associated with significantly decreased subjective anxiety (p < 0.001), reduced ECD uptake in the left parahippocampal gyrus, hippocampus, and inferior temporal gyrus (p < 0.001, uncorrected), and increased ECD uptake in the right posterior cingulate gyrus (p < 0.001, uncorrected). These results suggest that CBD reduces anxiety in SAD and that this is related to its effects on activity in limbic and paralimbic brain areas.

Cortical Thinning in Patients with Recent Onset Post-Traumatic Stress Disorder after a Single Prolonged Trauma Exposure

PubMed Central

Liu, Yang; Li, Yi-Jun; Luo, Er-Ping; Lu, Hong-Bing; Yin, Hong

2012-01-01

Most of magnetic resonance imaging (MRI) studies about post-traumatic stress disorder (PTSD) focused primarily on measuring of small brain structure volume or regional brain volume changes. There were rare reports investigating cortical thickness alterations in recent onset PTSD. Recent advances in computational analysis made it possible to measure cortical thickness in a fully automatic way, along with voxel-based morphometry (VBM) that enables an exploration of global structural changes throughout the brain by applying statistical parametric mapping (SPM) to high-resolution MRI. In this paper, Laplacian method was utilized to estimate cortical thickness after automatic segmentation of gray matter from MR images under SPM. Then thickness maps were analyzed by SPM8. Comparison between 10 survivors from a mining disaster with recent onset PTSD and 10 survivors without PTSD from the same trauma indicates cortical thinning in the left parietal lobe, right inferior frontal gyrus, and right parahippocampal gyrus. The regional cortical thickness of the right inferior frontal gyrus showed a significant negative correlation with the CAPS score in the patients with PTSD. Our study suggests that shape-related cortical thickness analysis may be more sensitive than volumetric analysis to subtle alteration at early stage of PTSD. PMID:22720021

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2014-01-01

Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

A general framework for parametric survival analysis.

PubMed

Crowther, Michael J; Lambert, Paul C

2014-12-30

Parametric survival models are being increasingly used as an alternative to the Cox model in biomedical research. Through direct modelling of the baseline hazard function, we can gain greater understanding of the risk profile of patients over time, obtaining absolute measures of risk. Commonly used parametric survival models, such as the Weibull, make restrictive assumptions of the baseline hazard function, such as monotonicity, which is often violated in clinical datasets. In this article, we extend the general framework of parametric survival models proposed by Crowther and Lambert (Journal of Statistical Software 53:12, 2013), to incorporate relative survival, and robust and cluster robust standard errors. We describe the general framework through three applications to clinical datasets, in particular, illustrating the use of restricted cubic splines, modelled on the log hazard scale, to provide a highly flexible survival modelling framework. Through the use of restricted cubic splines, we can derive the cumulative hazard function analytically beyond the boundary knots, resulting in a combined analytic/numerical approach, which substantially improves the estimation process compared with only using numerical integration. User-friendly Stata software is provided, which significantly extends parametric survival models available in standard software. Copyright © 2014 John Wiley & Sons, Ltd.

Software Reliability 2002

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

In FY01 we learned that hardware reliability models need substantial changes to account for differences in software, thus making software reliability measurements more effective, accurate, and easier to apply. These reliability models are generally based on familiar distributions or parametric methods. An obvious question is 'What new statistical and probability models can be developed using non-parametric and distribution-free methods instead of the traditional parametric method?" Two approaches to software reliability engineering appear somewhat promising. The first study, begin in FY01, is based in hardware reliability, a very well established science that has many aspects that can be applied to software. This research effort has investigated mathematical aspects of hardware reliability and has identified those applicable to software. Currently the research effort is applying and testing these approaches to software reliability measurement, These parametric models require much project data that may be difficult to apply and interpret. Projects at GSFC are often complex in both technology and schedules. Assessing and estimating reliability of the final system is extremely difficult when various subsystems are tested and completed long before others. Parametric and distribution free techniques may offer a new and accurate way of modeling failure time and other project data to provide earlier and more accurate estimates of system reliability.

Heating and thermal squeezing in parametrically driven oscillators with added noise.

PubMed

Batista, Adriano A

2012-11-01

In this paper we report a theoretical model based on Green's functions, Floquet theory, and averaging techniques up to second order that describes the dynamics of parametrically driven oscillators with added thermal noise. Quantitative estimates for heating and quadrature thermal noise squeezing near and below the transition line of the first parametric instability zone of the oscillator are given. Furthermore, we give an intuitive explanation as to why heating and thermal squeezing occur. For small amplitudes of the parametric pump the Floquet multipliers are complex conjugate of each other with a constant magnitude. As the pump amplitude is increased past a threshold value in the stable zone near the first parametric instability, the two Floquet multipliers become real and have different magnitudes. This creates two different effective dissipation rates (one smaller and the other larger than the real dissipation rate) along the stable manifolds of the first-return Poincaré map. We also show that the statistical average of the input power due to thermal noise is constant and independent of the pump amplitude and frequency. The combination of these effects causes most of heating and thermal squeezing. Very good agreement between analytical and numerical estimates of the thermal fluctuations is achieved.

Parametric-Studies and Data-Plotting Modules for the SOAP

NASA Technical Reports Server (NTRS)

2008-01-01

"Parametric Studies" and "Data Table Plot View" are the names of software modules in the Satellite Orbit Analysis Program (SOAP). Parametric Studies enables parameterization of as many as three satellite or ground-station attributes across a range of values and computes the average, minimum, and maximum of a specified metric, the revisit time, or 21 other functions at each point in the parameter space. This computation produces a one-, two-, or three-dimensional table of data representing statistical results across the parameter space. Inasmuch as the output of a parametric study in three dimensions can be a very large data set, visualization is a paramount means of discovering trends in the data (see figure). Data Table Plot View enables visualization of the data table created by Parametric Studies or by another data source: this module quickly generates a display of the data in the form of a rotatable three-dimensional-appearing plot, making it unnecessary to load the SOAP output data into a separate plotting program. The rotatable three-dimensionalappearing plot makes it easy to determine which points in the parameter space are most desirable. Both modules provide intuitive user interfaces for ease of use.

Differential diagnosis of normal pressure hydrocephalus by MRI mean diffusivity histogram analysis.

PubMed

Ivkovic, M; Liu, B; Ahmed, F; Moore, D; Huang, C; Raj, A; Kovanlikaya, I; Heier, L; Relkin, N

2013-01-01

Accurate diagnosis of normal pressure hydrocephalus is challenging because the clinical symptoms and radiographic appearance of NPH often overlap those of other conditions, including age-related neurodegenerative disorders such as Alzheimer and Parkinson diseases. We hypothesized that radiologic differences between NPH and AD/PD can be characterized by a robust and objective MR imaging DTI technique that does not require intersubject image registration or operator-defined regions of interest, thus avoiding many pitfalls common in DTI methods. We collected 3T DTI data from 15 patients with probable NPH and 25 controls with AD, PD, or dementia with Lewy bodies. We developed a parametric model for the shape of intracranial mean diffusivity histograms that separates brain and ventricular components from a third component composed mostly of partial volume voxels. To accurately fit the shape of the third component, we constructed a parametric function named the generalized Voss-Dyke function. We then examined the use of the fitting parameters for the differential diagnosis of NPH from AD, PD, and DLB. Using parameters for the MD histogram shape, we distinguished clinically probable NPH from the 3 other disorders with 86% sensitivity and 96% specificity. The technique yielded 86% sensitivity and 88% specificity when differentiating NPH from AD only. An adequate parametric model for the shape of intracranial MD histograms can distinguish NPH from AD, PD, or DLB with high sensitivity and specificity.

Parametric reduced models for the nonlinear Schrödinger equation

NASA Astrophysics Data System (ADS)

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Parametric reduced models for the nonlinear Schrödinger equation.

PubMed

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Non-classical Signature of Parametric Fluorescence and its Application in Metrology

NASA Astrophysics Data System (ADS)

Hamar, M.; Michálek, V.; Pathak, A.

2014-08-01

The article provides a short theoretical background of what the non-classical light means. We applied the criterion for the existence of non-classical effects derived by C.T. Lee on parametric fluorescence. The criterion was originally derived for the study of two light beams with one mode per beam. We checked if the criterion is still working for two multimode beams of parametric down-conversion through numerical simulations. The theoretical results were tested by measurement of photon number statistics of twin beams emitted by nonlinear BBO crystal pumped by intense femtoseconds UV pulse. We used ICCD camera as the detector of photons in both beams. It appears that the criterion can be used for the measurement of the quantum efficiencies of the ICCD cameras.

Relationship between regional cerebral metabolism and consciousness disturbance in traumatic diffuse brain injury without large focal lesions: an FDG-PET study with statistical parametric mapping analysis.

PubMed

Nakayama, N; Okumura, A; Shinoda, J; Nakashima, T; Iwama, T

2006-07-01

The cerebral metabolism of patients in the chronic stage of traumatic diffuse brain injury (TDBI) has not been fully investigated. To study the relationship between regional cerebral metabolism (rCM) and consciousness disturbance in patients with TDBI. 52 patients with TDBI in the chronic stage without large focal lesions were enrolled, and rCM was evaluated by fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) with statistical parametric mapping (SPM). All the patients were found to have disturbed consciousness or cognitive function and were divided into the following three groups: group A (n = 22), patients in a state with higher brain dysfunction; group B (n = 13), patients in a minimally conscious state; and group C (n = 17), patients in a vegetative state. rCM patterns on FDG-PET among these groups were evaluated and compared with those of normal control subjects on statistical parametric maps. Hypometabolism was consistently indicated bilaterally in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus. Hypometabolism in these regions was the most widespread and prominent in group C, and that in group B was more widespread and prominent than that in group A. Bilateral hypometabolism in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus may reflect the clinical deterioration of TDBI, which is due to functional and structural disconnections of neural networks rather than due to direct cerebral focal contusion.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

Biotrichotomy: The Neuroscientific and Neurobiological Systemology, Epistemology, and Methodology of the Tri-Squared Test and Tri-Center Analysis in Biostatistics

ERIC Educational Resources Information Center

Osler, James Edward

2015-01-01

This monograph provides a neuroscience-based systemological, epistemological, and methodological rational for the design of an advanced and novel parametric statistical analytics designed for the biological sciences referred to as "Biotrichotomy". The aim of this new arena of statistics is to provide dual metrics designed to analyze the…

Statistical Theory for the "RCT-YES" Software: Design-Based Causal Inference for RCTs. NCEE 2015-4011

ERIC Educational Resources Information Center

Schochet, Peter Z.

2015-01-01

This report presents the statistical theory underlying the "RCT-YES" software that estimates and reports impacts for RCTs for a wide range of designs used in social policy research. The report discusses a unified, non-parametric design-based approach for impact estimation using the building blocks of the Neyman-Rubin-Holland causal…

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation.

PubMed

Ghaffari, Mahsa; Tangen, Kevin; Alaraj, Ali; Du, Xinjian; Charbel, Fady T; Linninger, Andreas A

2017-12-01

In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical Parametric Mapping to Identify Differences between Consensus-Based Joint Patterns during Gait in Children with Cerebral Palsy.

PubMed

Nieuwenhuys, Angela; Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne

2017-01-01

Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study. Based on these findings, suggestions to improve pattern definitions were made.

Statistical Parametric Mapping to Identify Differences between Consensus-Based Joint Patterns during Gait in Children with Cerebral Palsy

PubMed Central

Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne

2017-01-01

Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with ‘no or minor gait deviations’ (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with ‘no or minor gait deviations’ differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study. Based on these findings, suggestions to improve pattern definitions were made. PMID:28081229

SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

PubMed

Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

2007-05-01

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

Sex-related differences in sleep slow wave activity in major depressive disorder: a high-density EEG investigation.

PubMed

Plante, David T; Landsness, Eric C; Peterson, Michael J; Goldstein, Michael R; Riedner, Brady A; Wanger, Timothy; Guokas, Jeffrey J; Tononi, Giulio; Benca, Ruth M

2012-09-18

Sleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder. All-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data. As a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night. Women, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

Tips and Tricks for Successful Application of Statistical Methods to Biological Data.

PubMed

Schlenker, Evelyn

2016-01-01

This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.

Age-dependent biochemical quantities: an approach for calculating reference intervals.

PubMed

Bjerner, J

2007-01-01

A parametric method is often preferred when calculating reference intervals for biochemical quantities, as non-parametric methods are less efficient and require more observations/study subjects. Parametric methods are complicated, however, because of three commonly encountered features. First, biochemical quantities seldom display a Gaussian distribution, and there must either be a transformation procedure to obtain such a distribution or a more complex distribution has to be used. Second, biochemical quantities are often dependent on a continuous covariate, exemplified by rising serum concentrations of MUC1 (episialin, CA15.3) with increasing age. Third, outliers often exert substantial influence on parametric estimations and therefore need to be excluded before calculations are made. The International Federation of Clinical Chemistry (IFCC) currently recommends that confidence intervals be calculated for the reference centiles obtained. However, common statistical packages allowing for the adjustment of a continuous covariate do not make this calculation. In the method described in the current study, Tukey's fence is used to eliminate outliers and two-stage transformations (modulus-exponential-normal) in order to render Gaussian distributions. Fractional polynomials are employed to model functions for mean and standard deviations dependent on a covariate, and the model is selected by maximum likelihood. Confidence intervals are calculated for the fitted centiles by combining parameter estimation and sampling uncertainties. Finally, the elimination of outliers was made dependent on covariates by reiteration. Though a good knowledge of statistical theory is needed when performing the analysis, the current method is rewarding because the results are of practical use in patient care.

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

PubMed

Tendeiro, Jorge N

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

Systematic Review of Video-Based Instruction Component and Parametric Analyses

ERIC Educational Resources Information Center

Bennett, Kyle D.; Aljehany, Mashal Salman; Altaf, Enas Mohammednour

2017-01-01

Video-based instruction (VBI) has a substantial amount of research supporting its use with individuals with autism spectrum disorder and other developmental disabilities. However, it has typically been implemented as a treatment package containing multiple interventions. Additionally, there are procedural variations of VBI. Thus, it is difficult…

Sensitivity of the Halstead and Wechsler Test Batteries to brain damage: Evidence from Reitan's original validation sample.

PubMed

Loring, David W; Larrabee, Glenn J

2006-06-01

The Halstead-Reitan Battery has been instrumental in the development of neuropsychological practice in the United States. Although Reitan administered both the Wechsler-Bellevue Intelligence Scale and Halstead's test battery when evaluating Halstead's theory of biologic intelligence, the relative sensitivity of each test battery to brain damage continues to be an area of controversy. Because Reitan did not perform direct parametric analysis to contrast group performances, we reanalyze Reitan's original validation data from both Halstead (Reitan, 1955) and Wechsler batteries (Reitan, 1959a) and calculate effect sizes and probability levels using traditional parametric approaches. Eight of the 10 tests comprising Halstead's original Impairment Index, as well as the Impairment Index itself, statistically differentiated patients with unequivocal brain damage from controls. In addition, 13 of 14 Wechsler measures including Full-Scale IQ also differed statistically between groups (Brain Damage Full-Scale IQ = 96.2; Control Group Full Scale IQ = 112.6). We suggest that differences in the statistical properties of each battery (e.g., raw scores vs. standardized scores) likely contribute to classification characteristics including test sensitivity and specificity.

A Monte Carlo Study of the Effect of Item Characteristic Curve Estimation on the Accuracy of Three Person-Fit Statistics

ERIC Educational Resources Information Center

St-Onge, Christina; Valois, Pierre; Abdous, Belkacem; Germain, Stephane

2009-01-01

To date, there have been no studies comparing parametric and nonparametric Item Characteristic Curve (ICC) estimation methods on the effectiveness of Person-Fit Statistics (PFS). The primary aim of this study was to determine if the use of ICCs estimated by nonparametric methods would increase the accuracy of item response theory-based PFS for…

The Importance of Practice in the Development of Statistics.

DTIC Science & Technology

1983-01-01

RESOLUTION TEST CHART NATIONAL BUREAU OIF STANDARDS 1963 -A NRC Technical Summary Report #2471 C THE IMORTANCE OF PRACTICE IN to THE DEVELOPMENT OF STATISTICS...component analysis, bioassay, limits for a ratio, quality control, sampling inspection, non-parametric tests , transformation theory, ARIMA time series...models, sequential tests , cumulative sum charts, data analysis plotting techniques, and a resolution of the Bayes - frequentist controversy. It appears

Statistical Analysis of the Exchange Rate of Bitcoin.

PubMed

Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

2015-01-01

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.

Cost model validation: a technical and cultural approach

NASA Technical Reports Server (NTRS)

Hihn, J.; Rosenberg, L.; Roust, K.; Warfield, K.

2001-01-01

This paper summarizes how JPL's parametric mission cost model (PMCM) has been validated using both formal statistical methods and a variety of peer and management reviews in order to establish organizational acceptance of the cost model estimates.

Perceptual reversals during binocular rivalry: ERP components and their concomitant source differences.

PubMed

Britz, Juliane; Pitts, Michael A

2011-11-01

We used an intermittent stimulus presentation to investigate event-related potential (ERP) components associated with perceptual reversals during binocular rivalry. The combination of spatiotemporal ERP analysis with source imaging and statistical parametric mapping of the concomitant source differences yielded differences in three time windows: reversals showed increased activity in early visual (∼120 ms) and in inferior frontal and anterior temporal areas (∼400-600 ms) and decreased activity in the ventral stream (∼250-350 ms). The combination of source imaging and statistical parametric mapping suggests that these differences were due to differences in generator strength and not generator configuration, unlike the initiation of reversals in right inferior parietal areas. These results are discussed within the context of the extensive network of brain areas that has been implicated in the initiation, implementation, and appraisal of bistable perceptual reversals. Copyright © 2011 Society for Psychophysiological Research.

Parametric distribution approach for flow availability in small hydro potential analysis

NASA Astrophysics Data System (ADS)

Abdullah, Samizee; Basri, Mohd Juhari Mat; Jamaluddin, Zahrul Zamri; Azrulhisham, Engku Ahmad; Othman, Jamel

2016-10-01

Small hydro system is one of the important sources of renewable energy and it has been recognized worldwide as clean energy sources. Small hydropower generation system uses the potential energy in flowing water to produce electricity is often questionable due to inconsistent and intermittent of power generated. Potential analysis of small hydro system which is mainly dependent on the availability of water requires the knowledge of water flow or stream flow distribution. This paper presented the possibility of applying Pearson system for stream flow availability distribution approximation in the small hydro system. By considering the stochastic nature of stream flow, the Pearson parametric distribution approximation was computed based on the significant characteristic of Pearson system applying direct correlation between the first four statistical moments of the distribution. The advantage of applying various statistical moments in small hydro potential analysis will have the ability to analyze the variation shapes of stream flow distribution.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Preclinical evaluation of parametric image reconstruction of [18F]FMISO PET: correlation with ex vivo immunohistochemistry

NASA Astrophysics Data System (ADS)

Cheng, Xiaoyin; Bayer, Christine; Maftei, Constantin-Alin; Astner, Sabrina T.; Vaupel, Peter; Ziegler, Sibylle I.; Shi, Kuangyu

2014-01-01

Compared to indirect methods, direct parametric image reconstruction (PIR) has the advantage of high quality and low statistical errors. However, it is not yet clear if this improvement in quality is beneficial for physiological quantification. This study aimed to evaluate direct PIR for the quantification of tumor hypoxia using the hypoxic fraction (HF) assessed from immunohistological data as a physiological reference. Sixteen mice with xenografted human squamous cell carcinomas were scanned with dynamic [18F]FMISO PET. Afterward, tumors were sliced and stained with H&E and the hypoxia marker pimonidazole. The hypoxic signal was segmented using k-means clustering and HF was specified as the ratio of the hypoxic area over the viable tumor area. The parametric Patlak slope images were obtained by indirect voxel-wise modeling on reconstructed images using filtered back projection and ordered-subset expectation maximization (OSEM) and by direct PIR (e.g., parametric-OSEM, POSEM). The mean and maximum Patlak slopes of the tumor area were investigated and compared with HF. POSEM resulted in generally higher correlations between slope and HF among the investigated methods. A strategy for the delineation of the hypoxic tumor volume based on thresholding parametric images at half maximum of the slope is recommended based on the results of this study.

Parametric scaling from species relative abundances to absolute abundances in the computation of biological diversity: a first proposal using Shannon's entropy.

PubMed

Ricotta, Carlo

2003-01-01

Traditional diversity measures such as the Shannon entropy are generally computed from the species' relative abundance vector of a given community to the exclusion of species' absolute abundances. In this paper, I first mention some examples where the total information content associated with a given community may be more adequate than Shannon's average information content for a better understanding of ecosystem functioning. Next, I propose a parametric measure of statistical information that contains both Shannon's entropy and total information content as special cases of this more general function.

Statistical Analysis of the Exchange Rate of Bitcoin

PubMed Central

Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

2015-01-01

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702

Density-based empirical likelihood procedures for testing symmetry of data distributions and K-sample comparisons.

PubMed

Vexler, Albert; Tanajian, Hovig; Hutson, Alan D

In practice, parametric likelihood-ratio techniques are powerful statistical tools. In this article, we propose and examine novel and simple distribution-free test statistics that efficiently approximate parametric likelihood ratios to analyze and compare distributions of K groups of observations. Using the density-based empirical likelihood methodology, we develop a Stata package that applies to a test for symmetry of data distributions and compares K -sample distributions. Recognizing that recent statistical software packages do not sufficiently address K -sample nonparametric comparisons of data distributions, we propose a new Stata command, vxdbel, to execute exact density-based empirical likelihood-ratio tests using K samples. To calculate p -values of the proposed tests, we use the following methods: 1) a classical technique based on Monte Carlo p -value evaluations; 2) an interpolation technique based on tabulated critical values; and 3) a new hybrid technique that combines methods 1 and 2. The third, cutting-edge method is shown to be very efficient in the context of exact-test p -value computations. This Bayesian-type method considers tabulated critical values as prior information and Monte Carlo generations of test statistic values as data used to depict the likelihood function. In this case, a nonparametric Bayesian method is proposed to compute critical values of exact tests.

Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models.

PubMed

Andersson, Therese M L; Dickman, Paul W; Eloranta, Sandra; Lambert, Paul C

2011-06-22

When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. © 2011 Andersson et al; licensee BioMed Central Ltd.

Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models

PubMed Central

2011-01-01

Background When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Methods Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. Results We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Conclusions Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. PMID:21696598

Parametric instabilities and their control in multidimensional nonuniform gain media

NASA Astrophysics Data System (ADS)

Charbonneau-Lefort, Mathieu; Afeyan, Bedros; Fejer, Martin

2007-11-01

In order to control parametric instabilities in large scale long pulse laser produced plasmas, optical mixing techniques seem most promising [1]. We examine ways of controlling the growth of some modes while creating other unstable ones in nonuniform gain media, including the effects of transverse localization of the pump wave. We show that multidimensional effects are essential to understand laser-gain medium interactions [2] and that one dimensional models such as the celebrated Rosenbluth result [3] can be misleading [4]. These findings are verified in experiments carried out in a chirped quasi-phase-matched gratings in optical parametric amplifiers where thousands of shots can be taken and statistically significant and stable results obtained. [1] B. Afeyan, et al., IFSA Proceedings, 2003. [2] M. M. Sushchik and G. I. Freidman, Radiofizika 13, 1354 (1970). [3] M. N. Rosenbluth, Phys. Rev. Lett. 29, 565 (1972). [4] M. Charbonneau-Lefort, PhD thesis, Stanford University, 2007.

TEMPORAL VARIABILITY OF TOXIC CONTAMINANTS IN ANIMAL DIETS

EPA Science Inventory

Uncertified commercial research animal feed (Purina Chow TM) was analyzed over forty-one months to determine essential and trace elements and toxic contaminants. Parametric statistics and graphic chronologic progressions of the results are presented for cat, monkey, rodent (rat/m...

Alteration of functional state of peripheral blood erythrocytes in women of different age groups at dislipidemia conditions.

PubMed

Ratiani, L; Intskirveli, N; Ormotsadze, G; Sanikidze, T

2011-12-01

The aim of the study was identification of statistically reliable correlations and the cause-effect relationships between viability of red blood cells and dislipidema parametres and/or metabolic disorders, induced by age related alterations of estrogen content, in women of different ages (reproductive, menopausal) On the basis of the analysis of research results we can conclude that in the different age groups of women with atherosclerosis-induced cardiovascular diseases revealed estrogen-related dependence between Tg-s and HDL content, functional status of phereperial blood erytrotcites and severity of dislipidemia. The aterogenic index Tg/HD proved to be sensitive marker of dislipidemia in reproductive aging women, but does't reflect disorders of lipid metabolism in postmenosal women. It was proved the existence of reliable corelation between red blood cells dysfunction indicator, spherulation quality, and atherogenic index Tg/HDL highlights; however, the correlation coefficient is 2 times higher in the reproductive age as in menopause. Spherulation quality of red blood cells at low HDL content showd fast growth rate in reproductive-aged women, and was unsensetive to HDL content in postmenopasal women. It was concluded that age-related lack of estrogens in postmenopausal women indirectly contributes to decrease protection of red blood cells against oxidative damage, reduces their deformabelity and disturbances the rheological properties. So, Spherulation quality of red blood cells may be used as a diagnostic marker of severity of atherosclerosis.

Absence of gender effect on children with attention-deficit/hyperactivity disorder as assessed by optimized voxel-based morphometry.

PubMed

Yang, Pinchen; Wang, Pei-Ning; Chuang, Kai-Hsiang; Jong, Yuh-Jyh; Chao, Tzu-Cheng; Wu, Ming-Ting

2008-12-30

Brain abnormalities, as determined by structural magnetic resonance imaging (MRI), have been reported in patients with attention-deficit hyperactivity disorder (ADHD); however, female subjects have been underrepresented in previous reports. In this study, we used optimized voxel-based morphometry to compare the total and regional gray matter volumes between groups of 7- to 17-year-old ADHD and healthy children (total 114 subjects). Fifty-seven children with ADHD (n=57, 35 males and 22 females) and healthy children (n=57) received MRI scans. Segmented brain MRI images were normalized into standardized stereotactic space, modulated to allow volumetric analysis, smoothed and compared at the voxel level with statistical parametric mapping. Global volumetric comparisons between groups revealed that the total brain volumes of ADHD children were smaller than those of the control children. As for the regional brain analysis, the brain volumes of ADHD children were found to be bilaterally smaller in the following regions as compared with normal control values: the caudate nucleus and the cerebellum. There were two clusters of regional decrease in the female brain, left posterior cingulum and right precuneus, as compared with the male brain. Brain regions showing the interaction effect of diagnosis and gender were negligible. These results were consistent with the hypothesized dysfunctional systems in ADHD, and they also suggested that neuroanatomical abnormalities in ADHD were not influenced by gender.

The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data

NASA Astrophysics Data System (ADS)

Peres, Leonardo de Faria; Lucena, Andrews José de; Rotunno Filho, Otto Corrêa; França, José Ricardo de Almeida

2018-02-01

The aim of this work is to study urban heat island (UHI) in Metropolitan Area of Rio de Janeiro (MARJ) based on the analysis of land-surface temperature (LST) and land-use patterns retrieved from Landsat-5/Thematic Mapper (TM), Landsat-7/Enhanced Thematic Mapper Plus (ETM+) and Landsat-8/Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS) data covering a 32-year period between 1984 and 2015. LST temporal evolution is assessed by comparing the average LST composites for 1984-1999 and 2000-2015 where the parametric Student t-test was conducted at 5% significance level to map the pixels where LST for the more recent period is statistically significantly greater than the previous one. The non-parametric Mann-Whitney-Wilcoxon rank sum test has also confirmed at the same 5% significance level that the more recent period (2000-2015) has higher LST values. UHI intensity between ;urban; and ;rural/urban low density; (;vegetation;) areas for 1984-1999 and 2000-2015 was established and confirmed by both parametric and non-parametric tests at 1% significance level as 3.3 °C (5.1 °C) and 4.4 °C (7.1 °C), respectively. LST has statistically significantly (p-value < 0.01) increased over time in two of three land cover classes (;urban; and ;urban low density;), respectively by 1.9 °C and 0.9 °C, except in ;vegetation; class. A spatial analysis was also performed to identify the urban pixels within MARJ where UHI is more intense by subtracting the LST of these pixels from the LST mean value of ;vegetation; land-use class.

Parametric modulation of neural activity by emotion in youth with bipolar disorder, severe mood dysregulation, and healthy subjects

PubMed Central

Thomas, Laura A.; Brotman, Melissa A.; Muhrer, Eli M.; Rosen, Brooke H.; Bones, Brian L.; Reynolds, Richard C.; Deveney, Christen; Pine, Daniel S.; Leibenluft, Ellen

2012-01-01

Context Youth with bipolar disorder (BD) and those with severe, non-episodic irritability (severe mood dysregulation, SMD) show amygdala dysfunction during face emotion processing. However, studies have not compared such patients to each other and to comparison subjects in neural responsiveness to subtle changes in face emotion; the ability to process such changes is important for social cognition. We employed a novel parametrically designed faces paradigm. Objective Using a parametrically morphed emotional faces task, we compared activation in the amygdala and across the brain in BD, SMD, and healthy volunteers (HV). Design Case-control study. Setting Government research institute. Participants 57 youths (19 BD, 15 SMD, 23 HV). Main Outcome Measure Blood oxygenated level dependent (BOLD) data. Neutral faces were morphed with angry and happy faces in 25% intervals; static face stimuli appeared for 3000ms. Subjects performed hostility or non-emotional facial feature (i.e., nose width) ratings. Slope of BOLD activity was calculated across neutral-to-angry (N→A) and neutral-to-happy (N→H) face stimuli. Results In HV, but not BD or SMD, there was a positive association between left amygdala activity and anger on the face. In the N→H whole brain analysis, BD and SMD modulated parietal, temporal, and medial-frontal areas differently from each other and from HV; with increasing facial-happiness, SMD increased, while BD decreased, activity in parietal, temporal, and frontal regions. Conclusions Youth with BD or SMD differ from HV in modulation of amygdala activity in response to small changes in facial anger displays. In contrast, BD and SMD show distinct perturbations in regions mediating attention and face processing in association with changes in the emotional intensity of facial happiness displays. These findings demonstrate similarities and differences in the neural correlates of face emotion processing in BD and SMD, suggesting these distinct clinical presentations may reflect differing pathologies along a mood disorders spectrum. PMID:23026912

ICD-11 and DSM-5 personality trait domains capture categorical personality disorders: Finding a common ground.

PubMed

Bach, Bo; Sellbom, Martin; Skjernov, Mathias; Simonsen, Erik

2018-05-01

The five personality disorder trait domains in the proposed International Classification of Diseases, 11th edition and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition are comparable in terms of Negative Affectivity, Detachment, Antagonism/Dissociality and Disinhibition. However, the International Classification of Diseases, 11th edition model includes a separate domain of Anankastia, whereas the Diagnostic and Statistical Manual of Mental Disorders, 5th edition model includes an additional domain of Psychoticism. This study examined associations of International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition trait domains, simultaneously, with categorical personality disorders. Psychiatric outpatients ( N = 226) were administered the Structured Clinical Interview for DSM-IV Axis II Personality Disorders Interview and the Personality Inventory for DSM-5. International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition trait domain scores were obtained using pertinent scoring algorithms for the Personality Inventory for DSM-5. Associations between categorical personality disorders and trait domains were examined using correlation and multiple regression analyses. Both the International Classification of Diseases, 11th edition and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition domain models showed relevant continuity with categorical personality disorders and captured a substantial amount of their information. As expected, the International Classification of Diseases, 11th edition model was superior in capturing obsessive-compulsive personality disorder, whereas the Diagnostic and Statistical Manual of Mental Disorders, 5th edition model was superior in capturing schizotypal personality disorder. These preliminary findings suggest that little information is 'lost' in a transition to trait domain models and potentially adds to narrowing the gap between Diagnostic and Statistical Manual of Mental Disorders, 5th edition and the proposed International Classification of Diseases, 11th edition model. Accordingly, the International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition domain models may be used to delineate one another as well as features of familiar categorical personality disorder types. A preliminary category-to-domain 'cross walk' is provided in the article.

Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Kumar, Sanjay; Dayal, Devi

2016-05-01

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability ( R y), resilience ( R e), and vulnerability ( V y) approach. Box-whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations ( R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable compared with that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of R y- R e- V y approach. In general, annual rainfall of the study area is less reliable, less resilient, and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time-series modeling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.

Statistical State Dynamics Based Study of the Role of Nonlinearity in the Maintenance of Turbulence in Couette Flow

NASA Astrophysics Data System (ADS)

Farrell, Brian; Ioannou, Petros; Nikolaidis, Marios-Andreas

2017-11-01

While linear non-normality underlies the mechanism of energy transfer from the externally driven flow to the perturbation field, nonlinearity is also known to play an essential role in sustaining turbulence. We report a study based on the statistical state dynamics of Couette flow turbulence with the goal of better understanding the role of nonlinearity in sustaining turbulence. The statistical state dynamics implementations used are ensemble closures at second order in a cumulant expansion of the Navier-Stokes equations in which the averaging operator is the streamwise mean. Two fundamentally non-normal mechanisms potentially contributing to maintaining the second cumulant are identified. These are essentially parametric perturbation growth arising from interaction of the perturbations with the fluctuating mean flow and transient growth of perturbations arising from nonlinear interaction between components of the perturbation field. By the method of selectively including these mechanisms parametric growth is found to maintain the perturbation field in the turbulent state while the more commonly invoked mechanism associated with transient growth of perturbations arising from scattering by nonlinear interaction is found to suppress perturbation variance. Funded by ERC Coturb Madrid Summer Program and NSF AGS-1246929.

Brain serotonin transporter density and aggression in abstinent methamphetamine abusers.

PubMed

Sekine, Yoshimoto; Ouchi, Yasuomi; Takei, Nori; Yoshikawa, Etsuji; Nakamura, Kazuhiko; Futatsubashi, Masami; Okada, Hiroyuki; Minabe, Yoshio; Suzuki, Katsuaki; Iwata, Yasuhide; Tsuchiya, Kenji J; Tsukada, Hideo; Iyo, Masaomi; Mori, Norio

2006-01-01

In animals, methamphetamine is known to have a neurotoxic effect on serotonin neurons, which have been implicated in the regulation of mood, anxiety, and aggression. It remains unknown whether methamphetamine damages serotonin neurons in humans. To investigate the status of brain serotonin neurons and their possible relationship with clinical characteristics in currently abstinent methamphetamine abusers. Case-control analysis. A hospital research center. Twelve currently abstinent former methamphetamine abusers (5 women and 7 men) and 12 age-, sex-, and education-matched control subjects recruited from the community. The brain regional density of the serotonin transporter, a structural component of serotonin neurons, was estimated using positron emission tomography and trans-1,2,3,5,6,10-beta-hexahydro-6-[4-(methylthio)phenyl]pyrrolo-[2,1-a]isoquinoline ([(11)C](+)McN-5652). Estimates were derived from region-of-interest and statistical parametric mapping methods, followed by within-case analysis using the measures of clinical variables. The duration of methamphetamine use, the magnitude of aggression and depressive symptoms, and changes in serotonin transporter density represented by the [(11)C](+)McN-5652 distribution volume. Methamphetamine abusers showed increased levels of aggression compared with controls. Region-of-interest and statistical parametric mapping analyses revealed that the serotonin transporter density in global brain regions (eg, the midbrain, thalamus, caudate, putamen, cerebral cortex, and cerebellum) was significantly lower in methamphetamine abusers than in control subjects, and this reduction was significantly inversely correlated with the duration of methamphetamine use. Furthermore, statistical parametric mapping analyses indicated that the density in the orbitofrontal, temporal, and anterior cingulate areas was closely associated with the magnitude of aggression in methamphetamine abusers. Protracted abuse of methamphetamine may reduce the density of the serotonin transporter in the brain, leading to elevated aggression, even in currently abstinent abusers.

Parametric modelling of cost data in medical studies.

PubMed

Nixon, R M; Thompson, S G

2004-04-30

The cost of medical resources used is often recorded for each patient in clinical studies in order to inform decision-making. Although cost data are generally skewed to the right, interest is in making inferences about the population mean cost. Common methods for non-normal data, such as data transformation, assuming asymptotic normality of the sample mean or non-parametric bootstrapping, are not ideal. This paper describes possible parametric models for analysing cost data. Four example data sets are considered, which have different sample sizes and degrees of skewness. Normal, gamma, log-normal, and log-logistic distributions are fitted, together with three-parameter versions of the latter three distributions. Maximum likelihood estimates of the population mean are found; confidence intervals are derived by a parametric BC(a) bootstrap and checked by MCMC methods. Differences between model fits and inferences are explored.Skewed parametric distributions fit cost data better than the normal distribution, and should in principle be preferred for estimating the population mean cost. However for some data sets, we find that models that fit badly can give similar inferences to those that fit well. Conversely, particularly when sample sizes are not large, different parametric models that fit the data equally well can lead to substantially different inferences. We conclude that inferences are sensitive to choice of statistical model, which itself can remain uncertain unless there is enough data to model the tail of the distribution accurately. Investigating the sensitivity of conclusions to choice of model should thus be an essential component of analysing cost data in practice. Copyright 2004 John Wiley & Sons, Ltd.

White-light parametric instabilities in plasmas.

PubMed

Santos, J E; Silva, L O; Bingham, R

2007-06-08

Parametric instabilities driven by partially coherent radiation in plasmas are described by a generalized statistical Wigner-Moyal set of equations, formally equivalent to the full wave equation, coupled to the plasma fluid equations. A generalized dispersion relation for stimulated Raman scattering driven by a partially coherent pump field is derived, revealing a growth rate dependence, with the coherence width sigma of the radiation field, scaling with 1/sigma for backscattering (three-wave process), and with 1/sigma1/2 for direct forward scattering (four-wave process). Our results demonstrate the possibility to control the growth rates of these instabilities by properly using broadband pump radiation fields.

The effect of pumping noise on the characteristics of a single-stage parametric amplifier

NASA Astrophysics Data System (ADS)

Medvedev, S. Iu.; Muzychuk, O. V.

1983-10-01

An analysis is made of the operation of a single-stage parametric amplifier based on a varactor with a sharp transition. Analytical expressions are obtained for the statistical moments of the output signal, the signal-noise ratio, and other characteristics in the case when the output signal and the pump are a mixture of harmonic oscillation and Gaussian noise. It is shown that, when a noise component is present in the pump, an increase of its harmonic component to values close to the threshold leads to a sharp decrease in the signal-noise ratio at the amplifier output.

Review of Statistical Methods for Analysing Healthcare Resources and Costs

PubMed Central

Mihaylova, Borislava; Briggs, Andrew; O'Hagan, Anthony; Thompson, Simon G

2011-01-01

We review statistical methods for analysing healthcare resource use and costs, their ability to address skewness, excess zeros, multimodality and heavy right tails, and their ease for general use. We aim to provide guidance on analysing resource use and costs focusing on randomised trials, although methods often have wider applicability. Twelve broad categories of methods were identified: (I) methods based on the normal distribution, (II) methods following transformation of data, (III) single-distribution generalized linear models (GLMs), (IV) parametric models based on skewed distributions outside the GLM family, (V) models based on mixtures of parametric distributions, (VI) two (or multi)-part and Tobit models, (VII) survival methods, (VIII) non-parametric methods, (IX) methods based on truncation or trimming of data, (X) data components models, (XI) methods based on averaging across models, and (XII) Markov chain methods. Based on this review, our recommendations are that, first, simple methods are preferred in large samples where the near-normality of sample means is assured. Second, in somewhat smaller samples, relatively simple methods, able to deal with one or two of above data characteristics, may be preferable but checking sensitivity to assumptions is necessary. Finally, some more complex methods hold promise, but are relatively untried; their implementation requires substantial expertise and they are not currently recommended for wider applied work. Copyright © 2010 John Wiley & Sons, Ltd. PMID:20799344

Kernel-based whole-genome prediction of complex traits: a review.

PubMed

Morota, Gota; Gianola, Daniel

2014-01-01

Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

Observed changes in relative humidity and dew point temperature in coastal regions of Iran

NASA Astrophysics Data System (ADS)

Hosseinzadeh Talaee, P.; Sabziparvar, A. A.; Tabari, Hossein

2012-12-01

The analysis of trends in hydroclimatic parameters and assessment of their statistical significance have recently received a great concern to clarify whether or not there is an obvious climate change. In the current study, parametric linear regression and nonparametric Mann-Kendall tests were applied for detecting annual and seasonal trends in the relative humidity (RH) and dew point temperature ( T dew) time series at ten coastal weather stations in Iran during 1966-2005. The serial structure of the data was considered, and the significant serial correlations were eliminated using the trend-free pre-whitening method. The results showed that annual RH increased by 1.03 and 0.28 %/decade at the northern and southern coastal regions of the country, respectively, while annual T dew increased by 0.29 and 0.15°C per decade at the northern and southern regions, respectively. The significant trends were frequent in the T dew series, but they were observed only at 2 out of the 50 RH series. The results showed that the difference between the results of the parametric and nonparametric tests was small, although the parametric test detected larger significant trends in the RH and T dew time series. Furthermore, the differences between the results of the trend tests were not related to the normality of the statistical distribution.

Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI

NASA Astrophysics Data System (ADS)

Rougon, Nicolas F.; Petitjean, Caroline; Preteux, Francoise J.

2004-05-01

We address the issue of modeling and quantifying myocardial contraction from 4D MR sequences, and present an unsupervised approach for building and using a statistical 3D motion atlas for the normal heart. This approach relies on a state-of-the-art variational non rigid registration (NRR) technique using generalized information measures, which allows for robust intra-subject motion estimation and inter-subject anatomical alignment. The atlas is built from a collection of jointly acquired tagged and cine MR exams in short- and long-axis views. Subject-specific non parametric motion estimates are first obtained by incremental NRR of tagged images onto the end-diastolic (ED) frame. Individual motion data are then transformed into the coordinate system of a reference subject using subject-to-reference mappings derived by NRR of cine ED images. Finally, principal component analysis of aligned motion data is performed for each cardiac phase, yielding a mean model and a set of eigenfields encoding kinematic ariability. The latter define an organ-dedicated hierarchical motion basis which enables parametric motion measurement from arbitrary tagged MR exams. To this end, the atlas is transformed into subject coordinates by reference-to-subject NRR of ED cine frames. Atlas-based motion estimation is then achieved by parametric NRR of tagged images onto the ED frame, yielding a compact description of myocardial contraction during diastole.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

Power flow analysis of two coupled plates with arbitrary characteristics

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1990-01-01

In the last progress report (Feb. 1988) some results were presented for a parametric analysis on the vibrational power flow between two coupled plate structures using the mobility power flow approach. The results reported then were for changes in the structural parameters of the two plates, but with the two plates identical in their structural characteristics. Herein, limitation is removed. The vibrational power input and output are evaluated for different values of the structural damping loss factor for the source and receiver plates. In performing this parametric analysis, the source plate characteristics are kept constant. The purpose of this parametric analysis is to determine the most critical parameters that influence the flow of vibrational power from the source plate to the receiver plate. In the case of the structural damping parametric analysis, the influence of changes in the source plate damping is also investigated. The results obtained from the mobility power flow approach are compared to results obtained using a statistical energy analysis (SEA) approach. The significance of the power flow results are discussed together with a discussion and a comparison between the SEA results and the mobility power flow results. Furthermore, the benefits derived from using the mobility power flow approach are examined.

Computational Analysis for Rocket-Based Combined-Cycle Systems During Rocket-Only Operation

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.; Smith, T. D.; Yungster, S.; Keller, D. J.

2000-01-01

A series of Reynolds-averaged Navier-Stokes calculations were employed to study the performance of rocket-based combined-cycle systems operating in an all-rocket mode. This parametric series of calculations were executed within a statistical framework, commonly known as design of experiments. The parametric design space included four geometric and two flowfield variables set at three levels each, for a total of 729 possible combinations. A D-optimal design strategy was selected. It required that only 36 separate computational fluid dynamics (CFD) solutions be performed to develop a full response surface model, which quantified the linear, bilinear, and curvilinear effects of the six experimental variables. The axisymmetric, Reynolds-averaged Navier-Stokes simulations were executed with the NPARC v3.0 code. The response used in the statistical analysis was created from Isp efficiency data integrated from the 36 CFD simulations. The influence of turbulence modeling was analyzed by using both one- and two-equation models. Careful attention was also given to quantify the influence of mesh dependence, iterative convergence, and artificial viscosity upon the resulting statistical model. Thirteen statistically significant effects were observed to have an influence on rocket-based combined-cycle nozzle performance. It was apparent that the free-expansion process, directly downstream of the rocket nozzle, can influence the Isp efficiency. Numerical schlieren images and particle traces have been used to further understand the physical phenomena behind several of the statistically significant results.

Methods to assess pecan scab

USDA-ARS?s Scientific Manuscript database

Pecan scab (Fusicladium effusum [G. Winter]) is the most important disease of pecan in the U.S. Measuring the severity of scab accurately and reliably and providing data amenable to analysis using parametric statistics is important where treatments are being compared to minimize the risk of Type II ...

Scenario based optimization of a container vessel with respect to its projected operating conditions

NASA Astrophysics Data System (ADS)

Wagner, Jonas; Binkowski, Eva; Bronsart, Robert

2014-06-01

In this paper the scenario based optimization of the bulbous bow of the KRISO Container Ship (KCS) is presented. The optimization of the parametrically modeled vessel is based on a statistically developed operational profile generated from noon-to-noon reports of a comparable 3600 TEU container vessel and specific development functions representing the growth of global economy during the vessels service time. In order to consider uncertainties, statistical fluctuations are added. An analysis of these data lead to a number of most probable upcoming operating conditions (OC) the vessel will stay in the future. According to their respective likeliness an objective function for the evaluation of the optimal design variant of the vessel is derived and implemented within the parametrical optimization workbench FRIENDSHIP Framework. In the following this evaluation is done with respect to vessel's calculated effective power based on the usage of potential flow code. The evaluation shows, that the usage of scenarios within the optimization process has a strong influence on the hull form.

A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien

2006-03-01

Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.

Indirect Reconstruction of Pore Morphology for Parametric Computational Characterization of Unidirectional Porous Iron.

PubMed

Kovačič, Aljaž; Borovinšek, Matej; Vesenjak, Matej; Ren, Zoran

2018-01-26

This paper addresses the problem of reconstructing realistic, irregular pore geometries of lotus-type porous iron for computer models that allow for simple porosity and pore size variation in computational characterization of their mechanical properties. The presented methodology uses image-recognition algorithms for the statistical analysis of pore morphology in real material specimens, from which a unique fingerprint of pore morphology at a certain porosity level is derived. The representative morphology parameter is introduced and used for the indirect reconstruction of realistic and statistically representative pore morphologies, which can be used for the generation of computational models with an arbitrary porosity. Such models were subjected to parametric computer simulations to characterize the dependence of engineering elastic modulus on the porosity of lotus-type porous iron. The computational results are in excellent agreement with experimental observations, which confirms the suitability of the presented methodology of indirect pore geometry reconstruction for computational simulations of similar porous materials.

[Detection of cerebral hypoperfusion using single photon emission computed tomography image analysis and statistical parametric mapping in patients with Parkinson's disease or progressive supranuclear palsy].

PubMed

Harada, Kengo; Saeki, Hiroshi; Matsuya, Eiji; Okita, Izumi

2013-11-01

We carried out differential diagnosis of brain blood flow images using single-photon emission computed tomography (SPECT) for patients with Parkinson's disease (PD) or progressive supranuclear paralysis (PSP) using statistical parametric mapping (SPM) and to whom we had applied anatomical standardization. We studied two groups and compared brain blood flow images using SPECT (N-isopropyl-4-iodoamphetamine [(123)I] hydrochloride injection, 222 MGq dosage i.v.). A total of 27 patients were studied using SPM: 18 with PD and 9 with PSP; humming bird sign on MRI was from moderate to medium. The decline of brain bloodstream in the PSP group was more notable in the midbrain, near the domain where the humming bird sign was observable, than in the PD group. The observable differences in brain bloodstream decline in the midbrain of PSP and PD patients suggest the potential usefulness of this technique's clinical application to distinction diagnosis.

Phylogenetic relationships of South American lizards of the genus Stenocercus (Squamata: Iguania): A new approach using a general mixture model for gene sequence data.

PubMed

Torres-Carvajal, Omar; Schulte, James A; Cadle, John E

2006-04-01

The South American iguanian lizard genus Stenocercus includes 54 species occurring mostly in the Andes and adjacent lowland areas from northern Venezuela and Colombia to central Argentina at elevations of 0-4000m. Small taxon or character sampling has characterized all phylogenetic analyses of Stenocercus, which has long been recognized as sister taxon to the Tropidurus Group. In this study, we use mtDNA sequence data to perform phylogenetic analyses that include 32 species of Stenocercus and 12 outgroup taxa. Monophyly of this genus is strongly supported by maximum parsimony and Bayesian analyses. Evolutionary relationships within Stenocercus are further analyzed with a Bayesian implementation of a general mixture model, which accommodates variability in the pattern of evolution across sites. These analyses indicate a basal split of Stenocercus into two clades, one of which receives very strong statistical support. In addition, we test previous hypotheses using non-parametric and parametric statistical methods, and provide a phylogenetic classification for Stenocercus.

How to Evaluate Phase Differences between Trial Groups in Ongoing Electrophysiological Signals

PubMed Central

VanRullen, Rufin

2016-01-01

A growing number of studies endeavor to reveal periodicities in sensory and cognitive functions, by comparing the distribution of ongoing (pre-stimulus) oscillatory phases between two (or more) trial groups reflecting distinct experimental outcomes. A systematic relation between the phase of spontaneous electrophysiological signals, before a stimulus is even presented, and the eventual result of sensory or cognitive processing for that stimulus, would be indicative of an intrinsic periodicity in the underlying neural process. Prior studies of phase-dependent perception have used a variety of analytical methods to measure and evaluate phase differences, and there is currently no established standard practice in this field. The present report intends to remediate this need, by systematically comparing the statistical power of various measures of “phase opposition” between two trial groups, in a number of real and simulated experimental situations. Seven measures were evaluated: one parametric test (circular Watson-Williams test), and three distinct measures of phase opposition (phase bifurcation index, phase opposition sum, and phase opposition product) combined with two procedures for non-parametric statistical testing (permutation, or a combination of z-score and permutation). While these are obviously not the only existing or conceivable measures, they have all been used in recent studies. All tested methods performed adequately on a previously published dataset (Busch et al., 2009). On a variety of artificially constructed datasets, no single measure was found to surpass all others, but instead the suitability of each measure was contingent on several experimental factors: the time, frequency, and depth of oscillatory phase modulation; the absolute and relative amplitudes of post-stimulus event-related potentials for the two trial groups; the absolute and relative trial numbers for the two groups; and the number of permutations used for non-parametric testing. The concurrent use of two phase opposition measures, the parametric Watson-Williams test and a non-parametric test based on summing inter-trial coherence values for the two trial groups, appears to provide the most satisfactory outcome in all situations tested. Matlab code is provided to automatically compute these phase opposition measures. PMID:27683543

Inhibition of Orthopaedic Implant Infections by Immunomodulatory Effects of Host Defense Peptides

DTIC Science & Technology

2014-12-01

significance was determined by t- tests or by one-way analysis of variance (ANOVA) followed by Bonferroni post hoc tests in experiments with multiple...groups. Non- parametric Mann-Whitney tests , Kruskal-Wallis ANOVA followed by Newman-Kuels post hoc tests , or van Elteren’s two-way tests were applied to...in D, and black symbols in A), statistical analysis was by one-way ANOVA followed by Bonferroni versus control, post hoc tests . Otherwise, statistical

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

PubMed

Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

Enhanced detection and visualization of anomalies in spectral imagery

NASA Astrophysics Data System (ADS)

Basener, William F.; Messinger, David W.

2009-05-01

Anomaly detection algorithms applied to hyperspectral imagery are able to reliably identify man-made objects from a natural environment based on statistical/geometric likelyhood. The process is more robust than target identification, which requires precise prior knowledge of the object of interest, but has an inherently higher false alarm rate. Standard anomaly detection algorithms measure deviation of pixel spectra from a parametric model (either statistical or linear mixing) estimating the image background. The topological anomaly detector (TAD) creates a fully non-parametric, graph theory-based, topological model of the image background and measures deviation from this background using codensity. In this paper we present a large-scale comparative test of TAD against 80+ targets in four full HYDICE images using the entire canonical target set for generation of ROC curves. TAD will be compared against several statistics-based detectors including local RX and subspace RX. Even a perfect anomaly detection algorithm would have a high practical false alarm rate in most scenes simply because the user/analyst is not interested in every anomalous object. To assist the analyst in identifying and sorting objects of interest, we investigate coloring of the anomalies with principle components projections using statistics computed from the anomalies. This gives a very useful colorization of anomalies in which objects of similar material tend to have the same color, enabling an analyst to quickly sort and identify anomalies of highest interest.

Reliability evaluation of I-123 ADAM SPECT imaging using SPM software and AAL ROI methods

NASA Astrophysics Data System (ADS)

Yang, Bang-Hung; Tsai, Sung-Yi; Wang, Shyh-Jen; Su, Tung-Ping; Chou, Yuan-Hwa; Chen, Chia-Chieh; Chen, Jyh-Cheng

2011-08-01

The level of serotonin was regulated by serotonin transporter (SERT), which is a decisive protein in regulation of serotonin neurotransmission system. Many psychiatric disorders and therapies were also related to concentration of cerebral serotonin. I-123 ADAM was the novel radiopharmaceutical to image SERT in brain. The aim of this study was to measure reliability of SERT densities of healthy volunteers by automated anatomical labeling (AAL) method. Furthermore, we also used statistic parametric mapping (SPM) on a voxel by voxel analysis to find difference of cortex between test and retest of I-123 ADAM single photon emission computed tomography (SPECT) images.Twenty-one healthy volunteers were scanned twice with SPECT at 4 h after intravenous administration of 185 MBq of 123I-ADAM. The image matrix size was 128×128 and pixel size was 3.9 mm. All images were obtained through filtered back-projection (FBP) reconstruction algorithm. Region of interest (ROI) definition was performed based on the AAL brain template in PMOD version 2.95 software package. ROI demarcations were placed on midbrain, pons, striatum, and cerebellum. All images were spatially normalized to the SPECT MNI (Montreal Neurological Institute) templates supplied with SPM2. And each image was transformed into standard stereotactic space, which was matched to the Talairach and Tournoux atlas. Then differences across scans were statistically estimated on a voxel by voxel analysis using paired t-test (population main effect: 2 cond's, 1 scan/cond.), which was applied to compare concentration of SERT between the test and retest cerebral scans.The average of specific uptake ratio (SUR: target/cerebellum-1) of 123I-ADAM binding to SERT in midbrain was 1.78±0.27, pons was 1.21±0.53, and striatum was 0.79±0.13. The cronbach's α of intra-class correlation coefficient (ICC) was 0.92. Besides, there was also no significant statistical finding in cerebral area using SPM2 analysis. This finding might help us to understand reliability of I-123 ADAM SPECT imaging and further develop new strategy for the treatment of psychiatric disorders.

Effects of Respiratory Resistance Training With a Concurrent Flow Device on Wheelchair Athletes

PubMed Central

Litchke, Lyn G; Russian, Christopher J; Lloyd, Lisa K; Schmidt, Eric A; Price, Larry; Walker, John L

2008-01-01

Background/Objective: To determine the effect of respiratory resistance training (RRT) with a concurrent flow respiratory (CFR) device on respiratory function and aerobic power in wheelchair athletes. Methods: Ten male wheelchair athletes (8 with spinal cord injuries, 1 with a neurological disorder, and 1 with postpolio syndrome), were matched by lesion level and/or track rating before random assignment to either a RRT group (n = 5) or a control group (CON, n = 5). The RRT group performed 1 set of breathing exercises using Expand-a-Lung, a CFR device, 2 to 3 times daily for 10 weeks. Pre/posttesting included measurement of maximum voluntary ventilation (MVV), maximum inspiratory pressure (MIP), and peak oxygen consumption ( ). Results: Repeated measures ANOVA revealed a significant group difference in change for MIP from pre- to posttest (P < 0.05). The RRT group improved by 33.0 cm H2O, while the CON group improved by 0.6 cm H2O. Although not significant, the MVV increased for the RRT group and decreased for the CON group. There was no significant group difference between for pre/posttesting. Due to small sample sizes in both groups and violations of some parametric statistical assumptions, nonparametric tests were also conducted as a crosscheck of the findings. The results of the nonparametric tests concurred with the parametric results. Conclusions: These data demonstrate that 10 weeks of RRT training with a CFR device can effectively improve MIP in wheelchair athletes. Further research and a larger sample size are warranted to further characterize the impact of Expand-a-Lung on performance and other cardiorespiratory variables in wheelchair athletes. PMID:18533414

Language Learning Strategy Use and Reading Achievement

ERIC Educational Resources Information Center

Ghafournia, Narjes

2014-01-01

The current study investigated the differences across the varying levels of EFL learners in the frequency and choice of learning strategies. Using a reading test, questionnaire, and parametric statistical analysis, the findings yielded up discrepancies among the participants in the implementation of language-learning strategies concerning their…

Statistical error model for a solar electric propulsion thrust subsystem

NASA Technical Reports Server (NTRS)

Bantell, M. H.

1973-01-01

The solar electric propulsion thrust subsystem statistical error model was developed as a tool for investigating the effects of thrust subsystem parameter uncertainties on navigation accuracy. The model is currently being used to evaluate the impact of electric engine parameter uncertainties on navigation system performance for a baseline mission to Encke's Comet in the 1980s. The data given represent the next generation in statistical error modeling for low-thrust applications. Principal improvements include the representation of thrust uncertainties and random process modeling in terms of random parametric variations in the thrust vector process for a multi-engine configuration.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy.

PubMed

Kramer, Gerbrand Maria; Frings, Virginie; Heijtel, Dennis; Smit, E F; Hoekstra, Otto S; Boellaard, Ronald

2017-06-01

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'- 18 F-fluorothymidine ( 18 F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18 F-FLT PET/CT to assess the robustness of these methods. Methods : Ten NSCLC patients underwent dynamic 18 F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V T ) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy ( R 2 ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K 1 values ( R 2 = 0.94; intraclass correlation coefficient, 0.96). Parametric K 1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric 18 F-FLT V T images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K 1 data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic 18 F-FLT PET/CT studies; however, SA can also be used. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Increased sensorimotor network activity in DYT1 dystonia: a functional imaging study

PubMed Central

Argyelan, Miklos; Habeck, Christian; Ghilardi, M. Felice; Fitzpatrick, Toni; Dhawan, Vijay; Pourfar, Michael; Bressman, Susan B.; Eidelberg, David

2010-01-01

Neurophysiological studies have provided evidence of primary motor cortex hyperexcitability in primary dystonia, but several functional imaging studies suggest otherwise. To address this issue, we measured sensorimotor activation at both the regional and network levels in carriers of the DYT1 dystonia mutation and in control subjects. We used 15Oxygen-labelled water and positron emission tomography to scan nine manifesting DYT1 carriers, 10 non-manifesting DYT1 carriers and 12 age-matched controls while they performed a kinematically controlled motor task; they were also scanned in a non-motor audio-visual control condition. Within- and between-group contrasts were analysed with statistical parametric mapping. For network analysis, we first identified a normal motor-related activation pattern in a set of 39 motor and audio-visual scans acquired in an independent cohort of 18 healthy volunteer subjects. The expression of this pattern was prospectively quantified in the motor and control scans acquired in each of the gene carriers and controls. Network values for the three groups were compared with ANOVA and post hoc contrasts. Voxel-wise comparison of DYT1 carriers and controls revealed abnormally increased motor activation responses in the former group (P < 0.05, corrected; statistical parametric mapping), localized to the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and the inferior parietal cortex. Network analysis of the normative derivation cohort revealed a significant normal motor-related activation pattern topography (P < 0.0001) characterized by covarying neural activity in the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and cerebellum. In the study cohort, normal motor-related activation pattern expression measured during movement was abnormally elevated in the manifesting gene carriers (P < 0.001) but not in their non-manifesting counterparts. In contrast, in the non-motor control condition, abnormal increases in network activity were present in both groups of gene carriers (P < 0.001). In this condition, normal motor-related activation pattern expression in non-manifesting carriers was greater than in controls, but lower than in affected carriers. In the latter group, measures of normal motor-related activation pattern expression in the audio-visual condition correlated with independent dystonia clinical ratings (r = 0.70, P = 0.04). These findings confirm that overexcitability of the sensorimotor system is a robust feature of dystonia. The presence of elevated normal motor-related activation pattern expression in the non-motor condition suggests that abnormal integration of audio-visual input with sensorimotor network activity is an important trait feature of this disorder. Lastly, quantification of normal motor-related activation pattern expression in individual cases may have utility as an objective descriptor of therapeutic response in trials of new treatments for dystonia and related disorders. PMID:20207699

Ultrasound-aided Multi-parametric Photoacoustic Microscopy of the Mouse Brain.

PubMed

Ning, Bo; Sun, Naidi; Cao, Rui; Chen, Ruimin; Kirk Shung, K; Hossack, John A; Lee, Jin-Moo; Zhou, Qifa; Hu, Song

2015-12-21

High-resolution quantitative imaging of cerebral oxygen metabolism in mice is crucial for understanding brain functions and formulating new strategies to treat neurological disorders, but remains a challenge. Here, we report on our newly developed ultrasound-aided multi-parametric photoacoustic microscopy (PAM), which enables simultaneous quantification of the total concentration of hemoglobin (CHb), the oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF) at the microscopic level and through the intact mouse skull. The three-dimensional skull and vascular anatomies delineated by the dual-contrast (i.e., ultrasonic and photoacoustic) system provide important guidance for dynamically focused contour scan and vessel orientation-dependent correction of CBF, respectively. Moreover, bi-directional raster scan allows determining the direction of blood flow in individual vessels. Capable of imaging all three hemodynamic parameters at the same spatiotemporal scale, our ultrasound-aided PAM fills a critical gap in preclinical neuroimaging and lays the foundation for high-resolution mapping of the cerebral metabolic rate of oxygen (CMRO2)-a quantitative index of cerebral oxygen metabolism. This technical innovation is expected to shed new light on the mechanism and treatment of a broad spectrum of neurological disorders, including Alzheimer's disease and ischemic stroke.

Effects of Regularisation Priors and Anatomical Partial Volume Correction on Dynamic PET Data

NASA Astrophysics Data System (ADS)

Caldeira, Liliana L.; Silva, Nuno da; Scheins, Jürgen J.; Gaens, Michaela E.; Shah, N. Jon

2015-08-01

Dynamic PET provides temporal information about the tracer uptake. However, each PET frame has usually low statistics, resulting in noisy images. Furthermore, PET images suffer from partial volume effects. The goal of this study is to understand the effects of prior regularisation on dynamic PET data and subsequent anatomical partial volume correction. The Median Root Prior (MRP) regularisation method was used in this work during reconstruction. The quantification and noise in image-domain and time-domain (time-activity curves) as well as the impact on parametric images is assessed and compared with Ordinary Poisson Ordered Subset Expectation Maximisation (OP-OSEM) reconstruction with and without Gaussian filter. This study shows the improvement in PET images and time-activity curves (TAC) in terms of noise as well as in the parametric images when using prior regularisation in dynamic PET data. Anatomical partial volume correction improves the TAC and consequently, parametric images. Therefore, the use of MRP with anatomical partial volume correction is of interest for dynamic PET studies.

BLIND EXTRACTION OF AN EXOPLANETARY SPECTRUM THROUGH INDEPENDENT COMPONENT ANALYSIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waldmann, I. P.; Tinetti, G.; Hollis, M. D. J.

2013-03-20

Blind-source separation techniques are used to extract the transmission spectrum of the hot-Jupiter HD189733b recorded by the Hubble/NICMOS instrument. Such a 'blind' analysis of the data is based on the concept of independent component analysis. The detrending of Hubble/NICMOS data using the sole assumption that nongaussian systematic noise is statistically independent from the desired light-curve signals is presented. By not assuming any prior or auxiliary information but the data themselves, it is shown that spectroscopic errors only about 10%-30% larger than parametric methods can be obtained for 11 spectral bins with bin sizes of {approx}0.09 {mu}m. This represents a reasonablemore » trade-off between a higher degree of objectivity for the non-parametric methods and smaller standard errors for the parametric de-trending. Results are discussed in light of previous analyses published in the literature. The fact that three very different analysis techniques yield comparable spectra is a strong indication of the stability of these results.« less

Genome-wide analysis of genetic susceptibility to language impairment in an isolated Chilean population

PubMed Central

Villanueva, Pia; Newbury, Dianne F; Jara, Lilian; De Barbieri, Zulema; Mirza, Ghazala; Palomino, Hernán M; Fernández, María Angélica; Cazier, Jean-Baptiste; Monaco, Anthony P; Palomino, Hernán

2011-01-01

Specific language impairment (SLI) is an unexpected deficit in the acquisition of language skills and affects between 5 and 8% of pre-school children. Despite its prevalence and high heritability, our understanding of the aetiology of this disorder is only emerging. In this paper, we apply genome-wide techniques to investigate an isolated Chilean population who exhibit an increased frequency of SLI. Loss of heterozygosity (LOH) mapping and parametric and non-parametric linkage analyses indicate that complex genetic factors are likely to underlie susceptibility to SLI in this population. Across all analyses performed, the most consistently implicated locus was on chromosome 7q. This locus achieved highly significant linkage under all three non-parametric models (max NPL=6.73, P=4.0 × 10−11). In addition, it yielded a HLOD of 1.24 in the recessive parametric linkage analyses and contained a segment that was homozygous in two affected individuals. Further, investigation of this region identified a two-SNP haplotype that occurs at an increased frequency in language-impaired individuals (P=0.008). We hypothesise that the linkage regions identified here, in particular that on chromosome 7, may contain variants that underlie the high prevalence of SLI observed in this isolated population and may be of relevance to other populations affected by language impairments. PMID:21248734

Parametric imaging using subharmonic signals from ultrasound contrast agents in patients with breast lesions.

PubMed

Eisenbrey, John R; Dave, Jaydev K; Merton, Daniel A; Palazzo, Juan P; Hall, Anne L; Forsberg, Flemming

2011-01-01

Parametric maps showing perfusion of contrast media can be useful tools for characterizing lesions in breast tissue. In this study we show the feasibility of parametric subharmonic imaging (SHI), which allows imaging of a vascular marker (the ultrasound contrast agent) while providing near complete tissue suppression. Digital SHI clips of 16 breast lesions from 14 women were acquired. Patients were scanned using a modified LOGIQ 9 scanner (GE Healthcare, Waukesha, WI) transmitting/receiving at 4.4/2.2 MHz. Using motion-compensated cumulative maximum intensity (CMI) sequences, parametric maps were generated for each lesion showing the time to peak (TTP), estimated perfusion (EP), and area under the time-intensity curve (AUC). Findings were grouped and compared according to biopsy results as benign lesions (n = 12, including 5 fibroadenomas and 3 cysts) and carcinomas (n = 4). For each lesion CMI, TTP, EP, and AUC parametric images were generated. No significant variations were detected with CMI (P = .80), TTP (P = .35), or AUC (P = .65). A statistically significant variation was detected for the average pixel EP (P = .002). Especially, differences were seen between carcinoma and benign lesions (mean ± SD, 0.10 ± 0.03 versus 0.05 ± 0.02 intensity units [IU]/s; P = .0014) and between carcinoma and fibroadenoma (0.10 ± 0.03 versus 0.04 ± 0.01 IU/s; P = .0044), whereas differences between carcinomas and cysts were found to be nonsignificant. In conclusion, a parametric imaging method for characterization of breast lesions using the high contrast to tissue signal provided by SHI has been developed. While the preliminary sample size was limited, results show potential for breast lesion characterization based on perfusion flow parameters.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes.

PubMed

Kargarian-Marvasti, Sadegh; Rimaz, Shahnaz; Abolghasemi, Jamileh; Heydari, Iraj

2017-01-01

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model ( P < 0.20) were entered into the multivariate Cox and parametric models ( P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy ( P < 0.05). According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

Discrete photon statistics from continuous microwave measurements

NASA Astrophysics Data System (ADS)

Virally, Stéphane; Simoneau, Jean Olivier; Lupien, Christian; Reulet, Bertrand

2016-04-01

Photocount statistics are an important tool for the characterization of electromagnetic fields, especially for fields with an irrelevant phase. In the microwave domain, continuous rather than discrete measurements are the norm. Using a different approach, we recover discrete photon statistics from the cumulants of a continuous distribution of field quadrature measurements. The use of cumulants allows the separation between the signal of interest and experimental noise. Using a parametric amplifier as the first stage of the amplification chain, we extract useful data from up to the sixth cumulant of the continuous distribution of a coherent field, hence recovering up to the third moment of the discrete statistics associated with a signal with much less than one average photon.

Clinical and imaging correlates of amyloid deposition in dementia with Lewy bodies.

PubMed

Donaghy, Paul C; Firbank, Michael J; Thomas, Alan J; Lloyd, Jim; Petrides, George; Barnett, Nicola; Olsen, Kirsty; O'Brien, John T

2018-04-19

Amyloid deposition is common in dementia with Lewy bodies, but its pathophysiological significance is unclear. The objective of this study was to investigate the relationship between amyloid deposition and clinical profile, gray matter volume, and brain perfusion in dementia with Lewy bodies. Dementia with Lewy bodies (n = 37), Alzheimer's disease (n = 20), and controls (n = 20) underwent a thorough clinical assessment, 3T MRI, and early- and late-phase 18 F-Florbetapir PET-CT to assess cortical perfusion and amyloid deposition, respectively. Amyloid scans were visually categorized as positive or negative. Image analysis was carried out using statistical parametric mapping (SPM) 8. There were no significant differences between amyloid-positive and amyloid-negative dementia with Lewy bodies cases in age (P = .78), overall cognitive impairment (P = .83), level of functional impairment (P = .80), or any other clinical or cognitive scale. There were also no significant differences in hippocampal or gray matter volumes. However, amyloid-positive dementia with Lewy bodies cases had lower medial temporal lobe perfusion (P = .03) than amyloid-negative cases, although a combination of medial temporal lobe perfusion, hippocampal volume, and cognitive measures was unable to accurately predict amyloid status in dementia with Lewy bodies. Amyloid deposition was not associated with differences in clinical or neuropsychological profiles in dementia with Lewy bodies, but was associated with imaging evidence of medial temporal lobe dysfunction. The presence of amyloid in dementia with Lewy bodies cannot be identified on the basis of clinical and other imaging features and will require direct assessment via PET imaging or CSF. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Reference interval estimation: Methodological comparison using extensive simulations and empirical data.

PubMed

Daly, Caitlin H; Higgins, Victoria; Adeli, Khosrow; Grey, Vijay L; Hamid, Jemila S

2017-12-01

To statistically compare and evaluate commonly used methods of estimating reference intervals and to determine which method is best based on characteristics of the distribution of various data sets. Three approaches for estimating reference intervals, i.e. parametric, non-parametric, and robust, were compared with simulated Gaussian and non-Gaussian data. The hierarchy of the performances of each method was examined based on bias and measures of precision. The findings of the simulation study were illustrated through real data sets. In all Gaussian scenarios, the parametric approach provided the least biased and most precise estimates. In non-Gaussian scenarios, no single method provided the least biased and most precise estimates for both limits of a reference interval across all sample sizes, although the non-parametric approach performed the best for most scenarios. The hierarchy of the performances of the three methods was only impacted by sample size and skewness. Differences between reference interval estimates established by the three methods were inflated by variability. Whenever possible, laboratories should attempt to transform data to a Gaussian distribution and use the parametric approach to obtain the most optimal reference intervals. When this is not possible, laboratories should consider sample size and skewness as factors in their choice of reference interval estimation method. The consequences of false positives or false negatives may also serve as factors in this decision. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models.

PubMed

Sarkar, Rajarshi

2013-07-01

The validity of the entire renal function tests as a diagnostic tool depends substantially on the Biological Reference Interval (BRI) of urea. Establishment of BRI of urea is difficult partly because exclusion criteria for selection of reference data are quite rigid and partly due to the compartmentalization considerations regarding age and sex of the reference individuals. Moreover, construction of Biological Reference Curve (BRC) of urea is imperative to highlight the partitioning requirements. This a priori study examines the data collected by measuring serum urea of 3202 age and sex matched individuals, aged between 1 and 80 years, by a kinetic UV Urease/GLDH method on a Roche Cobas 6000 auto-analyzer. Mann-Whitney U test of the reference data confirmed the partitioning requirement by both age and sex. Further statistical analysis revealed the incompatibility of the data for a proposed parametric model. Hence the data was non-parametrically analysed. BRI was found to be identical for both sexes till the 2(nd) decade, and the BRI for males increased progressively 6(th) decade onwards. Four non-parametric models were postulated for construction of BRC: Gaussian kernel, double kernel, local mean and local constant, of which the last one generated the best-fitting curves. Clinical decision making should become easier and diagnostic implications of renal function tests should become more meaningful if this BRI is followed and the BRC is used as a desktop tool in conjunction with similar data for serum creatinine.

[Suicide due to mental diseases based on the Vital Statistics Survey Death Form].

PubMed

Takizawa, Tohru

2012-06-01

Mental diseases such as schizophrenia and depression put patients at risk for suicide. It is extremely important to understand that one way of preventing suicide is to determine the actual mental state of the individual. The purpose of this study was to analyze the true mental state of suicide victims reported in the vital statistics. This study investigated the vital statistics of 30,299 suicide victims in Japan in 2008. The use of these basic statistics for non-statistical purposes was approved by the Japanese Ministry of Health, Labour and Welfare. The method involved reviewing the Vital Statistics Survey Death Form at the Ministry of Health, Labour and Welfare as well as analyzing their Online Reporting of Vital Statistics. Furthermore, this study was able to validate 29,799 of the 30,299 suicides (98.3%) that occurred in 2008. Mental diseases were validated not only from the "Cause of death" section as marked on the death certificate, but also by information found in sections for "Additional items for death by external cause" and "Other special remarks." RESULTS; From the Vital Statistics Survey Death Form and Online Reporting of Vital Statistics, 2964 individuals with either a mental disease or mental disorder were identified. Of the 2964 identified individuals, 55 had dementia (of which 13 were dementia in Alzheimer's disease), 116 had alcohol dependence/psychotic disorder, 550 had schizophrenia, 101 had bipolar affective disorder, 1,913 has had a depressive episode, 13 had obsessive-compulsive disorder, 22 had adjustment disorders, 14 had eating disorders, 49 had nonorganic sleep disorders, 24 had personality disorder, and 6 had pervasive developmental disorders. In addition, 125 individuals had more than one mental disease. The national police statistics from 2008 show that 1,368 suicide victims had schizophrenia and 6,490 had depression. These figures show quite a difference between the results of this study and the police statistics. Further, there have been controversies regarding autopsies of suicide victims. Thus, further investigation into the cause of death is of great importance.

Efficiency Analysis of Public Universities in Thailand

ERIC Educational Resources Information Center

Kantabutra, Saranya; Tang, John C. S.

2010-01-01

This paper examines the performance of Thai public universities in terms of efficiency, using a non-parametric approach called data envelopment analysis. Two efficiency models, the teaching efficiency model and the research efficiency model, are developed and the analysis is conducted at the faculty level. Further statistical analyses are also…

A comparative study between nonlinear regression and nonparametric approaches for modelling Phalaris paradoxa seedling emergence

USDA-ARS?s Scientific Manuscript database

Parametric non-linear regression (PNR) techniques commonly are used to develop weed seedling emergence models. Such techniques, however, require statistical assumptions that are difficult to meet. To examine and overcome these limitations, we compared PNR with a nonparametric estimation technique. F...

Parametric control in coupled fermionic oscillators

NASA Astrophysics Data System (ADS)

Ghosh, Arnab

2014-10-01

A simple model of parametric coupling between two fermionic oscillators is considered. Statistical properties, in particular the mean and variance of quanta for a single mode, are described by means of a time-dependent reduced density operator for the system and the associated P function. The density operator for fermionic fields as introduced by Cahill and Glauber [K. E. Cahill and R. J. Glauber, Phys. Rev. A 59, 1538 (1999), 10.1103/PhysRevA.59.1538] thus can be shown to provide a quantum mechanical description of the fields closely resembling their bosonic counterpart. In doing so, special emphasis is given to population trapping, and quantum control over the states of the system.

Application of Semiparametric Spline Regression Model in Analyzing Factors that In uence Population Density in Central Java

NASA Astrophysics Data System (ADS)

Sumantari, Y. D.; Slamet, I.; Sugiyanto

2017-06-01

Semiparametric regression is a statistical analysis method that consists of parametric and nonparametric regression. There are various approach techniques in nonparametric regression. One of the approach techniques is spline. Central Java is one of the most densely populated province in Indonesia. Population density in this province can be modeled by semiparametric regression because it consists of parametric and nonparametric component. Therefore, the purpose of this paper is to determine the factors that in uence population density in Central Java using the semiparametric spline regression model. The result shows that the factors which in uence population density in Central Java is Family Planning (FP) active participants and district minimum wage.

Photon Statistics of Propagating Thermal Microwaves.

PubMed

Goetz, J; Pogorzalek, S; Deppe, F; Fedorov, K G; Eder, P; Fischer, M; Wulschner, F; Xie, E; Marx, A; Gross, R

2017-03-10

In experiments with superconducting quantum circuits, characterizing the photon statistics of propagating microwave fields is a fundamental task. We quantify the n^{2}+n photon number variance of thermal microwave photons emitted from a blackbody radiator for mean photon numbers, 0.05≲n≲1.5. We probe the fields using either correlation measurements or a transmon qubit coupled to a microwave resonator. Our experiments provide a precise quantitative characterization of weak microwave states and information on the noise emitted by a Josephson parametric amplifier.

Photon Statistics of Propagating Thermal Microwaves

NASA Astrophysics Data System (ADS)

Goetz, J.; Pogorzalek, S.; Deppe, F.; Fedorov, K. G.; Eder, P.; Fischer, M.; Wulschner, F.; Xie, E.; Marx, A.; Gross, R.

2017-03-01

In experiments with superconducting quantum circuits, characterizing the photon statistics of propagating microwave fields is a fundamental task. We quantify the n2+n photon number variance of thermal microwave photons emitted from a blackbody radiator for mean photon numbers, 0.05 ≲n ≲1.5 . We probe the fields using either correlation measurements or a transmon qubit coupled to a microwave resonator. Our experiments provide a precise quantitative characterization of weak microwave states and information on the noise emitted by a Josephson parametric amplifier.

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

Rates of Autism Spectrum Disorder Diagnosis Under the DSM-5 Criteria Compared to DSM-IV-TR Criteria in a Hospital-Based Clinic.

PubMed

Hartley-McAndrew, Michelle; Mertz, Jana; Hoffman, Martin; Crawford, Donald

2016-04-01

We aimed to determine whether there was a decrease in the number of children diagnosed on the autism spectrum after the implementation of the new diagnostic criteria as outlined in the Diagnostic and Statistical Manual of Mental Health Disorders Fifth Edition published in May 2013. We reviewed 1552 charts of children evaluated at the Women and Children's Hospital of Buffalo, Autism Spectrum Disorders Clinic. A comparison was made of children diagnosed with autism spectrum disorder (autism, Asperger disorder, pervasive developmental disorder-not otherwise specified) from 2010 to May 2013 using the Diagnostic and Statistical Manual of Mental Health Disorders Fourth Edition, Text Revision criteria with children diagnosed from June 2013 through June 2015 under the Diagnostic and Statistical Manual of Mental Health Disorders Fifth Edition. Using χ(2) analysis, the 2013-2015 rate of autism spectrum disorder diagnosis (39%) was significantly lower (P < 0.01) than the 2010 to May 2013 sample years rate (50%). The rate of autism spectrum disorder diagnosis was significantly lower under the recently implemented Diagnostic and Statistical Manual of Mental Health Disorders Fifth Edition criteria. Published by Elsevier Inc.

Variable selection in a flexible parametric mixture cure model with interval-censored data.

PubMed

Scolas, Sylvie; El Ghouch, Anouar; Legrand, Catherine; Oulhaj, Abderrahim

2016-03-30

In standard survival analysis, it is generally assumed that every individual will experience someday the event of interest. However, this is not always the case, as some individuals may not be susceptible to this event. Also, in medical studies, it is frequent that patients come to scheduled interviews and that the time to the event is only known to occur between two visits. That is, the data are interval-censored with a cure fraction. Variable selection in such a setting is of outstanding interest. Covariates impacting the survival are not necessarily the same as those impacting the probability to experience the event. The objective of this paper is to develop a parametric but flexible statistical model to analyze data that are interval-censored and include a fraction of cured individuals when the number of potential covariates may be large. We use the parametric mixture cure model with an accelerated failure time regression model for the survival, along with the extended generalized gamma for the error term. To overcome the issue of non-stable and non-continuous variable selection procedures, we extend the adaptive LASSO to our model. By means of simulation studies, we show good performance of our method and discuss the behavior of estimates with varying cure and censoring proportion. Lastly, our proposed method is illustrated with a real dataset studying the time until conversion to mild cognitive impairment, a possible precursor of Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Regional brain changes in bipolar I depression: a functional magnetic resonance imaging study

PubMed Central

Altshuler, Lori; Bookheimer, Susan; Townsend, Jennifer; Proenza, Manuel A; Sabb, Fred; Mintz, Jim; Cohen, Mark S

2011-01-01

Objective To investigate neural activity in prefrontal cortex and amygdala during bipolar depression. Methods Eleven bipolar I depressed and 17 normal subjects underwent functional magnetic resonance imaging (fMRI) while performing a task known to activate prefrontal cortex and amygdala. Whole brain activation patterns were determined using statistical parametric mapping (SPM) when subjects matched faces displaying neutral or negative affect (match condition) or matched a geometric form (control condition). Contrasts for each group for the match versus control conditions were used in a second-level random effects analysis. Results Random effects between-group analysis revealed significant attenuation in right and left orbitofrontal cortex (BA47) and right dorsolateral prefrontal cortex (DLPFC) (BA9) in bipolar depressed subjects. Additionally, random effects analysis showed a significantly increased activation in left lateral orbitofrontal cortex (BA10) in the bipolar depressed versus control subjects. Within-group contrasts demonstrated significant amygdala activation in the controls and no significant amygdala activation in the bipolar depressed subjects. The amygdala between-group difference, however, was not significant. Conclusions Bipolar depression is associated with attenuated bilateral orbitofrontal (BA47) activation, attenuated right DLPFC (BA9) activation and heightened left orbitofrontal (BA10) activation. BA47 attenuation has also been reported in mania and may thus represent a trait feature of the disorder. Increased left prefrontal (BA10) activation may be a state marker to bipolar depression. Our findings suggest dissociation between mood-dependent and disease-dependent functional brain abnormalities in bipolar disorder. PMID:18837865

Neuropsychological and FDG-PET profiles in VGKC autoimmune limbic encephalitis.

PubMed

Dodich, Alessandra; Cerami, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Alongi, Pierpaolo; Crespi, Chiara; Canessa, Nicola; Andreetta, Francesca; Falini, Andrea; Cappa, Stefano F; Perani, Daniela

2016-10-01

Limbic encephalitis (LE) is characterized by an acute or subacute onset with memory impairments, confusional state, behavioral disorders, variably associated with seizures and dystonic movements. It is due to inflammatory processes that selectively affect the medial temporal lobe structures. Voltage-gate potassium channel (VGKC) autoantibodies are frequently observed. In this study, we assessed at the individual level FDG-PET brain metabolic dysfunctions and neuropsychological profiles in three autoimmune LE cases seropositive for neuronal VGKC-complex autoantibodies. LGI1 and CASPR2 potassium channel complex autoantibody subtyping was performed. Cognitive abilities were evaluated with an in-depth neuropsychological battery focused on episodic memory and affective recognition/processing skills. FDG-PET data were analyzed at single-subject level according to a standardized and validated voxel-based Statistical Parametric Mapping (SPM) method. Patients showed severe episodic memory and fear recognition deficits at the neuropsychological assessment. No disorder of mentalizing processing was present. Variable patterns of increases and decreases of brain glucose metabolism emerged in the limbic structures, highlighting the pathology-driven selective vulnerability of this system. Additional involvement of cortical and subcortical regions, particularly in the sensorimotor system and basal ganglia, was found. Episodic memory and fear recognition deficits characterize the cognitive profile of LE. Commonalities and differences may occur in the brain metabolic patterns. Single-subject voxel-based analysis of FDG-PET imaging could be useful in the early detection of the metabolic correlates of cognitive and non-cognitive deficits characterizing LE condition. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparison of the effects of citalopram and moclobemide on resting brain perfusion in social anxiety disorder.

PubMed

Warwick, J M; Carey, P; Van der Linden, G; Prinsloo, C; Niehaus, D; Seedat, S; Dupont, P; Stein, D J

2006-09-01

The serotonin specific reuptake inhibitor (SSRI) citalopram and the reversible mono-amine oxidase-A inhibitor (RIMA) moclobemide have both been used successfully for the treatment of social anxiety disorder (SAD). In this study we investigate the effects of these compounds on resting brain function using single photon emission computed tomography (SPECT). Subjects meeting DSM-IV criteria for SAD underwent regional cerebral blood flow (rCBF) SPECT using Tc-HMPAO at baseline and after 8 weeks of treatment with either citalopram or moclobemide. Using statistical parametric mapping brain SPECT studies were analysed to determine the effects of treatment on rCBF, to compare the effects of citalopram and moclobemide, and to detect correlations between changes in rCBF and clinical response. Subjects received citalopram (n=17) or moclobemide (n=14) as therapy. Subjects in both treatment groups demonstrated a significant improvement of SAD symptoms as measured by the Liebowitz Social Anxiety Scale total score. All subjects demonstrated a decrease in rCBF in the insulae post therapy. Subjects receiving citalopram had decreased superior cingulate rCBF after therapy compared to those receiving moclobemide. Both SSRI's and RIMA's decreased rCBF in the insulae during treatment of SAD; an effect that may be consistent with the role of these regions in processing internal somatic cues evoked by emotional stimuli. Citalopram had a greater effect on superior cingulate perfusion, an effect that is consistent with evidence of high levels of 5-HT transporters in this region.

Panic anxiety, under the weather?

NASA Astrophysics Data System (ADS)

Bulbena, A.; Pailhez, G.; Aceña, R.; Cunillera, J.; Rius, A.; Garcia-Ribera, C.; Gutiérrez, J.; Rojo, C.

2005-03-01

The relationship between weather conditions and psychiatric disorders has been a continuous subject of speculation due to contradictory findings. This study attempts to further clarify this relationship by focussing on specific conditions such as panic attacks and non-panic anxiety in relation to specific meteorological variables. All psychiatric emergencies attended at a general hospital in Barcelona (Spain) during 2002 with anxiety as main complaint were classified as panic or non-panic anxiety according to strict independent and retrospective criteria. Both groups were assessed and compared with meteorological data (wind speed and direction, daily rainfall, temperature, humidity and solar radiation). Seasons and weekend days were also included as independent variables. Non-parametric statistics were used throughout since most variables do not follow a normal distribution. Logistic regression models were applied to predict days with and without the clinical condition. Episodes of panic were three times more common with the poniente wind (hot wind), twice less often with rainfall, and one and a half times more common in autumn than in other seasons. These three trends (hot wind, rainfall and autumn) were accumulative for panic episodes in a logistic regression formula. Significant reduction of episodes on weekends was found only for non-panic episodes. Panic attacks, unlike other anxiety episodes, in a psychiatric emergency department in Barcelona seem to show significant meteorotropism. Assessing specific disorders instead of overall emergencies or other variables of a more general quality could shed new light on the relationship between weather conditions and behaviour.

Widespread abnormality of the γ-aminobutyric acid-ergic system in Tourette syndrome

PubMed Central

Bagic, Anto; Simmons, Janine M.; Mari, Zoltan; Bonne, Omer; Xu, Ben; Kazuba, Diane; Herscovitch, Peter; Carson, Richard E.; Murphy, Dennis L.; Drevets, Wayne C.; Hallett, Mark

2012-01-01

Dysfunction of the γ-aminobutyric acid-ergic system in Tourette syndrome may conceivably underlie the symptoms of motor disinhibition presenting as tics and psychiatric manifestations, such as attention deficit hyperactivity disorder and obsessive–compulsive disorder. The purpose of this study was to identify a possible dysfunction of the γ-aminobutyric acid-ergic system in Tourette patients, especially involving the basal ganglia-thalamo-cortical circuits and the cerebellum. We studied 11 patients with Tourette syndrome and 11 healthy controls. Positron emission tomography procedure: after injection of 20 mCi of [11C]flumazenil, dynamic emission images of the brain were acquired. Structural magnetic resonance imaging scans were obtained to provide an anatomical framework for the positron emission tomography data analysis. Images of binding potential were created using the two-step version of the simplified reference tissue model. The binding potential images then were spatially normalized, smoothed and compared between groups using statistical parametric mapping. We found decreased binding of GABAA receptors in Tourette patients bilaterally in the ventral striatum, globus pallidus, thalamus, amygdala and right insula. In addition, the GABAA receptor binding was increased in the bilateral substantia nigra, left periaqueductal grey, right posterior cingulate cortex and bilateral cerebellum. These results are consistent with the longstanding hypothesis that circuits involving the basal ganglia and thalamus are disinhibited in Tourette syndrome patients. In addition, the abnormalities in GABAA receptor binding in the insula and cerebellum appear particularly noteworthy based upon recent evidence implicating these structures in the generation of tics. PMID:22577221

Multimodal voxel-based meta-analysis of white matter abnormalities in obsessive-compulsive disorder.

PubMed

Radua, Joaquim; Grau, Mar; van den Heuvel, Odile A; Thiebaut de Schotten, Michel; Stein, Dan J; Canales-Rodríguez, Erick J; Catani, Marco; Mataix-Cols, David

2014-06-01

White matter (WM) abnormalities have long been suspected in obsessive-compulsive disorder (OCD) but the available evidence has been inconsistent. We conducted the first multimodal meta-analysis of WM volume (WMV) and fractional anisotropy (FA) studies in OCD. All voxel-wise studies comparing WMV or FA between patients with OCD and healthy controls in the PubMed, ScienceDirect, Google Scholar, Web of Knowledge and Scopus databases were retrieved. Manual searches were also conducted and authors were contacted soliciting additional data. Thirty-four data sets were identified, of which 22 met inclusion criteria (five of them unpublished; comprising 537 adult and pediatric patients with OCD and 575 matched healthy controls). Whenever possible, raw statistical parametric maps were also obtained from the authors. Peak and raw WMV and FA data were combined using novel multimodal meta-analytic methods implemented in effect-size signed differential mapping. Patients with OCD showed widespread WM abnormalities, but findings were particularly robust in the anterior midline tracts (crossing between anterior parts of cingulum bundle and body of corpus callosum), which showed both increased WMV and decreased FA, possibly suggesting an increase of fiber crossing in these regions. This finding was also observed when the analysis was limited to adult participants, and especially pronounced in samples with a higher proportion of medicated patients. Therefore, patients with OCD may have widespread WM abnormalities, particularly evident in anterior midline tracts, although these changes might be, at least in part, attributable to the effects of therapeutic drugs.

Genome-wide scan for genes involved in bipolar affective disorder in 70 European families ascertained through a bipolar type I early-onset proband: supportive evidence for linkage at 3p14

PubMed Central

Etain, Bruno; Mathieu, Flavie; Rietschel, Marcella; Maier, Wolfgang; Albus, Margot; Mckeon, Patrick; Roche, S.; Kealey, Carmel; Blackwood, Douglas; Muir, Walter; Bellivier, Franc; Henry, C.; Dina, Christian; Gallina, Sophie; Gurling, H.; Malafosse, Alain; Preisig, Martin; Ferrero, François; Cichon, Sven; Schumacher, J.; Ohlraun, Stéphanie; Borrmann-Hassenbach, M.; Propping, Peter; Abou Jamra, Rami; Schulze, Thomas G.; Marusic, Andrej; Dernovsek, Mojca Z.; Giros, Bruno; Bourgeron, Thomas; Lemainque, Arnaud; Bacq, Delphine; Betard, Christine; Charon, Céline; Nöthen, Markus M.; Lathrop, Mark; Leboyer, Marion

2006-01-01

Summary Preliminary studies suggested that age at onset (AAO) may help to define homogeneous bipolar affective disorder (BPAD) subtypes. This candidate symptom approach might be useful to identify vulnerability genes. Thus, the probability of detecting major disease-causing genes might be increased by focusing on families with early-onset BPAD type I probands. This study was conducted as part of the European Collaborative Study of Early Onset BPAD (France, Germany, Ireland, Scotland, Switzerland, England, Slovenia). We performed a genome-wide search with 384 microsatellite markers using non parametric linkage analysis in 87 sib-pairs ascertained through an early-onset BPAD type I proband (age at onset of 21 years or below). Non parametric multi-point analysis suggested eight regions of linkage with p-values <0.01 (2p21, 2q14.3, 3p14, 5q33, 7q36, 10q23, 16q23 and 20p12). The 3p14 region showed the most significant linkage (genome-wide p-value estimated over 10.000 simulated replicates of 0.015 [0.01–0.02]). After genome-wide search analysis, we performed additional linkage analyses with increase marker density using markers in four regions suggestive for linkage and having an information contents lower than 75% (3p14, 10q23, 16q23 and 20p12). For these regions, the information content improved by about 10%. In chromosome 3, the non parametric linkage score increased from 3.51 to 3.83. This study is the first to use early onset bipolar type I probands in an attempt to increase sample homogeneity. These preliminary findings require confirmation in independent panels of families. PMID:16534504

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database.

Assessing the Kansas water-level monitoring program: An example of the application of classical statistics to a geological problem

USGS Publications Warehouse

Davis, J.C.

2000-01-01

Geologists may feel that geological data are not amenable to statistical analysis, or at best require specialized approaches such as nonparametric statistics and geostatistics. However, there are many circumstances, particularly in systematic studies conducted for environmental or regulatory purposes, where traditional parametric statistical procedures can be beneficial. An example is the application of analysis of variance to data collected in an annual program of measuring groundwater levels in Kansas. Influences such as well conditions, operator effects, and use of the water can be assessed and wells that yield less reliable measurements can be identified. Such statistical studies have resulted in yearly improvements in the quality and reliability of the collected hydrologic data. Similar benefits may be achieved in other geological studies by the appropriate use of classical statistical tools.

Redefining Autism Spectrum Disorder Using DSM-5: The Implications of the Proposed DSM-5 Criteria for Autism Spectrum Disorders

ERIC Educational Resources Information Center

Young, Robyn L.; Rodi, Melissa L.

2014-01-01

A number of changes were made to pervasive developmental disorders (PDDs) in the recently released diagnostic and statistical manual of mental disorders (APA, "Diagnostic and statistical manual of mental disorders," American Psychiatric Publishing, Arlington, VA, 2013). Of the 210 participants in the present study who met DSM-IV-TR…

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

Nonparametric estimation and testing of fixed effects panel data models

PubMed Central

Henderson, Daniel J.; Carroll, Raymond J.; Li, Qi

2009-01-01

In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test between the three alternatives in practice. We further propose a test statistic for testing the null hypothesis of random effects against fixed effects in a nonparametric panel data regression model. Simulations are used to examine the finite sample performance of the proposed estimators and the test statistics. PMID:19444335

A statistical method (cross-validation) for bone loss region detection after spaceflight

PubMed Central

Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

2010-01-01

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

PubMed

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

STAPP: Spatiotemporal analysis of plantar pressure measurements using statistical parametric mapping.

PubMed

Booth, Brian G; Keijsers, Noël L W; Sijbers, Jan; Huysmans, Toon

2018-05-03

Pedobarography produces large sets of plantar pressure samples that are routinely subsampled (e.g. using regions of interest) or aggregated (e.g. center of pressure trajectories, peak pressure images) in order to simplify statistical analysis and provide intuitive clinical measures. We hypothesize that these data reductions discard gait information that can be used to differentiate between groups or conditions. To test the hypothesis of null information loss, we created an implementation of statistical parametric mapping (SPM) for dynamic plantar pressure datasets (i.e. plantar pressure videos). Our SPM software framework brings all plantar pressure videos into anatomical and temporal correspondence, then performs statistical tests at each sampling location in space and time. Novelly, we introduce non-linear temporal registration into the framework in order to normalize for timing differences within the stance phase. We refer to our software framework as STAPP: spatiotemporal analysis of plantar pressure measurements. Using STAPP, we tested our hypothesis on plantar pressure videos from 33 healthy subjects walking at different speeds. As walking speed increased, STAPP was able to identify significant decreases in plantar pressure at mid-stance from the heel through the lateral forefoot. The extent of these plantar pressure decreases has not previously been observed using existing plantar pressure analysis techniques. We therefore conclude that the subsampling of plantar pressure videos - a task which led to the discarding of gait information in our study - can be avoided using STAPP. Copyright © 2018 Elsevier B.V. All rights reserved.

Prospective multi-centre Voxel Based Morphometry study employing scanner specific segmentations: Procedure development using CaliBrain structural MRI data

PubMed Central

2009-01-01

Background Structural Magnetic Resonance Imaging (sMRI) of the brain is employed in the assessment of a wide range of neuropsychiatric disorders. In order to improve statistical power in such studies it is desirable to pool scanning resources from multiple centres. The CaliBrain project was designed to provide for an assessment of scanner differences at three centres in Scotland, and to assess the practicality of pooling scans from multiple-centres. Methods We scanned healthy subjects twice on each of the 3 scanners in the CaliBrain project with T1-weighted sequences. The tissue classifier supplied within the Statistical Parametric Mapping (SPM5) application was used to map the grey and white tissue for each scan. We were thus able to assess within scanner variability and between scanner differences. We have sought to correct for between scanner differences by adjusting the probability mappings of tissue occupancy (tissue priors) used in SPM5 for tissue classification. The adjustment procedure resulted in separate sets of tissue priors being developed for each scanner and we refer to these as scanner specific priors. Results Voxel Based Morphometry (VBM) analyses and metric tests indicated that the use of scanner specific priors reduced tissue classification differences between scanners. However, the metric results also demonstrated that the between scanner differences were not reduced to the level of within scanner variability, the ideal for scanner harmonisation. Conclusion Our results indicate the development of scanner specific priors for SPM can assist in pooling of scan resources from different research centres. This can facilitate improvements in the statistical power of quantitative brain imaging studies. PMID:19445668

New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings.

PubMed

Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia

2016-06-01

Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.

A Model Fit Statistic for Generalized Partial Credit Model

ERIC Educational Resources Information Center

Liang, Tie; Wells, Craig S.

2009-01-01

Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…

Generalizations and Extensions of the Probability of Superiority Effect Size Estimator

ERIC Educational Resources Information Center

Ruscio, John; Gera, Benjamin Lee

2013-01-01

Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…

A Nonparametric K-Sample Test for Equality of Slopes.

ERIC Educational Resources Information Center

Penfield, Douglas A.; Koffler, Stephen L.

1986-01-01

The development of a nonparametric K-sample test for equality of slopes using Puri's generalized L statistic is presented. The test is recommended when the assumptions underlying the parametric model are violated. This procedure replaces original data with either ranks (for data with heavy tails) or normal scores (for data with light tails).…

A Bootstrap Generalization of Modified Parallel Analysis for IRT Dimensionality Assessment

ERIC Educational Resources Information Center

Finch, Holmes; Monahan, Patrick

2008-01-01

This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…

Performance of DIMTEST-and NOHARM-Based Statistics for Testing Unidimensionality

ERIC Educational Resources Information Center

Finch, Holmes; Habing, Brian

2007-01-01

This Monte Carlo study compares the ability of the parametric bootstrap version of DIMTEST with three goodness-of-fit tests calculated from a fitted NOHARM model to detect violations of the assumption of unidimensionality in testing data. The effectiveness of the procedures was evaluated for different numbers of items, numbers of examinees,…

Development of a Scaling Technique for Sociometric Data.

ERIC Educational Resources Information Center

Peper, John B.; Chansky, Norman M.

This study explored the stability and interjudge agreements of a sociometric scaling device to which children could easily respond, which teachers could easily administer and score, and which provided scores that researchers could use in parametric statistical analyses. Each student was paired with every other member of his class. He voted on each…

Bootstrapping in Applied Linguistics: Assessing Its Potential Using Shared Data

ERIC Educational Resources Information Center

Plonsky, Luke; Egbert, Jesse; Laflair, Geoffrey T.

2015-01-01

Parametric analyses such as t tests and ANOVAs are the norm--if not the default--statistical tests found in quantitative applied linguistics research (Gass 2009). Applied statisticians and one applied linguist (Larson-Hall 2010, 2012; Larson-Hall and Herrington 2010), however, have argued that this approach may not be appropriate for small samples…

Tsallis p, q-deformed Touchard polynomials and Stirling numbers

NASA Astrophysics Data System (ADS)

Herscovici, O.; Mansour, T.

2017-01-01

In this paper, we develop and investigate a new two-parametrized deformation of the Touchard polynomials, based on the definition of the NEXT q-exponential function of Tsallis. We obtain new generalizations of the Stirling numbers of the second kind and of the binomial coefficients and represent two new statistics for the set partitions.

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

Learning Patterns as Criterion for Forming Work Groups in 3D Simulation Learning Environments

ERIC Educational Resources Information Center

Maria Cela-Ranilla, Jose; Molías, Luis Marqués; Cervera, Mercè Gisbert

2016-01-01

This study analyzes the relationship between the use of learning patterns as a grouping criterion to develop learning activities in the 3D simulation environment at University. Participants included 72 Spanish students from the Education and Marketing disciplines. Descriptive statistics and non-parametric tests were conducted. The process was…

Comparison of Kasai Autocorrelation and Maximum Likelihood Estimators for Doppler Optical Coherence Tomography

PubMed Central

Chan, Aaron C.; Srinivasan, Vivek J.

2013-01-01

In optical coherence tomography (OCT) and ultrasound, unbiased Doppler frequency estimators with low variance are desirable for blood velocity estimation. Hardware improvements in OCT mean that ever higher acquisition rates are possible, which should also, in principle, improve estimation performance. Paradoxically, however, the widely used Kasai autocorrelation estimator’s performance worsens with increasing acquisition rate. We propose that parametric estimators based on accurate models of noise statistics can offer better performance. We derive a maximum likelihood estimator (MLE) based on a simple additive white Gaussian noise model, and show that it can outperform the Kasai autocorrelation estimator. In addition, we also derive the Cramer Rao lower bound (CRLB), and show that the variance of the MLE approaches the CRLB for moderate data lengths and noise levels. We note that the MLE performance improves with longer acquisition time, and remains constant or improves with higher acquisition rates. These qualities may make it a preferred technique as OCT imaging speed continues to improve. Finally, our work motivates the development of more general parametric estimators based on statistical models of decorrelation noise. PMID:23446044

Genome-wide regression and prediction with the BGLR statistical package.

PubMed

Pérez, Paulino; de los Campos, Gustavo

2014-10-01

Many modern genomic data analyses require implementing regressions where the number of parameters (p, e.g., the number of marker effects) exceeds sample size (n). Implementing these large-p-with-small-n regressions poses several statistical and computational challenges, some of which can be confronted using Bayesian methods. This approach allows integrating various parametric and nonparametric shrinkage and variable selection procedures in a unified and consistent manner. The BGLR R-package implements a large collection of Bayesian regression models, including parametric variable selection and shrinkage methods and semiparametric procedures (Bayesian reproducing kernel Hilbert spaces regressions, RKHS). The software was originally developed for genomic applications; however, the methods implemented are useful for many nongenomic applications as well. The response can be continuous (censored or not) or categorical (either binary or ordinal). The algorithm is based on a Gibbs sampler with scalar updates and the implementation takes advantage of efficient compiled C and Fortran routines. In this article we describe the methods implemented in BGLR, present examples of the use of the package, and discuss practical issues emerging in real-data analysis. Copyright © 2014 by the Genetics Society of America.

Non-parametric early seizure detection in an animal model of temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Spano, Mark L.; Simonotto, Jennifer; Furman, Michael D.; Myers, Stephen M.; Winters, Jason T.; Ditto, William L.; Carney, Paul R.

2008-03-01

The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.

DSM-5 ASD Moves Forward into the Past

ERIC Educational Resources Information Center

Tsai, Luke Y.; Ghaziuddin, Mohammad

2014-01-01

The fifth edition of the diagnostic and statistical manual of mental disorders (DSM-5) (APA in diagnostic and statistical manual of mental disorders, Author, Washington, 2013) has decided to merge the subtypes of pervasive developmental disorders into a single category of autism spectrum disorder (ASD) on the assumption that they cannot be…

Dysbindin modulates brain function during visual processing in children.

PubMed

Mechelli, A; Viding, E; Kumar, A; Pettersson-Yeo, W; Fusar-Poli, P; Tognin, S; O'Donovan, M C; McGuire, P

2010-01-01

Schizophrenia is a neurodevelopmental disorder, and risk genes are thought to act through disruption of brain development. Several genetic studies have identified dystrobrevin binding protein 1 (DTNBP1, also known as dysbindin) as a potential susceptibility gene for schizophrenia, but its impact on brain function is poorly understood. It has been proposed that DTNBP1 may be associated with differences in visual processing. To test this, we examined the impact on visual processing in 61 healthy children aged 10-12 years of a genetic variant in DTNBP1 (rs2619538) that was common to all schizophrenia associated haplotypes in an earlier UK-Irish study. We tested the hypothesis that carriers of the risk allele would show altered occipital cortical function relative to noncarriers. Functional Magnetic Resonance Imaging (fMRI) was used to measure brain responses during a visual matching task. The data were analysed using statistical parametric mapping and statistical inferences were made at p<0.05 (corrected for multiple comparisons). Relative to noncarriers, carriers of the risk allele had greater activation in the lingual, fusiform gyrus and inferior occipital gyri. In these regions DTNBP1 genotype accounted for 19%, 20% and 14% of the inter-individual variance, respectively. Our results suggest that that genetic variation in DTNBP1 is associated with differences in the function of brain areas that mediate visual processing, and that these effects are evident in young children. These findings are consistent with the notion that the DTNBP1 gene influences brain development and can thereby modulate vulnerability to schizophrenia.

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

PubMed

Rose, Sherri

2018-03-11

To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

Parametric inference for biological sequence analysis.

PubMed

Pachter, Lior; Sturmfels, Bernd

2004-11-16

One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.

Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

NASA Astrophysics Data System (ADS)

Dai, Xiaoqian; Tian, Jie; Chen, Zhe

2010-03-01

Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.

Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

NASA Astrophysics Data System (ADS)

Han, Feng; Zheng, Yi

2018-06-01

Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

Frequency Analysis Using Bootstrap Method and SIR Algorithm for Prevention of Natural Disasters

NASA Astrophysics Data System (ADS)

Kim, T.; Kim, Y. S.

2017-12-01

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results show that probabilistic daily snowfall depth by frequency analysis is decreased at most stations, and most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics. Acknowledgment.This research was supported by a grant(MPSS-NH-2015-79) from Disaster Prediction and Mitigation Technology Development Program funded by Korean Ministry of Public Safety and Security(MPSS).

Introduction to multivariate discrimination

NASA Astrophysics Data System (ADS)

Kégl, Balázs

2013-07-01

Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either relevant to or even motivated by certain unorthodox applications of multivariate discrimination in experimental physics.

Post-Traumatic Stress Disorder after childbirth and the influence of maternity team care during labour and birth: A cohort study.

PubMed

De Schepper, Sarah; Vercauteren, Tinne; Tersago, Jolein; Jacquemyn, Yves; Raes, Filip; Franck, Erik

2016-01-01

we examined the prevalence of Post-Traumatic Stress Disorder (PTSD) and the role of personal and obstetric risk factors, as well as the role of midwifery team care factors in a cohort of Flemish women. prospective cohort study. Data collection was performed at two times post partum: During the first week, socio-demographic and obstetric data as well as information related to midwifery team care factors were assessed using self-report measures. To asses PTSD symptomatology, the Impact of Event Scale-Revised (IES-R) and the Traumatic Event Scale (TES) were used. At six weeks post partum, PTSD symptoms were reassessed either by telephone interviews or e-mail. Results were calculated in frequencies, means and standard deviations. Differences between week one and six were analysed using parametrical and non-parametrical statistics. Multiple and logistic regression was performed to determine risk factors for PTSD symptomatology. P-value was set at 0.05. maternity wards in Flanders, Belgium. the first (week 1) and follow-up (week 6) sample of the data collection consisted of 340 and 229 women respectively. the prevalence of PTSD symptoms after childbirth ranged from 22% to 24% in the first week and from 13% to 20% at six weeks follow-up. Multiple regression analysis showed that Islamic belief, a traumatic childbirth experience, family income <€2500, a history of psychological or psychiatric consults and labour/birth with complications significantly predicted PTSD symptomatology at six weeks post-birth. Midwifery team care and the opportunity to ask questions, as well as experiencing a normal physiological birth were significantly associated with less postnatal PTSD symptoms. KEY CONCLUSIONS AND IMPLICATIONS FOR PRACTISE: the results of this study suggest that contextual factors such as religion, socio-economic status, and childbirth experience might be important factors to address by the midwifery team. Midwifery team care factors such as 'providing the opportunity to the mother to ask questions' and the 'perception of the midwife being in control' proved to be potential protective factors for postnatal PTSD symptoms. Despite its prevalence, PTSD symptoms after birth are not yet well understood by health care workers. Further research concerning the influence of midwifery team care factors on developing childbirth related PTSD is required. Copyright © 2015 Elsevier Ltd. All rights reserved.

Preliminary results of using ALAnerv® in subacute motor incomplete paraplegics.

PubMed

Andone, I; Anghelescu, A; Daia, C; Onose, G

2015-01-01

To assess whether using ALAnerv® contributes to improvements of outcomes obtained in post SCI patients. A prospective controlled clinical survey also to evaluate the safety and efficacy of ALAnerv® (2cps/ day for 28 days) in motor incomplete (AIS/ Frankel C) paraplegic subacute patients. 59 patients divided in study (treated with ALAnerv®) and control, groups. This survey's follow-up duration was of 28 days. Most of the studied patients were mid-aged (mean 43.75 years old) and respectively, men (64,29% in the study group; 58,06% in controls). We used descriptive statistics (functions: minimum, maximum, mean, median, standard deviation) and for related comparisons, parametric (Student t) and non-parametric (Mann-Whitney, Fisher's exact, chi-square) tests. The primary end-point: AIS motor values' evolution (P= 0.015 - Mann-Whitney), showed that patients treated with ALAnerv® - vs. controls - had a statistically significant better increase of such scores at discharge. Paraclinical parameters, mainly exploring systemic inflammatory status (secondary end-point): ESR dynamics (P=0.13) had no statistical significance; the plasma leucocytes number (P=0.018), the neutrophils' percentage (P=0.001) and fibrinogenemia (P= 0,017) proved in the treated group to have a statistically significant better evolution. We used "Statistical Package for Social Sciences" (SPSS). As there is actually no effective curative solution for the devastating pathology following SCI, any medical approach susceptible to bring even limited improvements, such as treatment with ALAnerv® seemed to have proven, is worth being surveyed, under strict circumstances of ethics and research methodology. Considering the necessity for more statistical power concerning primary, secondary end-points, and safety issues, as well, continuing this research is needed. SCI = spinal cord injury, TSCI = traumatic spinal cord injury, BBB = blood brain barrier, CNS = central nervous system, SC = spinal cord, NSAIDs = non-steroidal anti-inflammatory drugs, SAIDs = steroidal anti-inflammatory drugs, AIS = American Spinal Injury Association Impairment Scale, SPSS = Statistical Package for Social Sciences, BATEH = Bagdasar-Arseni Teaching Emergency Hospital.

Dark energy models through nonextensive Tsallis' statistics

NASA Astrophysics Data System (ADS)

Barboza, Edésio M.; Nunes, Rafael da C.; Abreu, Everton M. C.; Ananias Neto, Jorge

2015-10-01

The accelerated expansion of the Universe is one of the greatest challenges of modern physics. One candidate to explain this phenomenon is a new field called dark energy. In this work we have used the Tsallis nonextensive statistical formulation of the Friedmann equation to explore the Barboza-Alcaniz and Chevalier-Polarski-Linder parametric dark energy models and the Wang-Meng and Dalal vacuum decay models. After that, we have discussed the observational tests and the constraints concerning the Tsallis nonextensive parameter. Finally, we have described the dark energy physics through the role of the q-parameter.

[Comorbidity of different forms of anxiety disorders and depression].

PubMed

Małyszczak, Krzysztof; Szechiński, Marcin

2004-01-01

Comorbidity of some anxiety disorders and depression were examined in order to compare their statistical closeness. Patients treated in an out-patient care center for psychiatric disorders and/or family medicine were recruited. Persons that have anxiety and depressive symptoms as a consequence of somatic illnesses or consequence of other psychiatric disorders were excluded. Disorders were diagnosed a with diagnostic questionnaire based on Schedule for Assessment in Neuropsychiatry (SCAN), version 2.0, according to ICD-10 criteria. Analyses include selected disorders: generalized anxiety disorder, panic disorder, agoraphobia, specific phobias, social phobia and depression. 104 patients were included. 35 of them (33.7%) had anxiety disorders, 13 persons (12.5%) have depression. Analyses show that in patients with generalized anxiety disorder, depression occurred at least twice as often as in the remaining patients (odds ratio = 7.1), while in patients with agoraphobia the occurrence of panic disorder increased at least by 2.88 times (odds ratio = 11.9). In other disorders the odds ratios was greater than 1, but the differences were not statistically significant. Depression/generalized anxiety disorder and agoraphobia/panic disorder were shown to be statistically closer than other disorders.

Disorder and superfluid density in overdoped cuprate superconductors

NASA Astrophysics Data System (ADS)

Lee-Hone, N. R.; Dodge, J. S.; Broun, D. M.

2017-07-01

We calculate superfluid density for a dirty d -wave superconductor. The effects of impurity scattering are treated within the self-consistent t -matrix approximation, in weak-coupling BCS theory. Working from a realistic tight-binding parametrization of the Fermi surface, we find a superfluid density that is both correlated with Tc and linear in temperature, in good correspondence with recent experiments on overdoped La2 -xSrxCuO4 .

MMPI-2 profiles of Gulf and Vietnam combat veterans with chronic posttraumatic stress disorder.

PubMed

Glenn, D Michael; Beckham, Jean C; Sampson, William S; Feldman, Michelle E; Hertzberg, Michael A; Moore, Scott D

2002-04-01

The current study examined service era differences in a sample of 172 Gulf and Vietnam outpatient veterans with combat-related posttraumatic stress disorder (PTSD). Participants completed the MMPI-2 and several additional self-report measures of symptom severity (PTSD, depression, anxiety, hostility, and health complaints). Results indicated that MMPI-2 profiles differed significantly according to service era with Vietnam veterans scoring higher on scales 2, 8, and 0 and lower on scale 9 than did Gulf veterans. Examination of group means derived from parametric analysis of MMPI-2 data suggested a mean two-point code type of 2-8/8-2 for Vietnam veterans and 1-8/8-1 for Gulf veterans. In contrast, when the data were examined using descriptive techniques based on frequency counts of individual MMPI-2 profiles, the most frequently occurring two-point codetype was 7-8/8-7 for Vietnam veterans, and 6-8/8-6 for Gulf veterans. In addition, Gulf veterans reported a greater number of total health complaints than Vietnam veterans, whereas Vietnam veterans reported a greater number of physician-diagnosed physical conditions. Potential advantages of incorporating descriptive approaches versus parametric methods when examining profile data are also presented. Copyright 2002 Wiley Periodicals, Inc.

A Backward-Lagrangian-Stochastic Footprint Model for the Urban Environment

NASA Astrophysics Data System (ADS)

Wang, Chenghao; Wang, Zhi-Hua; Yang, Jiachuan; Li, Qi

2018-02-01

Built terrains, with their complexity in morphology, high heterogeneity, and anthropogenic impact, impose substantial challenges in Earth-system modelling. In particular, estimation of the source areas and footprints of atmospheric measurements in cities requires realistic representation of the landscape characteristics and flow physics in urban areas, but has hitherto been heavily reliant on large-eddy simulations. In this study, we developed physical parametrization schemes for estimating urban footprints based on the backward-Lagrangian-stochastic algorithm, with the built environment represented by street canyons. The vertical profile of mean streamwise velocity is parametrized for the urban canopy and boundary layer. Flux footprints estimated by the proposed model show reasonable agreement with analytical predictions over flat surfaces without roughness elements, and with experimental observations over sparse plant canopies. Furthermore, comparisons of canyon flow and turbulence profiles and the subsequent footprints were made between the proposed model and large-eddy simulation data. The results suggest that the parametrized canyon wind and turbulence statistics, based on the simple similarity theory used, need to be further improved to yield more realistic urban footprint modelling.

Power flow analysis of two coupled plates with arbitrary characteristics

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1988-01-01

The limitation of keeping two plates identical is removed and the vibrational power input and output are evaluated for different area ratios, plate thickness ratios, and for different values of the structural damping loss factor for the source plate (plate with excitation) and the receiver plate. In performing this parametric analysis, the source plate characteristics are kept constant. The purpose of this parametric analysis is to be able to determine the most critical parameters that influence the flow of vibrational power from the source plate to the receiver plate. In the case of the structural damping parametric analysis, the influence of changes in the source plate damping is also investigated. As was done previously, results obtained from the mobility power flow approach will be compared to results obtained using a statistical energy analysis (SEA) approach. The significance of the power flow results are discussed together with a discussion and a comparison between SEA results and the mobility power flow results. Furthermore, the benefits that can be derived from using the mobility power flow approach, are also examined.

Parametric Model Based On Imputations Techniques for Partly Interval Censored Data

NASA Astrophysics Data System (ADS)

Zyoud, Abdallah; Elfaki, F. A. M.; Hrairi, Meftah

2017-12-01

The term ‘survival analysis’ has been used in a broad sense to describe collection of statistical procedures for data analysis. In this case, outcome variable of interest is time until an event occurs where the time to failure of a specific experimental unit might be censored which can be right, left, interval, and Partly Interval Censored data (PIC). In this paper, analysis of this model was conducted based on parametric Cox model via PIC data. Moreover, several imputation techniques were used, which are: midpoint, left & right point, random, mean, and median. Maximum likelihood estimate was considered to obtain the estimated survival function. These estimations were then compared with the existing model, such as: Turnbull and Cox model based on clinical trial data (breast cancer data), for which it showed the validity of the proposed model. Result of data set indicated that the parametric of Cox model proved to be more superior in terms of estimation of survival functions, likelihood ratio tests, and their P-values. Moreover, based on imputation techniques; the midpoint, random, mean, and median showed better results with respect to the estimation of survival function.

Study design and statistical analysis of data in human population studies with the micronucleus assay.

PubMed

Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano

2011-01-01

The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.

Disordered eating behavior and mental health correlates among treatment seeking obese women.

PubMed

Altamura, M; Rossi, G; Aquilano, P; De Fazio, P; Segura-Garcia, C; Rossetti, M; Petrone, A; Lo Russo, T; Vendemiale, G; Bellomo, A

2015-01-01

Previous research has suggest that obesity is associated with increased risk for psychopathological disorders, however, little is known about which obese patients are most vulnerable to psychopathological disorders. We therefore investigated 126 treatment-seeking obese women to describe eating disorder pathology and mental health correlates, and to identify disordered eating behaviors that may place obese at increased risk for psychopathological disorders. The Structured Clinical Interview for DSM-IV (SCID) was used to identify Eating Disorders (ED). A battery of psychological tests, including the Anxiety Scale Questionnaire (ASQ,) Clinical Depression Questionnaire (CDQ), Eating Disorder Inventory-2 (EDI-2) Eating Attitudes Test-26 (EAT-26) scales and structured clinical interview were administered to all the patients. We analyzed the link between psychopathological disorders and eating attitudes by using both multiple regression analysis and non-parametric correlation. Disordered eating behaviors and emotional behavioral aspects related to Anorexia Nervosa, such as ineffectiveness, are strongly linked to the depression and anxiety in obese subjects. No correlation was found between psychopathological disorders and age or anthropometric measurements. Findings corroborate earlier work indicating that psychological distress is elevated in obese treatment seeking, bolstering the need for mental health assessment of such individuals. The feeling of ineffectiveness constitutes the major predictor of psychopathological aspects. This is an important result which may inform the development of effective interventions for obese patients and prevention of psychopathological disorders.

The extension of the parametrization of the radio source coordinates in geodetic VLBI and its impact on the time series analysis

NASA Astrophysics Data System (ADS)

Karbon, Maria; Heinkelmann, Robert; Mora-Diaz, Julian; Xu, Minghui; Nilsson, Tobias; Schuh, Harald

2017-07-01

The radio sources within the most recent celestial reference frame (CRF) catalog ICRF2 are represented by a single, time-invariant coordinate pair. The datum sources were chosen mainly according to certain statistical properties of their position time series. Yet, such statistics are not applicable unconditionally, and also ambiguous. However, ignoring systematics in the source positions of the datum sources inevitably leads to a degradation of the quality of the frame and, therefore, also of the derived quantities such as the Earth orientation parameters. One possible approach to overcome these deficiencies is to extend the parametrization of the source positions, similarly to what is done for the station positions. We decided to use the multivariate adaptive regression splines algorithm to parametrize the source coordinates. It allows a great deal of automation, by combining recursive partitioning and spline fitting in an optimal way. The algorithm finds the ideal knot positions for the splines and, thus, the best number of polynomial pieces to fit the data autonomously. With that we can correct the ICRF2 a priori coordinates for our analysis and eliminate the systematics in the position estimates. This allows us to introduce also special handling sources into the datum definition, leading to on average 30 % more sources in the datum. We find that not only the CPO can be improved by more than 10 % due to the improved geometry, but also the station positions, especially in the early years of VLBI, can benefit greatly.

Family members' involvement in psychiatric care: experiences of the healthcare professionals' approach and feeling of alienation.

PubMed

Ewertzon, M; Lützén, K; Svensson, E; Andershed, B

2010-06-01

The involvement of family members in psychiatric care is important for the recovery of persons with psychotic disorders and subsequently reduces the burden on the family. Earlier qualitative studies suggest that the participation of family members can be limited by how they experience the professionals' approach, which suggests a connection to the concept of alienation. Thus, the aim of this study was in a national sample investigate family members' experiences of the psychiatric health care professionals' approach. Data were collected by the Family Involvement and Alienation Questionnaire. The median level and quartiles were used to describe the distributions and data were analysed with non-parametric statistical methods. Seventy family members of persons receiving psychiatric care participated in the study. The results indicate that a majority of the participants respond that they have experiencing a negative approach from the professionals, indicating lack of confirmation and cooperation. The results also indicate that a majority of the participants felt powerlessness and social isolation in the care being provided, indicating feelings of alienation. A significant but weak association was found between the family members' experiences of the professionals' approach and their feelings of alienation.

Iterative Structural and Functional Synergistic Resolution Recovery (iSFS-RR) Applied to PET-MR Images in Epilepsy

NASA Astrophysics Data System (ADS)

Silva-Rodríguez, J.; Cortés, J.; Rodríguez-Osorio, X.; López-Urdaneta, J.; Pardo-Montero, J.; Aguiar, P.; Tsoumpas, C.

2016-10-01

Structural Functional Synergistic Resolution Recovery (SFS-RR) is a technique that uses supplementary structural information from MR or CT to improve the spatial resolution of PET or SPECT images. This wavelet-based method may have a potential impact on the clinical decision-making of brain focal disorders such as refractory epilepsy, since it can produce images with better quantitative accuracy and enhanced detectability. In this work, a method for the iterative application of SFS-RR (iSFS-RR) was firstly developed and optimized in terms of convergence and input voxel size, and the corrected images were used for the diagnosis of 18 patients with refractory epilepsy. To this end, PET/MR images were clinically evaluated through visual inspection, atlas-based asymmetry indices (AIs) and SPM (Statistical Parametric Mapping) analysis, using uncorrected images and images corrected with SFS-RR and iSFS-RR. Our results showed that the sensitivity can be increased from 78% for uncorrected images, to 84% for SFS-RR and 94% for the proposed iSFS-RR. Thus, the proposed methodology has demonstrated the potential to improve the management of refractory epilepsy patients in the clinical routine.

Physicians’ Perspectives on the Uncertainties and Implications of Chromosomal Microarray Testing of Children and Families

PubMed Central

Reiff, Marian; Ross, Kathryn; Mulchandani, Surabhi; Propert, Kathleen Joy; Pyeritz, Reed E.; Spinner, Nancy B.; Bernhardt, Barbara A.

2012-01-01

Chromosomal microarray analysis (CMA) has improved the diagnostic rate of genomic disorders in pediatric populations, but can produce uncertain and unexpected findings. This paper explores clinicians’ perspectives and identifies challenges in effectively interpreting results and communicating with families about CMA. Responses to an online survey were obtained from 40 clinicians who had ordered CMA. Content included practice characteristics and perceptions, and queries about a hypothetical case involving uncertain and incidental findings. Data were analyzed using non-parametric statistical tests. Clinicians’ comfort levels differed significantly for explaining uncertain, abnormal, and normal CMA results, with lowest levels for uncertain results. Despite clinical guidelines recommending informed consent, many clinicians did not consider it pertinent to discuss the potential for CMA to reveal information concerning biological parentage or predisposition to late-onset disease, in a hypothetical case. Many non-genetics professionals ordering CMA did not feel equipped to interpret the results for patients, and articulated needs for education and access to genetics professionals. This exploratory study highlights key challenges in the practice of genomic medicine, and identifies needs for education, disseminated practice guidelines, and access to genetics professionals, especially when dealing with uncertain or unexpected findings. PMID:22989118

Chemosensory perception and medicinal plants for digestive ailments in a Mapuche community in NW Patagonia, Argentina.

PubMed

Molares, Soledad; Ladio, Ana

2009-06-25

To document the richness of plant species used in gastrointestinal disorders and to investigate about the criteria of aroma and flavor associated with its recognition, classification, selection and use. Ethnobotanical fieldwork consisted of interviews to 30 inhabitants living in a Mapuche community of Northwestern Patagonia; data collected was analyzed by means of non-parametric statistics. This work records 75 ethnospecies, pertaining to 40 botanic families. Lamiaceae, Asteraceae and Chenopodiaceae were the most frequently mentioned and described in terms of smell and taste. Most of species (69%) have notable aroma and/or flavor characteristics. The species presenting highest consensus in the population are positively associated with a higher frequency of organoleptic descriptions. In addition, local people consider these perceptions to be potentially useful in the search for substitutes when species are scarce or disappear from a locality. It is possible to establish a preliminary system of classification of medicinal plants based on their organoleptic characteristics and relate this to their effects on health. Moreover the cultural interpretation of smell and taste is of great heuristic importance to ethnopharmacology, in that it indicates which plants are most likely to contain the main active ingredients sought.

Voxel-based morphometric analysis in hypothyroidism using diffeomorphic anatomic registration via an exponentiated lie algebra algorithm approach.

PubMed

Singh, S; Modi, S; Bagga, D; Kaur, P; Shankar, L R; Khushu, S

2013-03-01

The present study aimed to investigate whether brain morphological differences exist between adult hypothyroid subjects and age-matched controls using voxel-based morphometry (VBM) with diffeomorphic anatomic registration via an exponentiated lie algebra algorithm (DARTEL) approach. High-resolution structural magnetic resonance images were taken in ten healthy controls and ten hypothyroid subjects. The analysis was conducted using statistical parametric mapping. The VBM study revealed a reduction in grey matter volume in the left postcentral gyrus and cerebellum of hypothyroid subjects compared to controls. A significant reduction in white matter volume was also found in the cerebellum, right inferior and middle frontal gyrus, right precentral gyrus, right inferior occipital gyrus and right temporal gyrus of hypothyroid patients compared to healthy controls. Moreover, no meaningful cluster for greater grey or white matter volume was obtained in hypothyroid subjects compared to controls. Our study is the first VBM study of hypothyroidism in an adult population and suggests that, compared to controls, this disorder is associated with differences in brain morphology in areas corresponding to known functional deficits in attention, language, motor speed, visuospatial processing and memory in hypothyroidism. © 2012 British Society for Neuroendocrinology.

Exploring risk factors for stuttering development in Parkinson disease after deep brain stimulation.

PubMed

Picillo, Marina; Vincos, Gustavo B; Sammartino, Francesco; Lozano, Andres M; Fasano, Alfonso

2017-05-01

Stuttering is a speech disorder with disruption of verbal fluency, occasionally present in Parkinson's disease (PD). PD co-incident stuttering may either worsen or improve after Deep Brain Stimulation (DBS). Sixteen out of 453 PD patients (3.5%) exhibited stuttering after DBS (PD-S) and were compared with a group of patients without stuttering (PD-NS) using non-parametric statistics. After DBS, stuttering worsened in 3 out of 4 patients with co-incidental stuttering. Most PD-S underwent subthalamic (STN) DBS, but 4 were implanted in the globus pallidus (GPi). Nine out of 16 PD-S (56.3%) reported a positive familial history for stuttering compared to none of the PD-NS. PD-S were mainly male (81.3%) with slight worse motor features compared to PD-NS. Herein, we describe a group of PD patients developing stuttering after DBS and report the presence of a positive familial history for stuttering as the most relevant risk factor, suggesting a possible underlying genetic cause. The fact that stuttering occurred after either STN or GPi DBS is an argument against the impact of medication reduction on stuttering. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linkage analysis of alternative anxiety phenotypes in multiply affected panic disorder families

PubMed Central

Fyer, Abby J.; Costa, Ramiro; Haghighi, Fatemeh; Logue, Mark W.; Knowles, James A.; Weissman, Myrna M.; Hodge, Susan E.; Hamilton, Steven P.

2013-01-01

Background The choice of phenotype definitions for genetic studies of panic and phobic disorders is complicated by family, twin and neurobiological data indicating both distinct and shared risk factors as well as heterogeneity within categories. We previously reported a genome scan in 120 multiplex panic disorder (PD) families using a phenotype that closely adhered to the DSM IV PD definition. Here we extend this work by conducting exploratory linkage analyses in this same pedigree set using ten additional literature- based panic and phobia-related phenotypes that take into account aspects of these hypothesized complexities. Methods Multiply affected families (> 2 individuals with PD) were recruited from clinical and non-clinical sources, evaluated by clinician administered semi-structured interview and subsequent blind consensus best estimate procedure. Each phenotype was analyzed under dominant and recessive models using parametric 2-point (homogeneity and heterogeneity), multipoint, and non-parametric methods. Empirically based permutations were used to estimate model specific and global (across all phenotypes) p-values. Results The highest score was a 2-point lod (4.27, global p < 0.08) on chromosome 13 (D13S793, 76cM) for the phenotype “specific or social phobia” under a recessive model and conditions of homogeneity. There was minimal support for linkage to any of the remaining nine phenotypes. Conclusions Though interpretation of findings is limited by sample size and the large number of phenotypes and models analyzed these data suggest a region on chromosome 13 as a potential site for further exploration in relation to risk for specific and social phobias. PMID:22525237

Anomalous spin-dependent tunneling statistics in Fe/MgO/Fe junctions induced by disorder at the interface

NASA Astrophysics Data System (ADS)

Yan, Jiawei; Wang, Shizhuo; Xia, Ke; Ke, Youqi

2018-01-01

We present first-principles analysis of interfacial disorder effects on spin-dependent tunneling statistics in thin Fe/MgO/Fe magnetic tunnel junctions. We find that interfacial disorder scattering can significantly modulate the tunneling statistics in the minority spin of the parallel configuration (PC) while all other spin channels remain dominated by the Poissonian process. For the minority-spin channel of PC, interfacial disorder scattering favors the formation of resonant tunneling channels by lifting the limitation of symmetry conservation at low concentration, presenting an important sub-Poissonian process in PC, but is destructive to the open channels at high concentration. We find that the important modulation of tunneling statistics is independent of the type of interfacial disorder. A bimodal distribution function of transmission with disorder dependence is introduced and fits very well our first-principles results. The increase of MgO thickness can quickly change the tunneling from a sub-Poissonian to Poissonian dominated process in the minority spin of PC with disorder. Our results provide a sensitive detection method of an ultralow concentration of interfacial defects.

Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Bloch, B. Nicholas; Chappelow, Jonathan; Patel, Pratik; Rofsky, Neil; Lenkinski, Robert; Genega, Elizabeth; Madabhushi, Anant

2011-03-01

Currently, there is significant interest in developing methods for quantitative integration of multi-parametric (structural, functional) imaging data with the objective of building automated meta-classifiers to improve disease detection, diagnosis, and prognosis. Such techniques are required to address the differences in dimensionalities and scales of individual protocols, while deriving an integrated multi-parametric data representation which best captures all disease-pertinent information available. In this paper, we present a scheme called Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE); a powerful, generalizable framework applicable to a variety of domains for multi-parametric data representation and fusion. Our scheme utilizes an ensemble of embeddings (via dimensionality reduction, DR); thereby exploiting the variance amongst multiple uncorrelated embeddings in a manner similar to ensemble classifier schemes (e.g. Bagging, Boosting). We apply this framework to the problem of prostate cancer (CaP) detection on 12 3 Tesla pre-operative in vivo multi-parametric (T2-weighted, Dynamic Contrast Enhanced, and Diffusion-weighted) magnetic resonance imaging (MRI) studies, in turn comprising a total of 39 2D planar MR images. We first align the different imaging protocols via automated image registration, followed by quantification of image attributes from individual protocols. Multiple embeddings are generated from the resultant high-dimensional feature space which are then combined intelligently to yield a single stable solution. Our scheme is employed in conjunction with graph embedding (for DR) and probabilistic boosting trees (PBTs) to detect CaP on multi-parametric MRI. Finally, a probabilistic pairwise Markov Random Field algorithm is used to apply spatial constraints to the result of the PBT classifier, yielding a per-voxel classification of CaP presence. Per-voxel evaluation of detection results against ground truth for CaP extent on MRI (obtained by spatially registering pre-operative MRI with available whole-mount histological specimens) reveals that EMPrAvISE yields a statistically significant improvement (AUC=0.77) over classifiers constructed from individual protocols (AUC=0.62, 0.62, 0.65, for T2w, DCE, DWI respectively) as well as one trained using multi-parametric feature concatenation (AUC=0.67).

Direct fluorescence characterisation of a picosecond seeded optical parametric amplifier

NASA Astrophysics Data System (ADS)

Stuart, N. H.; Bigourd, D.; Hill, R. W.; Robinson, T. S.; Mecseki, K.; Patankar, S.; New, G. H. C.; Smith, R. A.

2015-02-01

The temporal intensity contrast of high-power lasers based on optical parametric amplification (OPA) can be limited by parametric fluorescence from the non-linear gain stages. Here we present a spectroscopic method for direct measurement of unwanted parametric fluorescence widely applicable from unseeded to fully seeded and saturated OPA operation. Our technique employs simultaneous spectroscopy of fluorescence photons slightly outside the seed bandwidth and strongly attenuated light at the seed central wavelength. To demonstrate its applicability we have characterised the performance of a two-stage picosecond OPA pre-amplifier with 2.8×105 gain, delivering 335 μJ pulses at 1054 nm. We show that fluorescence from a strongly seeded OPA is reduced by ~500× from the undepleted to full pump depletion regimes. We also determine the vacuum fluctuation driven noise term seeding this OPA fluorescence to be 0.7±0.4 photons ps-1 nm-1 bandwidth. The resulting shot-to-shot statistics highlights a 1.5% probability of a five-fold and 0.3% probability of a ten-fold increase of fluorescence above the average value. Finally, we show that OPA fluorescence can be limited to a few-ps pedestal with 3×10-9 temporal intensity contrast 1.3 ps ahead of an intense laser pulse, a level highly attractive for large scale chirped-pulse OPA laser systems.

Radioactivity Registered With a Small Number of Events

NASA Astrophysics Data System (ADS)

Zlokazov, Victor; Utyonkov, Vladimir

2018-02-01

The synthesis of superheavy elements asks for the analysis of low statistics experimental data presumably obeying an unknown exponential distribution and to take the decision whether they originate from one source or have admixtures. Here we analyze predictions following from non-parametrical methods, employing only such fundamental sample properties as the sample mean, the median and the mode.

Robustness of S1 statistic with Hodges-Lehmann for skewed distributions

NASA Astrophysics Data System (ADS)

Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping

2016-10-01

Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.

Quantifying discrimination of Framingham risk functions with different survival C statistics.

PubMed

Pencina, Michael J; D'Agostino, Ralph B; Song, Linye

2012-07-10

Cardiovascular risk prediction functions offer an important diagnostic tool for clinicians and patients themselves. They are usually constructed with the use of parametric or semi-parametric survival regression models. It is essential to be able to evaluate the performance of these models, preferably with summaries that offer natural and intuitive interpretations. The concept of discrimination, popular in the logistic regression context, has been extended to survival analysis. However, the extension is not unique. In this paper, we define discrimination in survival analysis as the model's ability to separate those with longer event-free survival from those with shorter event-free survival within some time horizon of interest. This definition remains consistent with that used in logistic regression, in the sense that it assesses how well the model-based predictions match the observed data. Practical and conceptual examples and numerical simulations are employed to examine four C statistics proposed in the literature to evaluate the performance of survival models. We observe that they differ in the numerical values and aspects of discrimination that they capture. We conclude that the index proposed by Harrell is the most appropriate to capture discrimination described by the above definition. We suggest researchers report which C statistic they are using, provide a rationale for their selection, and be aware that comparing different indices across studies may not be meaningful. Copyright © 2012 John Wiley & Sons, Ltd.

Evaluating Cellular Polyfunctionality with a Novel Polyfunctionality Index

PubMed Central

Larsen, Martin; Sauce, Delphine; Arnaud, Laurent; Fastenackels, Solène; Appay, Victor; Gorochov, Guy

2012-01-01

Functional evaluation of naturally occurring or vaccination-induced T cell responses in mice, men and monkeys has in recent years advanced from single-parameter (e.g. IFN-γ-secretion) to much more complex multidimensional measurements. Co-secretion of multiple functional molecules (such as cytokines and chemokines) at the single-cell level is now measurable due primarily to major advances in multiparametric flow cytometry. The very extensive and complex datasets generated by this technology raise the demand for proper analytical tools that enable the analysis of combinatorial functional properties of T cells, hence polyfunctionality. Presently, multidimensional functional measures are analysed either by evaluating all combinations of parameters individually or by summing frequencies of combinations that include the same number of simultaneous functions. Often these evaluations are visualized as pie charts. Whereas pie charts effectively represent and compare average polyfunctionality profiles of particular T cell subsets or patient groups, they do not document the degree or variation of polyfunctionality within a group nor does it allow more sophisticated statistical analysis. Here we propose a novel polyfunctionality index that numerically evaluates the degree and variation of polyfuntionality, and enable comparative and correlative parametric and non-parametric statistical tests. Moreover, it allows the usage of more advanced statistical approaches, such as cluster analysis. We believe that the polyfunctionality index will render polyfunctionality an appropriate end-point measure in future studies of T cell responsiveness. PMID:22860124

Cure of cancer for seven cancer sites in the Flemish Region.

PubMed

Silversmit, Geert; Jegou, David; Vaes, Evelien; Van Hoof, Elke; Goetghebeur, Els; Van Eycken, Liesbet

2017-03-01

Cumulative relative survival curves for many cancers reach a plateau several years after diagnosis, indicating that the cancer survivor group has reached "statistical" cure. Parametric mixture cure model analysis on grouped relative survival curves provide an interesting way to determine the proportion of statistically cured cases and the mean survival time of the fatal cases in particular for population-based cancer registries. Based on the relative survival data from the Belgian Cancer Registry, parametric cure models were applied to seven cancer sites (cervix, colon, corpus uteri, skin melanoma, pancreas, stomach and oesophagus), at the Flemish Regional level for the incidence period 1999-2011. Statistical cure was observed for the examined cancer sites except for oesophageal cancer. The estimated cured proportion ranged from 5.9% [5.7, 6.1] for pancreatic cancer to 80.8% [80.5, 81.2] for skin melanoma. Cure results were further stratified by gender or age group. Stratified cured proportions were higher for females compared to males in colon cancer, stomach cancer, pancreas cancer and skin melanoma, which can mainly be attributed to differences in stage and age distribution between both sexes. This study demonstrates the applicability of cure rate models for the selected cancer sites after 14 years of follow-up and presents the first population-based results on the cure of cancer in Belgium. © 2016 UICC.

Statistical parametric mapping of stimuli-evoked changes in quantitative blood flow using extended-focus optical coherence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo

2016-03-01

Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.

Estimating the expected value of partial perfect information in health economic evaluations using integrated nested Laplace approximation.

PubMed

Heath, Anna; Manolopoulou, Ioanna; Baio, Gianluca

2016-10-15

The Expected Value of Perfect Partial Information (EVPPI) is a decision-theoretic measure of the 'cost' of parametric uncertainty in decision making used principally in health economic decision making. Despite this decision-theoretic grounding, the uptake of EVPPI calculations in practice has been slow. This is in part due to the prohibitive computational time required to estimate the EVPPI via Monte Carlo simulations. However, recent developments have demonstrated that the EVPPI can be estimated by non-parametric regression methods, which have significantly decreased the computation time required to approximate the EVPPI. Under certain circumstances, high-dimensional Gaussian Process (GP) regression is suggested, but this can still be prohibitively expensive. Applying fast computation methods developed in spatial statistics using Integrated Nested Laplace Approximations (INLA) and projecting from a high-dimensional into a low-dimensional input space allows us to decrease the computation time for fitting these high-dimensional GP, often substantially. We demonstrate that the EVPPI calculated using our method for GP regression is in line with the standard GP regression method and that despite the apparent methodological complexity of this new method, R functions are available in the package BCEA to implement it simply and efficiently. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Probabilistic dietary exposure assessment taking into account variability in both amount and frequency of consumption.

PubMed

Slob, Wout

2006-07-01

Probabilistic dietary exposure assessments that are fully based on Monte Carlo sampling from the raw intake data may not be appropriate. This paper shows that the data should first be analysed by using a statistical model that is able to take the various dimensions of food consumption patterns into account. A (parametric) model is discussed that takes into account the interindividual variation in (daily) consumption frequencies, as well as in amounts consumed. Further, the model can be used to include covariates, such as age, sex, or other individual attributes. Some illustrative examples show how this model may be used to estimate the probability of exceeding an (acute or chronic) exposure limit. These results are compared with the results based on directly counting the fraction of observed intakes exceeding the limit value. This comparison shows that the latter method is not adequate, in particular for the acute exposure situation. A two-step approach for probabilistic (acute) exposure assessment is proposed: first analyse the consumption data by a (parametric) statistical model as discussed in this paper, and then use Monte Carlo techniques for combining the variation in concentrations with the variation in consumption (by sampling from the statistical model). This approach results in an estimate of the fraction of the population as a function of the fraction of days at which the exposure limit is exceeded by the individual.

Statistical analysis of the electric energy production from photovoltaic conversion using mobile and fixed constructions

NASA Astrophysics Data System (ADS)

Bugała, Artur; Bednarek, Karol; Kasprzyk, Leszek; Tomczewski, Andrzej

2017-10-01

The paper presents the most representative - from the three-year measurement time period - characteristics of daily and monthly electricity production from a photovoltaic conversion using modules installed in a fixed and 2-axis tracking construction. Results are presented for selected summer, autumn, spring and winter days. Analyzed measuring stand is located on the roof of the Faculty of Electrical Engineering Poznan University of Technology building. The basic parameters of the statistical analysis like mean value, standard deviation, skewness, kurtosis, median, range, or coefficient of variation were used. It was found that the asymmetry factor can be useful in the analysis of the daily electricity production from a photovoltaic conversion. In order to determine the repeatability of monthly electricity production, occurring between the summer, and summer and winter months, a non-parametric Mann-Whitney U test was used as a statistical solution. In order to analyze the repeatability of daily peak hours, describing the largest value of the hourly electricity production, a non-parametric Kruskal-Wallis test was applied as an extension of the Mann-Whitney U test. Based on the analysis of the electric energy distribution from a prepared monitoring system it was found that traditional forecasting methods of the electricity production from a photovoltaic conversion, like multiple regression models, should not be the preferred methods of the analysis.

The influence of vegetation height heterogeneity on forest and woodland bird species richness across the United States.

PubMed

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r(2) = ∼ 0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r(2) = ∼ 0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness.

The Influence of Vegetation Height Heterogeneity on Forest and Woodland Bird Species Richness across the United States

PubMed Central

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J.

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r2 = ∼0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r2 = ∼0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. PMID:25101782

The landscape of W± and Z bosons produced in pp collisions up to LHC energies

NASA Astrophysics Data System (ADS)

Basso, Eduardo; Bourrely, Claude; Pasechnik, Roman; Soffer, Jacques

2017-10-01

We consider a selection of recent experimental results on electroweak W± , Z gauge boson production in pp collisions at BNL RHIC and CERN LHC energies in comparison to prediction of perturbative QCD calculations based on different sets of NLO parton distribution functions including the statistical PDF model known from fits to the DIS data. We show that the current statistical PDF parametrization (fitted to the DIS data only) underestimates the LHC data on W± , Z gauge boson production cross sections at the NLO by about 20%. This suggests that there is a need to refit the parameters of the statistical PDF including the latest LHC data.

The Role and Importance of the D in PTSD

DTIC Science & Technology

2013-01-01

changes to the new edition of the Diagnos- tic and Statistical Manual of Mental Disorders (DSM). Among the decisions was one to retain the word...tion of the Diagnostic and Statistical Manual of Mental Disorders (DSM), senior U.S. Army leadership seized its chance to seek changes to the ...defined by criteria listed in the fifth edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders, the DSM

Should Social Workers Use "Diagnostic and Statistical Manual of Mental Disorders-5?"

ERIC Educational Resources Information Center

Frances, Allen; Jones, K. Dayle

2014-01-01

Up until now, social workers have depended on the "Diagnostic and Statistical Manual of Mental Disorders" ("DSM") as the primary diagnostic classification for mental disorders. However, the "DSM-5" revision includes scientifically unfounded, inadequately tested, and potentially dangerous diagnoses that may lead them…

Irradiation-hyperthermia in canine hemangiopericytomas: large-animal model for therapeutic response.

PubMed

Richardson, R C; Anderson, V L; Voorhees, W D; Blevins, W E; Inskeep, T K; Janas, W; Shupe, R E; Babbs, C F

1984-11-01

Results of irradiation-hyperthermia treatment in 11 dogs with naturally occurring hemangiopericytoma were reported. Similarities of canine and human hemangiopericytomas were described. Orthovoltage X-irradiation followed by microwave-induced hyperthermia resulted in a 91% objective response rate. A statistical procedure was given to evaluate quantitatively the clinical behavior of locally invasive, nonmetastatic tumors in dogs that were undergoing therapy for control of local disease. The procedure used a small sample size and demonstrated distribution of the data on a scaled response as well as transformation of the data through classical parametric and nonparametric statistical methods. These statistical methods set confidence limits on the population mean and placed tolerance limits on a population percentage. Application of the statistical methods to human and animal clinical trials was apparent.

LORETA imaging of P300 in schizophrenia with individual MRI and 128-channel EEG.

PubMed

Pae, Ji Soo; Kwon, Jun Soo; Youn, Tak; Park, Hae-Jeong; Kim, Myung Sun; Lee, Boreom; Park, Kwang Suk

2003-11-01

We investigated the characteristics of P300 generators in schizophrenics by using voxel-based statistical parametric mapping of current density images. P300 generators, produced by a rare target tone of 1500 Hz (15%) under a frequent nontarget tone of 1000 Hz (85%), were measured in 20 right-handed schizophrenics and 21 controls. Low-resolution electromagnetic tomography (LORETA), using a realistic head model of the boundary element method based on individual MRI, was applied to the 128-channel EEG. Three-dimensional current density images were reconstructed from the LORETA intensity maps that covered the whole cortical gray matter. Spatial normalization and intensity normalization of the smoothed current density images were used to reduce anatomical variance and subject-specific global activity and statistical parametric mapping (SPM) was applied for the statistical analysis. We found that the sources of P300 were consistently localized at the left superior parietal area in normal subjects, while those of schizophrenics were diversely distributed. Upon statistical comparison, schizophrenics, with globally reduced current densities, showed a significant P300 current density reduction in the left medial temporal area and in the left inferior parietal area, while both left prefrontal and right orbitofrontal areas were relatively activated. The left parietotemporal area was found to correlate negatively with Positive and Negative Syndrome Scale total scores of schizophrenic patients. In conclusion, the reduced and increased areas of current density in schizophrenic patients suggest that the medial temporal and frontal areas contribute to the pathophysiology of schizophrenia, the frontotemporal circuitry abnormality.

Short-term monitoring of benzene air concentration in an urban area: a preliminary study of application of Kruskal-Wallis non-parametric test to assess pollutant impact on global environment and indoor.

PubMed

Mura, Maria Chiara; De Felice, Marco; Morlino, Roberta; Fuselli, Sergio

2010-01-01

In step with the need to develop statistical procedures to manage small-size environmental samples, in this work we have used concentration values of benzene (C6H6), concurrently detected by seven outdoor and indoor monitoring stations over 12 000 minutes, in order to assess the representativeness of collected data and the impact of the pollutant on indoor environment. Clearly, the former issue is strictly connected to sampling-site geometry, which proves critical to correctly retrieving information from analysis of pollutants of sanitary interest. Therefore, according to current criteria for network-planning, single stations have been interpreted as nodes of a set of adjoining triangles; then, a) node pairs have been taken into account in order to estimate pollutant stationarity on triangle sides, as well as b) node triplets, to statistically associate data from air-monitoring with the corresponding territory area, and c) node sextuplets, to assess the impact probability of the outdoor pollutant on indoor environment for each area. Distributions from the various node combinations are all non-Gaussian, in the consequently, Kruskal-Wallis (KW) non-parametric statistics has been exploited to test variability on continuous density function from each pair, triplet and sextuplet. Results from the above-mentioned statistical analysis have shown randomness of site selection, which has not allowed a reliable generalization of monitoring data to the entire selected territory, except for a single "forced" case (70%); most important, they suggest a possible procedure to optimize network design.

Psychometric properties of the Generalized Anxiety Disorder Inventory in a Canadian sample.

PubMed

Henderson, Leigh C; Antony, Martin M; Koerner, Naomi

2014-05-01

The Generalized Anxiety Disorder Inventory is a recently developed self-report measure that assesses symptoms of generalized anxiety disorder. Its psychometric properties have not been investigated further since its original development. The current study investigated its psychometric properties in a Canadian student/community sample. Exploratory principal component analysis replicated the original three-component structure. The total scale and subscales demonstrated excellent internal consistency reliability (α = 0.84-0.94) and correlated strongly with the Penn State Worry Questionnaire (r = 0.41-0.74, all ps <0.001) and Generalized Anxiety Disorder-7 (r = 0.55-0.84, all ps <0.001). However, only the total scale and cognitive subscale (r = 0.48-0.49, all ps <0.05) significantly predicted generalized anxiety disorder diagnosis established by diagnostic interview. The somatic subscale in particular may require revision to improve predictive validity. Revision may also be necessary given changes in required somatic symptoms for generalized anxiety disorder diagnostic criteria in more recent versions of the Diagnostic and Statistical Manual of Mental Disorders (i.e. although major changes occurred from Diagnostic and Statistical Manual of Mental Disorders-III-R to Diagnostic and Statistical Manual of Mental Disorders-IV, changes in Diagnostic and Statistical Manual of Mental Disorders-5 were minimal) and the possibility of changes in the upcoming 11th revision of the International Classification of Diseases.

75 FR 51335 - Revised Medical Criteria for Evaluating Mental Disorders

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-19

... Statistical Manual of Mental Disorders (DSM).\\3\\ We have also gained considerable adjudicative experience in... ``mild'' range in the current edition of the DSM, the Diagnostic and Statistical Manual of Mental... sometimes four, parts.\\10\\ The first part of every mental disorder listing is a brief introductory paragraph...

Statistical properties of light from optical parametric oscillators

NASA Astrophysics Data System (ADS)

Vyas, Reeta; Singh, Surendra

2009-12-01

Coherence properties of light beams generated by optical parametric oscillators (OPOs) are discussed in the region of threshold. Analytic expressions, that are valid throughout the threshold region, for experimentally measurable quantities such as the mean and variance of photon number fluctuations, squeezing of field quadratures, and photon counting distributions are derived. These expressions describe non-Gaussian fluctuations of light in the region of threshold and reproduce Gaussian fluctuations below and above threshold, thus providing a bridge between below and above threshold regimes of operation. They are used to study the transformation of fluctuation properties of light as the OPOs make a transition from below to above threshold. The results for the OPOs are compared to those for the single-mode and two-mode lasers and their similarities and differences are discussed.

A Maximum Entropy Method for Particle Filtering

NASA Astrophysics Data System (ADS)

Eyink, Gregory L.; Kim, Sangil

2006-06-01

Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.

Witnessing entanglement without entanglement witness operators.

PubMed

Pezzè, Luca; Li, Yan; Li, Weidong; Smerzi, Augusto

2016-10-11

Quantum mechanics predicts the existence of correlations between composite systems that, although puzzling to our physical intuition, enable technologies not accessible in a classical world. Notwithstanding, there is still no efficient general method to theoretically quantify and experimentally detect entanglement of many qubits. Here we propose to detect entanglement by measuring the statistical response of a quantum system to an arbitrary nonlocal parametric evolution. We witness entanglement without relying on the tomographic reconstruction of the quantum state, or the realization of witness operators. The protocol requires two collective settings for any number of parties and is robust against noise and decoherence occurring after the implementation of the parametric transformation. To illustrate its user friendliness we demonstrate multipartite entanglement in different experiments with ions and photons by analyzing published data on fidelity visibilities and variances of collective observables.

Estimation and confidence intervals for empirical mixing distributions

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1995-01-01

Questions regarding collections of parameter estimates can frequently be expressed in terms of an empirical mixing distribution (EMD). This report discusses empirical Bayes estimation of an EMD, with emphasis on the construction of interval estimates. Estimation of the EMD is accomplished by substitution of estimates of prior parameters in the posterior mean of the EMD. This procedure is examined in a parametric model (the normal-normal mixture) and in a semi-parametric model. In both cases, the empirical Bayes bootstrap of Laird and Louis (1987, Journal of the American Statistical Association 82, 739-757) is used to assess the variability of the estimated EMD arising from the estimation of prior parameters. The proposed methods are applied to a meta-analysis of population trend estimates for groups of birds.

Altered functional connectivity of the subthalamus and the bed nucleus of the stria terminalis in obsessive-compulsive disorder.

PubMed

Cano, M; Alonso, P; Martínez-Zalacaín, I; Subirà, M; Real, E; Segalàs, C; Pujol, J; Cardoner, N; Menchón, J M; Soriano-Mas, C

2018-04-01

The assessment of inter-regional functional connectivity (FC) has allowed for the description of the putative mechanism of action of treatments such as deep brain stimulation (DBS) of the nucleus accumbens in patients with obsessive-compulsive disorder (OCD). Nevertheless, the possible FC alterations of other clinically-effective DBS targets have not been explored. Here we evaluated the FC patterns of the subthalamic nucleus (STN) and the bed nucleus of the stria terminalis (BNST) in patients with OCD, as well as their association with symptom severity. Eighty-six patients with OCD and 104 healthy participants were recruited. A resting-state image was acquired for each participant and a seed-based analysis focused on our two regions of interest was performed using statistical parametric mapping software (SPM8). Between-group differences in FC patterns were assessed with two-sample t test models, while the association between symptom severity and FC patterns was assessed with multiple regression analyses. In comparison with controls, patients with OCD showed: (1) increased FC between the left STN and the right pre-motor cortex, (2) decreased FC between the right STN and the lenticular nuclei, and (3) increased FC between the left BNST and the right frontopolar cortex. Multiple regression analyses revealed a negative association between clinical severity and FC between the right STN and lenticular nucleus. This study provides a neurobiological framework to understand the mechanism of action of DBS on the STN and the BNST, which seems to involve brain circuits related with motor response inhibition and anxiety control, respectively.

Abnormal resting-state brain activities in patients with first-episode obsessive-compulsive disorder

PubMed Central

Niu, Qihui; Yang, Lei; Song, Xueqin; Chu, Congying; Liu, Hao; Zhang, Lifang; Li, Yan; Zhang, Xiang; Cheng, Jingliang; Li, Youhui

2017-01-01

Objective This paper attempts to explore the brain activity of patients with obsessive-compulsive disorder (OCD) and its correlation with the disease at resting duration in patients with first-episode OCD, providing a forceful imaging basis for clinic diagnosis and pathogenesis of OCD. Methods Twenty-six patients with first-episode OCD and 25 healthy controls (HC group; matched for age, sex, and education level) underwent functional magnetic resonance imaging (fMRI) scanning at resting state. Statistical parametric mapping 8, data processing assistant for resting-state fMRI analysis toolkit, and resting state fMRI data analysis toolkit packages were used to process the fMRI data on Matlab 2012a platform, and the difference of regional homogeneity (ReHo) values between the OCD group and HC group was detected with independent two-sample t-test. With age as a concomitant variable, the Pearson correlation analysis was adopted to study the correlation between the disease duration and ReHo value of whole brain. Results Compared with HC group, the ReHo values in OCD group were decreased in brain regions, including left thalamus, right thalamus, right paracentral lobule, right postcentral gyrus, and the ReHo value was increased in the left angular gyrus region. There was a negative correlation between disease duration and ReHo value in the bilateral orbitofrontal cortex (OFC). Conclusion OCD is a multifactorial disease generally caused by abnormal activities of many brain regions at resting state. Worse brain activity of the OFC is related to the OCD duration, which provides a new insight to the pathogenesis of OCD. PMID:28243104

Premenstrual dysphoric disorder in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition: contributions from Asia.

PubMed

Mehta, N; Mehta, S

2014-12-01

Premenstrual dysphoric disorder has been included as a separate diagnostic entity in the chapter of 'Depressive Disorders' of the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5). The antecedent, concurrent, and predictive diagnostic validators of premenstrual dysphoric disorder have been reviewed by a sub-workgroup of the DSM-5 Mood Disorders Work Group, which includes a panel of experts on women's mental health. Contributions from the Asian continent have been mainly in the form of prevalence studies. Genetic and neurobiological domains of premenstrual dysphoric disorder largely remain untouched in Asia and offer a potential area for investigation.

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

PubMed

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

A global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method.

PubMed

Zou, Kelly H; Resnic, Frederic S; Talos, Ion-Florin; Goldberg-Zimring, Daniel; Bhagwat, Jui G; Haker, Steven J; Kikinis, Ron; Jolesz, Ferenc A; Ohno-Machado, Lucila

2005-10-01

Medical classification accuracy studies often yield continuous data based on predictive models for treatment outcomes. A popular method for evaluating the performance of diagnostic tests is the receiver operating characteristic (ROC) curve analysis. The main objective was to develop a global statistical hypothesis test for assessing the goodness-of-fit (GOF) for parametric ROC curves via the bootstrap. A simple log (or logit) and a more flexible Box-Cox normality transformations were applied to untransformed or transformed data from two clinical studies to predict complications following percutaneous coronary interventions (PCIs) and for image-guided neurosurgical resection results predicted by tumor volume, respectively. We compared a non-parametric with a parametric binormal estimate of the underlying ROC curve. To construct such a GOF test, we used the non-parametric and parametric areas under the curve (AUCs) as the metrics, with a resulting p value reported. In the interventional cardiology example, logit and Box-Cox transformations of the predictive probabilities led to satisfactory AUCs (AUC=0.888; p=0.78, and AUC=0.888; p=0.73, respectively), while in the brain tumor resection example, log and Box-Cox transformations of the tumor size also led to satisfactory AUCs (AUC=0.898; p=0.61, and AUC=0.899; p=0.42, respectively). In contrast, significant departures from GOF were observed without applying any transformation prior to assuming a binormal model (AUC=0.766; p=0.004, and AUC=0.831; p=0.03), respectively. In both studies the p values suggested that transformations were important to consider before applying any binormal model to estimate the AUC. Our analyses also demonstrated and confirmed the predictive values of different classifiers for determining the interventional complications following PCIs and resection outcomes in image-guided neurosurgery.

A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice.

PubMed

Jacquin, Laval; Cao, Tuong-Vi; Ahmadi, Nourollah

2016-01-01

One objective of this study was to provide readers with a clear and unified understanding of parametric statistical and kernel methods, used for genomic prediction, and to compare some of these in the context of rice breeding for quantitative traits. Furthermore, another objective was to provide a simple and user-friendly R package, named KRMM, which allows users to perform RKHS regression with several kernels. After introducing the concept of regularized empirical risk minimization, the connections between well-known parametric and kernel methods such as Ridge regression [i.e., genomic best linear unbiased predictor (GBLUP)] and reproducing kernel Hilbert space (RKHS) regression were reviewed. Ridge regression was then reformulated so as to show and emphasize the advantage of the kernel "trick" concept, exploited by kernel methods in the context of epistatic genetic architectures, over parametric frameworks used by conventional methods. Some parametric and kernel methods; least absolute shrinkage and selection operator (LASSO), GBLUP, support vector machine regression (SVR) and RKHS regression were thereupon compared for their genomic predictive ability in the context of rice breeding using three real data sets. Among the compared methods, RKHS regression and SVR were often the most accurate methods for prediction followed by GBLUP and LASSO. An R function which allows users to perform RR-BLUP of marker effects, GBLUP and RKHS regression, with a Gaussian, Laplacian, polynomial or ANOVA kernel, in a reasonable computation time has been developed. Moreover, a modified version of this function, which allows users to tune kernels for RKHS regression, has also been developed and parallelized for HPC Linux clusters. The corresponding KRMM package and all scripts have been made publicly available.

Mental Illness Statistics

MedlinePlus

... Top ı cs Mental Illness Any Anxiety Disorder Attention-Deficit/Hyperactivity Disorder (ADHD) Autism Spectrum Disorder (ASD) Bipolar ... Anorexia Nervosa Any Anxiety Disorder Any Mood Disorder Attention-Deficit/Hyperactivity Disorder (ADHD) Autism Spectrum Disorder (ASD) Binge ...

A Robust Adaptive Autonomous Approach to Optimal Experimental Design

NASA Astrophysics Data System (ADS)

Gu, Hairong

Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.

Estimating and comparing microbial diversity in the presence of sequencing errors

PubMed Central

Chiu, Chun-Huo

2016-01-01

Estimating and comparing microbial diversity are statistically challenging due to limited sampling and possible sequencing errors for low-frequency counts, producing spurious singletons. The inflated singleton count seriously affects statistical analysis and inferences about microbial diversity. Previous statistical approaches to tackle the sequencing errors generally require different parametric assumptions about the sampling model or about the functional form of frequency counts. Different parametric assumptions may lead to drastically different diversity estimates. We focus on nonparametric methods which are universally valid for all parametric assumptions and can be used to compare diversity across communities. We develop here a nonparametric estimator of the true singleton count to replace the spurious singleton count in all methods/approaches. Our estimator of the true singleton count is in terms of the frequency counts of doubletons, tripletons and quadrupletons, provided these three frequency counts are reliable. To quantify microbial alpha diversity for an individual community, we adopt the measure of Hill numbers (effective number of taxa) under a nonparametric framework. Hill numbers, parameterized by an order q that determines the measures’ emphasis on rare or common species, include taxa richness (q = 0), Shannon diversity (q = 1, the exponential of Shannon entropy), and Simpson diversity (q = 2, the inverse of Simpson index). A diversity profile which depicts the Hill number as a function of order q conveys all information contained in a taxa abundance distribution. Based on the estimated singleton count and the original non-singleton frequency counts, two statistical approaches (non-asymptotic and asymptotic) are developed to compare microbial diversity for multiple communities. (1) A non-asymptotic approach refers to the comparison of estimated diversities of standardized samples with a common finite sample size or sample completeness. This approach aims to compare diversity estimates for equally-large or equally-complete samples; it is based on the seamless rarefaction and extrapolation sampling curves of Hill numbers, specifically for q = 0, 1 and 2. (2) An asymptotic approach refers to the comparison of the estimated asymptotic diversity profiles. That is, this approach compares the estimated profiles for complete samples or samples whose size tends to be sufficiently large. It is based on statistical estimation of the true Hill number of any order q ≥ 0. In the two approaches, replacing the spurious singleton count by our estimated count, we can greatly remove the positive biases associated with diversity estimates due to spurious singletons and also make fair comparisons across microbial communities, as illustrated in our simulation results and in applying our method to analyze sequencing data from viral metagenomes. PMID:26855872

Brief Report: An Exploratory Study Comparing Diagnostic Outcomes for Autism Spectrum Disorders under DSM-IV-TR with the Proposed DSM-5 Revision

ERIC Educational Resources Information Center

Gibbs, Vicki; Aldridge, Fiona; Chandler, Felicity; Witzlsperger, Ellen; Smith, Karen

2012-01-01

The proposed revision for Autism spectrum disorders (ASDs) in the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) represents a shift from the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition, Text Revision (DSM-IV-TR). As the proposed DSM-5 criteria require a higher minimum number of symptoms to be…

Modeling of spacecraft charging

NASA Technical Reports Server (NTRS)

Whipple, E. C., Jr.

1977-01-01

Three types of modeling of spacecraft charging are discussed: statistical models, parametric models, and physical models. Local time dependence of circuit upset for DoD and communication satellites, and electron current to a sphere with an assumed Debye potential distribution are presented. Four regions were involved in spacecraft charging: (1) undisturbed plasma, (2) plasma sheath region, (3) spacecraft surface, and (4) spacecraft equivalent circuit.

The Dundee Ready Education Environment Measure (DREEM): a review of its adoption and use.

PubMed

Miles, Susan; Swift, Louise; Leinster, Sam J

2012-01-01

The Dundee Ready Education Environment Measure (DREEM) was published in 1997 as a tool to evaluate educational environments of medical schools and other health training settings and a recent review concluded that it was the most suitable such instrument. This study aimed to review the settings and purposes to which the DREEM has been applied and the approaches used to analyse and report it, with a view to guiding future users towards appropriate methodology. A systematic literature review was conducted using the Web of Knowledge databases of all articles reporting DREEM data between 1997 and 4 January 2011. The review found 40 publications, using data from 20 countries. DREEM is used in evaluation for diagnostic purposes, comparison between different groups and comparison with ideal/expected scores. A variety of non-parametric and parametric statistical methods have been applied, but their use is inconsistent. DREEM has been used internationally for different purposes and is regarded as a useful tool by users. However, reporting and analysis differs between publications. This lack of uniformity makes comparison between institutions difficult. Most users of DREEM are not statisticians and there is a need for informed guidelines on its reporting and statistical analysis.

Analysis of Parasite and Other Skewed Counts

PubMed Central

Alexander, Neal

2012-01-01

Objective To review methods for the statistical analysis of parasite and other skewed count data. Methods Statistical methods for skewed count data are described and compared, with reference to those used over a ten year period of Tropical Medicine and International Health. Two parasitological datasets are used for illustration. Results Ninety papers were identified, 89 with descriptive and 60 with inferential analysis. A lack of clarity is noted in identifying measures of location, in particular the Williams and geometric mean. The different measures are compared, emphasizing the legitimacy of the arithmetic mean for skewed data. In the published papers, the t test and related methods were often used on untransformed data, which is likely to be invalid. Several approaches to inferential analysis are described, emphasizing 1) non-parametric methods, while noting that they are not simply comparisons of medians, and 2) generalized linear modelling, in particular with the negative binomial distribution. Additional methods, such as the bootstrap, with potential for greater use are described. Conclusions Clarity is recommended when describing transformations and measures of location. It is suggested that non-parametric methods and generalized linear models are likely to be sufficient for most analyses. PMID:22943299

Detecting trend on ecological river status - how to deal with short incomplete bioindicator time series? Methodological and operational issues

NASA Astrophysics Data System (ADS)

Cernesson, Flavie; Tournoud, Marie-George; Lalande, Nathalie

2018-06-01

Among the various parameters monitored in river monitoring networks, bioindicators provide very informative data. Analysing time variations in bioindicator data is tricky for water managers because the data sets are often short, irregular, and non-normally distributed. It is then a challenging methodological issue for scientists, as it is in Saône basin (30 000 km2, France) where, between 1998 and 2010, among 812 IBGN (French macroinvertebrate bioindicator) monitoring stations, only 71 time series have got more than 10 data values and were studied here. Combining various analytical tools (three parametric and non-parametric statistical tests plus a graphical analysis), 45 IBGN time series were classified as stationary and 26 as non-stationary (only one of which showing a degradation). Series from sampling stations located within the same hydroecoregion showed similar trends, while river size classes seemed to be non-significant to explain temporal trends. So, from a methodological point of view, combining statistical tests and graphical analysis is a relevant option when striving to improve trend detection. Moreover, it was possible to propose a way to summarise series in order to analyse links between ecological river quality indicators and land use stressors.

Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor

NASA Astrophysics Data System (ADS)

Taverniers, Søren; Tartakovsky, Daniel M.

2017-11-01

Predictions of the total energy deposited into a brain tumor through X-ray irradiation are notoriously error-prone. We investigate how this predictive uncertainty is affected by uncertainty in both the location of the region occupied by a dose-enhancing iodinated contrast agent and the agent's concentration. This is done within the probabilistic framework in which these uncertain parameters are modeled as random variables. We employ the stochastic collocation (SC) method to estimate statistical moments of the deposited energy in terms of statistical moments of the random inputs, and the global sensitivity analysis (GSA) to quantify the relative importance of uncertainty in these parameters on the overall predictive uncertainty. A nonlinear radiation-diffusion equation dramatically magnifies the coefficient of variation of the uncertain parameters, yielding a large coefficient of variation for the predicted energy deposition. This demonstrates that accurate prediction of the energy deposition requires a proper treatment of even small parametric uncertainty. Our analysis also reveals that SC outperforms standard Monte Carlo, but its relative efficiency decreases as the number of uncertain parameters increases from one to three. A robust GSA ameliorates this problem by reducing this number.

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

Trends and associated uncertainty in the global mean temperature record

NASA Astrophysics Data System (ADS)

Poppick, A. N.; Moyer, E. J.; Stein, M.

2016-12-01

Physical models suggest that the Earth's mean temperature warms in response to changing CO2 concentrations (and hence increased radiative forcing); given physical uncertainties in this relationship, the historical temperature record is a source of empirical information about global warming. A persistent thread in many analyses of the historical temperature record, however, is the reliance on methods that appear to deemphasize both physical and statistical assumptions. Examples include regression models that treat time rather than radiative forcing as the relevant covariate, and time series methods that account for natural variability in nonparametric rather than parametric ways. We show here that methods that deemphasize assumptions can limit the scope of analysis and can lead to misleading inferences, particularly in the setting considered where the data record is relatively short and the scale of temporal correlation is relatively long. A proposed model that is simple but physically informed provides a more reliable estimate of trends and allows a broader array of questions to be addressed. In accounting for uncertainty, we also illustrate how parametric statistical models that are attuned to the important characteristics of natural variability can be more reliable than ostensibly more flexible approaches.

Common and Unique Factors Associated with DSM-IV-TR Internalizing Disorders in Children

ERIC Educational Resources Information Center

Higa-McMillan, Charmaine K.; Smith, Rita L.; Chorpita, Bruce F.; Hayashi, Kentaro

2008-01-01

With the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association. "Diagnostic and statistical manual of mental disorders DSM-IV Fourth Edition-Text Revision". Author, Washington, DC. 2000) ahead, decisions will be made about the future of taxonomic conceptualizations. This study examined the…

An Exploratory Data Analysis System for Support in Medical Decision-Making

PubMed Central

Copeland, J. A.; Hamel, B.; Bourne, J. R.

1979-01-01

An experimental system was developed to allow retrieval and analysis of data collected during a study of neurobehavioral correlates of renal disease. After retrieving data organized in a relational data base, simple bivariate statistics of parametric and nonparametric nature could be conducted. An “exploratory” mode in which the system provided guidance in selection of appropriate statistical analyses was also available to the user. The system traversed a decision tree using the inherent qualities of the data (e.g., the identity and number of patients, tests, and time epochs) to search for the appropriate analyses to employ.

Computing Science and Statistics: Proceedings of the Symposium on the Interface: Computationally Intensive Methods in Statistics (20th) Held in Fairfax, Virginia on April 20-23, 1988

DTIC Science & Technology

1989-03-15

essence of the idea ycessible mtho forunrtandig eth- Tis tand thP ra) rm guh ide propet oaes nd d of e aessie meh bsd fooesadng asymptoti- isthe for s...network? This of Such empirical parametric model fitting is of course depends heavily on the class of net- course the essence of much of applied...smaller problems is the essence of graphical modeling. A model hy- attributes. Let e be the discrete joint outcome space for those N pergraph, g

An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models

NASA Astrophysics Data System (ADS)

Dukkipati, Ambedkar; Manathara, Joel George

In this paper we study representation of KL-divergence minimization, in the cases where integer sufficient statistics exists, using tools from polynomial algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. In particular, we also study the case of Kullback-Csisźar iteration scheme. We present implicit descriptions of these models and show that implicitization preserves specialization of prior distribution. This result leads us to a Gröbner bases method to compute an implicit representation of minimum KL-divergence models.

Analysis of censored data.

PubMed

Lucijanic, Marko; Petrovecki, Mladen

2012-01-01

Analyzing events over time is often complicated by incomplete, or censored, observations. Special non-parametric statistical methods were developed to overcome difficulties in summarizing and comparing censored data. Life-table (actuarial) method and Kaplan-Meier method are described with an explanation of survival curves. For the didactic purpose authors prepared a workbook based on most widely used Kaplan-Meier method. It should help the reader understand how Kaplan-Meier method is conceptualized and how it can be used to obtain statistics and survival curves needed to completely describe a sample of patients. Log-rank test and hazard ratio are also discussed.

Full statistical mode reconstruction of a light field via a photon-number-resolved measurement

NASA Astrophysics Data System (ADS)

Burenkov, I. A.; Sharma, A. K.; Gerrits, T.; Harder, G.; Bartley, T. J.; Silberhorn, C.; Goldschmidt, E. A.; Polyakov, S. V.

2017-05-01

We present a method to reconstruct the complete statistical mode structure and optical losses of multimode conjugated optical fields using an experimentally measured joint photon-number probability distribution. We demonstrate that this method evaluates classical and nonclassical properties using a single measurement technique and is well suited for quantum mesoscopic state characterization. We obtain a nearly perfect reconstruction of a field comprised of up to ten modes based on a minimal set of assumptions. To show the utility of this method, we use it to reconstruct the mode structure of an unknown bright parametric down-conversion source.

Linkage analysis of high myopia susceptibility locus in 26 families.

PubMed

Paget, Sandrine; Julia, Sophie; Vitezica, Zulma G; Soler, Vincent; Malecaze, François; Calvas, Patrick

2008-01-01

We conducted a linkage analysis in high myopia families to replicate suggestive results from chromosome 7q36 using a model of autosomal dominant inheritance and genetic heterogeneity. We also performed a genome-wide scan to identify novel loci. Twenty-six families, with at least two high-myopic subjects (ie. refractive value in the less affected eye of -5 diopters) in each family, were included. Phenotypic examination included standard autorefractometry, ultrasonographic eye length measurement, and clinical confirmation of the non-syndromic character of the refractive disorder. Nine families were collected de novo including 136 available members of whom 34 were highly myopic subjects. Twenty new subjects were added in 5 of the 17 remaining families. A total of 233 subjects were submitted to a genome scan using ABI linkage mapping set LMSv2-MD-10, additional markers in all regions where preliminary LOD scores were greater than 1.5 were used. Multipoint parametric and non-parametric analyses were conducted with the software packages Genehunter 2.0 and Merlin 1.0.1. Two autosomal recessive, two autosomal dominant, and four autosomal additive models were used in the parametric linkage analyses. No linkage was found using the subset of nine newly collected families. Study of the entire population of 26 families with a parametric model did not yield a significant LOD score (>3), even for the previously suggestive locus on 7q36. A non-parametric model demonstrated significant linkage to chromosome 7p15 in the entire population (Z-NPL=4.07, p=0.00002). The interval is 7.81 centiMorgans (cM) between markers D7S2458 and D7S2515. The significant interval reported here needs confirmation in other cohorts. Among possible susceptibility genes in the interval, certain candidates are likely to be involved in eye growth and development.

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Semiparametric time varying coefficient model for matched case-crossover studies.

PubMed

Ortega-Villa, Ana Maria; Kim, Inyoung; Kim, H

2017-03-15

In matched case-crossover studies, it is generally accepted that the covariates on which a case and associated controls are matched cannot exert a confounding effect on independent predictors included in the conditional logistic regression model. This is because any stratum effect is removed by the conditioning on the fixed number of sets of the case and controls in the stratum. Hence, the conditional logistic regression model is not able to detect any effects associated with the matching covariates by stratum. However, some matching covariates such as time often play an important role as an effect modification leading to incorrect statistical estimation and prediction. Therefore, we propose three approaches to evaluate effect modification by time. The first is a parametric approach, the second is a semiparametric penalized approach, and the third is a semiparametric Bayesian approach. Our parametric approach is a two-stage method, which uses conditional logistic regression in the first stage and then estimates polynomial regression in the second stage. Our semiparametric penalized and Bayesian approaches are one-stage approaches developed by using regression splines. Our semiparametric one stage approach allows us to not only detect the parametric relationship between the predictor and binary outcomes, but also evaluate nonparametric relationships between the predictor and time. We demonstrate the advantage of our semiparametric one-stage approaches using both a simulation study and an epidemiological example of a 1-4 bi-directional case-crossover study of childhood aseptic meningitis with drinking water turbidity. We also provide statistical inference for the semiparametric Bayesian approach using Bayes Factors. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Efficient statistically accurate algorithms for the Fokker-Planck equation in large dimensions

NASA Astrophysics Data System (ADS)

Chen, Nan; Majda, Andrew J.

2018-02-01

Solving the Fokker-Planck equation for high-dimensional complex turbulent dynamical systems is an important and practical issue. However, most traditional methods suffer from the curse of dimensionality and have difficulties in capturing the fat tailed highly intermittent probability density functions (PDFs) of complex systems in turbulence, neuroscience and excitable media. In this article, efficient statistically accurate algorithms are developed for solving both the transient and the equilibrium solutions of Fokker-Planck equations associated with high-dimensional nonlinear turbulent dynamical systems with conditional Gaussian structures. The algorithms involve a hybrid strategy that requires only a small number of ensembles. Here, a conditional Gaussian mixture in a high-dimensional subspace via an extremely efficient parametric method is combined with a judicious non-parametric Gaussian kernel density estimation in the remaining low-dimensional subspace. Particularly, the parametric method provides closed analytical formulae for determining the conditional Gaussian distributions in the high-dimensional subspace and is therefore computationally efficient and accurate. The full non-Gaussian PDF of the system is then given by a Gaussian mixture. Different from traditional particle methods, each conditional Gaussian distribution here covers a significant portion of the high-dimensional PDF. Therefore a small number of ensembles is sufficient to recover the full PDF, which overcomes the curse of dimensionality. Notably, the mixture distribution has significant skill in capturing the transient behavior with fat tails of the high-dimensional non-Gaussian PDFs, and this facilitates the algorithms in accurately describing the intermittency and extreme events in complex turbulent systems. It is shown in a stringent set of test problems that the method only requires an order of O (100) ensembles to successfully recover the highly non-Gaussian transient PDFs in up to 6 dimensions with only small errors.

Comparative study of some robust statistical methods: weighted, parametric, and nonparametric linear regression of HPLC convoluted peak responses using internal standard method in drug bioavailability studies.

PubMed

Korany, Mohamed A; Maher, Hadir M; Galal, Shereen M; Ragab, Marwa A A

2013-05-01

This manuscript discusses the application and the comparison between three statistical regression methods for handling data: parametric, nonparametric, and weighted regression (WR). These data were obtained from different chemometric methods applied to the high-performance liquid chromatography response data using the internal standard method. This was performed on a model drug Acyclovir which was analyzed in human plasma with the use of ganciclovir as internal standard. In vivo study was also performed. Derivative treatment of chromatographic response ratio data was followed by convolution of the resulting derivative curves using 8-points sin x i polynomials (discrete Fourier functions). This work studies and also compares the application of WR method and Theil's method, a nonparametric regression (NPR) method with the least squares parametric regression (LSPR) method, which is considered the de facto standard method used for regression. When the assumption of homoscedasticity is not met for analytical data, a simple and effective way to counteract the great influence of the high concentrations on the fitted regression line is to use WR method. WR was found to be superior to the method of LSPR as the former assumes that the y-direction error in the calibration curve will increase as x increases. Theil's NPR method was also found to be superior to the method of LSPR as the former assumes that errors could occur in both x- and y-directions and that might not be normally distributed. Most of the results showed a significant improvement in the precision and accuracy on applying WR and NPR methods relative to LSPR.

Multidimensional fatigue inventory and post-polio syndrome - a Rasch analysis.

PubMed

Dencker, Anna; Sunnerhagen, Katharina S; Taft, Charles; Lundgren-Nilsson, Åsa

2015-02-12

Fatigue is a common symptom in post-polio syndrome (PPS) and can have a substantial impact on patients. There is a need for validated questionnaires to assess fatigue in PPS for use in clinical practice and research. The aim with this study was to assess the validity and reliability of the Swedish version of Multidimensional Fatigue Inventory (MFI-20) in patients with PPS using the Rasch model. A total of 231 patients diagnosed with PPS completed the Swedish MFI-20 questionnaire at post-polio out-patient clinics in Sweden. The mean age of participants was 62 years and 61% were females. Data were tested against assumptions of the Rasch measurement model (i.e. unidimensionality of the scale, good item fit, independency of items and absence of differential item functioning). Reliability was tested with the person separation index (PSI). A transformation of the ordinal total scale scores into an interval scale for use in parametric analysis was performed. Dummy cases with minimum and maximum scoring were used for the transformation table to achieve interval scores between 20 and 100, which are comprehensive limits for the MFI-20 scale. An initial Rasch analysis of the full scale with 20 items showed misfit to the Rasch model (p < 0.001). Seven items showed slightly disordered thresholds and person estimates were not significantly improved by rescoring items. Analysis of MFI-20 scale with the 5 MFI-20 subscales as testlets showed good fit with a non-significant x (2) value (p = 0.089). PSI for the testlet solution was 0.86. Local dependency was present in all subscales and fit to the Rasch model was solved with testlets within each subscale. PSI ranged from 0.52 to 0.82 in the subscales. This study shows that the Swedish MFI-20 total scale and subscale scores yield valid and reliable measures of fatigue in persons with post-polio syndrome. The Rasch transformed total scores can be used for parametric statistical analyses in future clinical studies.

Behavioral measures and self-report of impulsivity in bipolar disorder: no association between Stroop test and Barratt Impulsiveness Scale.

PubMed

Strasser, Elisa Sophie; Haffner, Paula; Fiebig, Jana; Quinlivan, Esther; Adli, Mazda; Stamm, Thomas Josef

2016-12-01

Impulsivity as a tendency to act quickly without considering future consequences has been proposed as a dimensional factor in bipolar disorder. It can be measured using behavioral tasks and self-report questionnaires. Previous findings revealed patients to show worse performance on at least one behavioral measure of impulsivity. Additionally, self-reported impulsivity seems to be higher among bipolar patients, both parameters being possibly associated with a more severe course of illness. In this study, our primary aim was to investigate the relationship between these two constructs of impulsivity among bipolar patients. A total of 40 euthymic patients with bipolar disorder (21 female, 22 Bipolar I) and 30 healthy controls were recruited for comprehensive neuropsychological assessment. To assess inhibition control as a behavioral measure of impulsivity, the Stroop Color and Word Test (Stroop) was used. Additionally, both groups completed the Barratt Impulsiveness Scale (BIS) as a self-report of impulsivity. To compare the groups' performance on the Stroop and ratings on the BIS, the non-parametric Mann-Whitney U test was used. Within the bipolar group, we additionally examined the possibility of an association between Stroop performance and BIS total scores using Pearson's Correlation r. Patients and controls differed significantly on the Stroop and BIS, with patients performing worse on the Stroop and scoring higher on the BIS. However, there was no association between the Stroop and BIS within the bipolar group. As an exploratory analysis, a positive correlation between Stroop performance and number of episodes was found. Further, we detected a statistical trend in the direction of poorer Stroop performance among patients treated with polypharmacy. Both difficulties with behavioral inhibition and self-reported impulsivity were observed to be higher in bipolar patients than controls in the current study. However, within the patient group we did not observe an association between patients' behavioral performance and self-report. This indicates that the parameters likely constitute distinct, dimensional factors of bipolar disorder. In future research, studies with larger samples should investigate which of the two markers constitutes the better marker for the illness and is more suitable to differentiate the most severe patients.

Assessing the utility of diagnostic criteria: a multisite study on gender identity disorder.

PubMed

Paap, Muirne C S; Kreukels, Baudewijntje P C; Cohen-Kettenis, Peggy T; Richter-Appelt, Hertha; de Cuypere, Griet; Haraldsen, Ira R

2011-01-01

Studies involving patients with gender identity disorder (GID) are inconsistent with regard to outcomes and often difficult to compare because of the vague descriptions of the diagnostic process. A multisite study is needed to scrutinize the utility and generality of different aspects of the diagnostic criteria for GID. To investigate the way in which the diagnosis-specific Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision criteria for GID were used to reach a psychiatric diagnosis in four European countries: the Netherlands (Amsterdam), Norway (Oslo), Germany (Hamburg), and Belgium (Ghent). The main goal was to compare item (symptom) characteristics across countries. The current study included all new applicants to the four GID clinics who were seen between January 2007 and March 2009, were at least 16 years of age at their first visit, and had completed the diagnostic assessment (N = 214, mean age = 32 ± 12.2 years). Mokken scale analysis, a form of Nonparametric Item Response Theory (NIRT) was performed. Operationalization and quantification of the core criteria A and B resulted in a 23-item score sheet that was filled out by the participating clinicians after they had made a diagnosis. We found that, when ordering the 23 items according to their means for each country separately, the rank ordering was similar among the four countries for 21 of the items. Furthermore, only one scale emerged, which combined criteria A and B when all data were analyzed together. Our results indicate that patients' symptoms were interpreted in a similar fashion in all four countries. However, we did not find support for the treatment of A and B as two separate criteria. We recommend the use of NIRT in future studies, especially in studies with small sample sizes and/or with data that show a poor fit to parametric IRT models. © 2010 International Society for Sexual Medicine.

Retrospective examination of the healthcare 'journey' of chronic orofacial pain patients referred to oral and maxillofacial surgery.

PubMed

Beecroft, E V; Durham, J; Thomson, P

2013-03-01

To gain a deeper understanding of the clinical journey taken by orofacial pain patients from initial presentation in primary care to treatment by oral and maxillofacial surgery. Retrospective audit. Data were collected from 101 consecutive patients suffering from chronic orofacial pain, attending oral and maxillofacial surgery clinics between 2009 and 2010. Once the patients were identified, information was drawn from their hospital records and referral letters, and a predesigned proforma was completed by a single examiner (EVB). Basic descriptive statistics and non-parametric inferential statistical techniques (Krushal-Wallis) were used to analyse the data. DATA AND DISCUSSION: Six definitive orofacial pain conditions were represented in the data set, 75% of which were temporomandibular disorders (TMD). Individuals within our study were treated in nine different hospital settings and were referred to 15 distinct specialties. The mean number of consultations received by the patients in our study across all care settings is seven (SD 5). The mean number of specialities that the subjects were assessed by was three (SD 1). The sample set had a total of 341 treatment attempts to manage their chronic orofacial pain conditions, of which only 83 (24%) of all the treatments attempted yielded a successful outcome. Improved education and remuneration for primary care practitioners as well as clear care pathways for patients with chronic orofacial pain should be established to reduce multiple re-referrals and improve efficiency of care. The creation of specialist regional centres for chronic orofacial pain may be considered to manage severe cases and drive evidence-based practice.

Testing in semiparametric models with interaction, with applications to gene-environment interactions.

PubMed

Maity, Arnab; Carroll, Raymond J; Mammen, Enno; Chatterjee, Nilanjan

2009-01-01

Motivated from the problem of testing for genetic effects on complex traits in the presence of gene-environment interaction, we develop score tests in general semiparametric regression problems that involves Tukey style 1 degree-of-freedom form of interaction between parametrically and non-parametrically modelled covariates. We find that the score test in this type of model, as recently developed by Chatterjee and co-workers in the fully parametric setting, is biased and requires undersmoothing to be valid in the presence of non-parametric components. Moreover, in the presence of repeated outcomes, the asymptotic distribution of the score test depends on the estimation of functions which are defined as solutions of integral equations, making implementation difficult and computationally taxing. We develop profiled score statistics which are unbiased and asymptotically efficient and can be performed by using standard bandwidth selection methods. In addition, to overcome the difficulty of solving functional equations, we give easy interpretations of the target functions, which in turn allow us to develop estimation procedures that can be easily implemented by using standard computational methods. We present simulation studies to evaluate type I error and power of the method proposed compared with a naive test that does not consider interaction. Finally, we illustrate our methodology by analysing data from a case-control study of colorectal adenoma that was designed to investigate the association between colorectal adenoma and the candidate gene NAT2 in relation to smoking history.

A strategy for improved computational efficiency of the method of anchored distributions

NASA Astrophysics Data System (ADS)

Over, Matthew William; Yang, Yarong; Chen, Xingyuan; Rubin, Yoram

2013-06-01

This paper proposes a strategy for improving the computational efficiency of model inversion using the method of anchored distributions (MAD) by "bundling" similar model parametrizations in the likelihood function. Inferring the likelihood function typically requires a large number of forward model (FM) simulations for each possible model parametrization; as a result, the process is quite expensive. To ease this prohibitive cost, we present an approximation for the likelihood function called bundling that relaxes the requirement for high quantities of FM simulations. This approximation redefines the conditional statement of the likelihood function as the probability of a set of similar model parametrizations "bundle" replicating field measurements, which we show is neither a model reduction nor a sampling approach to improving the computational efficiency of model inversion. To evaluate the effectiveness of these modifications, we compare the quality of predictions and computational cost of bundling relative to a baseline MAD inversion of 3-D flow and transport model parameters. Additionally, to aid understanding of the implementation we provide a tutorial for bundling in the form of a sample data set and script for the R statistical computing language. For our synthetic experiment, bundling achieved a 35% reduction in overall computational cost and had a limited negative impact on predicted probability distributions of the model parameters. Strategies for minimizing error in the bundling approximation, for enforcing similarity among the sets of model parametrizations, and for identifying convergence of the likelihood function are also presented.

Impact of signal scattering and parametric uncertainties on receiver operating characteristics

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Breton, Daniel J.; Hart, Carl R.; Pettit, Chris L.

2017-05-01

The receiver operating characteristic (ROC curve), which is a plot of the probability of detection as a function of the probability of false alarm, plays a key role in the classical analysis of detector performance. However, meaningful characterization of the ROC curve is challenging when practically important complications such as variations in source emissions, environmental impacts on the signal propagation, uncertainties in the sensor response, and multiple sources of interference are considered. In this paper, a relatively simple but realistic model for scattered signals is employed to explore how parametric uncertainties impact the ROC curve. In particular, we show that parametric uncertainties in the mean signal and noise power substantially raise the tails of the distributions; since receiver operation with a very low probability of false alarm and a high probability of detection is normally desired, these tails lead to severely degraded performance. Because full a priori knowledge of such parametric uncertainties is rarely available in practice, analyses must typically be based on a finite sample of environmental states, which only partially characterize the range of parameter variations. We show how this effect can lead to misleading assessments of system performance. For the cases considered, approximately 64 or more statistically independent samples of the uncertain parameters are needed to accurately predict the probabilities of detection and false alarm. A connection is also described between selection of suitable distributions for the uncertain parameters, and Bayesian adaptive methods for inferring the parameters.

Developmental Trajectories of Adaptive Behaviors from Early Childhood to Adolescence in a Cohort of 152 Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Baghdadli, Amaria; Assouline, Brigitte; Sonie, Sandrine; Pernon, Eric; Darrou, Celine; Michelon, Cecile; Picot, Marie-Christine; Aussilloux, Charles; Pry, Rene

2012-01-01

This study examines change in 152 children over an almost 10-year period (T1: 4.9 (plus or minus 1.3) years; T2: 8.1 (plus or minus 1.3) years; T3: 15(plus or minus 1.6) years) using a group-based, semi-parametric method in order to identify distinct developmental trajectories. Important deficits remain at adolescence in the adaptive abilities of…

Parametric regression model for survival data: Weibull regression model as an example

PubMed Central

2016-01-01

Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

Efficient Simulation of Tropical Cyclone Pathways with Stochastic Perturbations

NASA Astrophysics Data System (ADS)

Webber, R.; Plotkin, D. A.; Abbot, D. S.; Weare, J.

2017-12-01

Global Climate Models (GCMs) are known to statistically underpredict intense tropical cyclones (TCs) because they fail to capture the rapid intensification and high wind speeds characteristic of the most destructive TCs. Stochastic parametrization schemes have the potential to improve the accuracy of GCMs. However, current analysis of these schemes through direct sampling is limited by the computational expense of simulating a rare weather event at fine spatial gridding. The present work introduces a stochastically perturbed parametrization tendency (SPPT) scheme to increase simulated intensity of TCs. We adapt the Weighted Ensemble algorithm to simulate the distribution of TCs at a fraction of the computational effort required in direct sampling. We illustrate the efficiency of the SPPT scheme by comparing simulations at different spatial resolutions and stochastic parameter regimes. Stochastic parametrization and rare event sampling strategies have great potential to improve TC prediction and aid understanding of tropical cyclogenesis. Since rising sea surface temperatures are postulated to increase the intensity of TCs, these strategies can also improve predictions about climate change-related weather patterns. The rare event sampling strategies used in the current work are not only a novel tool for studying TCs, but they may also be applied to sampling any range of extreme weather events.

The composition of M-type asteroids: Synthesis of spectroscopic and radar observations

NASA Astrophysics Data System (ADS)

Neeley, J. R.; Ockert-Bell, M. E.; Clark, B. E.; Shepard, M. K.; Cloutis, E. A.; Fornasier, S.; Bus, S. J.

2011-10-01

This work updates our and expands our long term radar-driven observational campaign of 27 main-belt asteroids (MBAs) focused on Bus-DeMeo Xc- and Xk-type objects (Tholen X and M class asteroids) using the Arecibo radar and NASA Infrared Telescope Facilities (IRTF). Seventeen of our targets were near-simultaneously observed with radar and those observations are described in companion paper (Shepard et al., 2010). We utilized visible wavelength for a more complete compositional analysis of our targets. Compositional evidence is derived from our target asteroid spectra using three different methods: 1) a χ2 search for spectral matches in the RELAB database, 2) parametric comparisons with meteorites and 3) linear discriminant analysis. This paper synthesizes the results of the RELAB search, parametric comparisons, and linear discriminant analysis with compositional suggestions based on radar observations. We find that for six of seventeen targets with radar data, our spectral results are consistent with their radar analog (16 Psyche, 21 Lutetia, 69 Hesperia, 135 Hertha, 216 Kleopatra, and 497 Iva). For twenty out of twenty-seven objects our statistical comparisons with RELAB meteorites result in consistent analog identification, providing a degree of confidence in our parametric methods.

The binned bispectrum estimator: template-based and non-parametric CMB non-Gaussianity searches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bucher, Martin; Racine, Benjamin; Tent, Bartjan van, E-mail: bucher@apc.univ-paris7.fr, E-mail: benjar@uio.no, E-mail: vantent@th.u-psud.fr

2016-05-01

We describe the details of the binned bispectrum estimator as used for the official 2013 and 2015 analyses of the temperature and polarization CMB maps from the ESA Planck satellite. The defining aspect of this estimator is the determination of a map bispectrum (3-point correlation function) that has been binned in harmonic space. For a parametric determination of the non-Gaussianity in the map (the so-called f NL parameters), one takes the inner product of this binned bispectrum with theoretically motivated templates. However, as a complementary approach one can also smooth the binned bispectrum using a variable smoothing scale in ordermore » to suppress noise and make coherent features stand out above the noise. This allows one to look in a model-independent way for any statistically significant bispectral signal. This approach is useful for characterizing the bispectral shape of the galactic foreground emission, for which a theoretical prediction of the bispectral anisotropy is lacking, and for detecting a serendipitous primordial signal, for which a theoretical template has not yet been put forth. Both the template-based and the non-parametric approaches are described in this paper.« less

Evaluation of Oxidative Stress in Bipolar Disorder in terms of Total Oxidant Status, Total Antioxidant Status, and Oxidative Stress Index

PubMed Central

CİNGİ YİRÜN, Merve; ÜNAL, Kübranur; ALTUNSOY ŞEN, Neslihan; YİRÜN, Onur; AYDEMİR, Çiğdem; GÖKA, Erol

2016-01-01

Introduction Bipolar disorder is one of the most debilitating psychiatric disorders characterized by disruptive episodes of mania/hypomania and depression. Considering the complex role of biological and environmental factors in the etiology of affective disorders, recent studies have focused on oxidative stress, which may damage nerve cell components and take part in pathophysiology. The aim of the present study was to contribute to the data about oxidative stress in bipolar disorder by detecting the total antioxidant status (TAS), total oxidant status (TOS), and oxidative stress index (OSI) levels of manic episode (ME) and euthymic (EU) patients and by comparing these results with those of healthy controls (HCs). Methods The study population consisted of 28 EU outpatients meeting the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for bipolar disorder I and 23 inpatients who were currently hospitalized in a psychiatry ward with the diagnosis of the bipolar disorder ME according to the DSM-5 criteria. Forty-three healthy subjects were included in the study as the control group (HC). Serum TAS, TOS, and OSI levels of all the participants were determined. Results Statistical analysis of serum TAS, TOS, and OSI levels did not show any significant differences between the ME patients, EU patients, and HCs. Comparison between the bipolar disorder patients (ME+EU) and HC also did not reveal any statistically significant difference between these two groups in terms of serum TAS, TOS, and OSI levels. Conclusion To date, studies on oxidative stress in bipolar disorder have led to controversial results. In the present study, no statistically significant difference was detected between the oxidative parameters of bipolar disorder patients and HCs. In order to comprehensively evaluate oxidative stress in bipolar disorder, further studies are needed. PMID:28373794

Evaluation of Oxidative Stress in Bipolar Disorder in terms of Total Oxidant Status, Total Antioxidant Status, and Oxidative Stress Index.

PubMed

Cingi Yirün, Merve; Ünal, Kübranur; Altunsoy Şen, Neslihan; Yirün, Onur; Aydemir, Çiğdem; Göka, Erol

2016-09-01

Bipolar disorder is one of the most debilitating psychiatric disorders characterized by disruptive episodes of mania/hypomania and depression. Considering the complex role of biological and environmental factors in the etiology of affective disorders, recent studies have focused on oxidative stress, which may damage nerve cell components and take part in pathophysiology. The aim of the present study was to contribute to the data about oxidative stress in bipolar disorder by detecting the total antioxidant status (TAS), total oxidant status (TOS), and oxidative stress index (OSI) levels of manic episode (ME) and euthymic (EU) patients and by comparing these results with those of healthy controls (HCs). The study population consisted of 28 EU outpatients meeting the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for bipolar disorder I and 23 inpatients who were currently hospitalized in a psychiatry ward with the diagnosis of the bipolar disorder ME according to the DSM-5 criteria. Forty-three healthy subjects were included in the study as the control group (HC). Serum TAS, TOS, and OSI levels of all the participants were determined. Statistical analysis of serum TAS, TOS, and OSI levels did not show any significant differences between the ME patients, EU patients, and HCs. Comparison between the bipolar disorder patients (ME+EU) and HC also did not reveal any statistically significant difference between these two groups in terms of serum TAS, TOS, and OSI levels. To date, studies on oxidative stress in bipolar disorder have led to controversial results. In the present study, no statistically significant difference was detected between the oxidative parameters of bipolar disorder patients and HCs. In order to comprehensively evaluate oxidative stress in bipolar disorder, further studies are needed.

Statistics of Delta v magnitude for a trajectory correction maneuver containing deterministic and random components

NASA Technical Reports Server (NTRS)

Bollman, W. E.; Chadwick, C.

1982-01-01

A number of interplanetary missions now being planned involve placing deterministic maneuvers along the flight path to alter the trajectory. Lee and Boain (1973) examined the statistics of trajectory correction maneuver (TCM) magnitude with no deterministic ('bias') component. The Delta v vector magnitude statistics were generated for several values of random Delta v standard deviations using expansions in terms of infinite hypergeometric series. The present investigation uses a different technique (Monte Carlo simulation) to generate Delta v magnitude statistics for a wider selection of random Delta v standard deviations and also extends the analysis to the case of nonzero deterministic Delta v's. These Delta v magnitude statistics are plotted parametrically. The plots are useful in assisting the analyst in quickly answering questions about the statistics of Delta v magnitude for single TCM's consisting of both a deterministic and a random component. The plots provide quick insight into the nature of the Delta v magnitude distribution for the TCM.

Witnessing entanglement without entanglement witness operators

PubMed Central

Pezzè, Luca; Li, Yan; Li, Weidong; Smerzi, Augusto

2016-01-01

Quantum mechanics predicts the existence of correlations between composite systems that, although puzzling to our physical intuition, enable technologies not accessible in a classical world. Notwithstanding, there is still no efficient general method to theoretically quantify and experimentally detect entanglement of many qubits. Here we propose to detect entanglement by measuring the statistical response of a quantum system to an arbitrary nonlocal parametric evolution. We witness entanglement without relying on the tomographic reconstruction of the quantum state, or the realization of witness operators. The protocol requires two collective settings for any number of parties and is robust against noise and decoherence occurring after the implementation of the parametric transformation. To illustrate its user friendliness we demonstrate multipartite entanglement in different experiments with ions and photons by analyzing published data on fidelity visibilities and variances of collective observables. PMID:27681625

Nonparametric estimation of benchmark doses in environmental risk assessment

PubMed Central

Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

2013-01-01

Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

PubMed Central

Petrus, Marloes L. C.; van Veluw, G. Jerre; Wösten, Han A. B.; Claessen, Dennis

2014-01-01

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these organisms form networks of interconnected hyphae, known as pellets, which are heterogeneous in size. Here we describe a method to analyze and sort mycelial pellets using a Complex Object Parametric Analyzer and Sorter (COPAS). Detailed instructions are given for the use of the instrument and the basic statistical analysis of the data. We furthermore describe how pellets can be sorted according to user-defined settings, which enables downstream processing such as the analysis of the RNA or protein content. Using this methodology the mechanism underlying heterogeneous growth can be tackled. This will be instrumental for improving streptomycetes as a cell factory, considering the fact that productivity correlates with pellet size. PMID:24561666

Photon statistics of shot noise measured using a Josephson parametric amplifier

NASA Astrophysics Data System (ADS)

Simoneau, Jean Olivier; Virally, Stéphane; Lupien, Christian; Reulet, Bertrand

2015-03-01

Quantum measurements are very sensitive to external noise sources. Such measurements require careful amplification chain design so as not to overwhelm the signal with extraneous noise. A quantum-limited amplifier, like the Josephson parametric amplifier (paramp), is thus an ideal candidate for this purpose. We used a paramp to investigate the quantum noise of a tunnel junction. This measurement scheme allowed us to improve upon previous observations of shot noise by an order of magnitude in terms of noise temperature. With this setup, we have measured the second and fourth cumulants of current fluctuations generated by the tunnel junction within a 40 MHz bandwidth around 6 GHz. From theses measurements, we deduce the variance of the photon number fluctuations for various bias schemes of the junction. In particular, we investigate the regime where the junction emits pairs of photons.

Parametric and experimental analysis using a power flow approach

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1990-01-01

A structural power flow approach for the analysis of structure-borne transmission of vibrations is used to analyze the influence of structural parameters on transmitted power. The parametric analysis is also performed using the Statistical Energy Analysis approach and the results are compared with those obtained using the power flow approach. The advantages of structural power flow analysis are demonstrated by comparing the type of results that are obtained by the two analytical methods. Also, to demonstrate that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental study of structural power flow is presented. This experimental study presents results for an L shaped beam for which an available solution was already obtained. Various methods to measure vibrational power flow are compared to study their advantages and disadvantages.

Statistical parametric mapping of the regional distribution and ontogenetic scaling of foot pressures during walking in Asian elephants (Elephas maximus).

PubMed

Panagiotopoulou, Olga; Pataky, Todd C; Hill, Zoe; Hutchinson, John R

2012-05-01

Foot pressure distributions during locomotion have causal links with the anatomical and structural configurations of the foot tissues and the mechanics of locomotion. Elephant feet have five toes bound in a flexible pad of fibrous tissue (digital cushion). Does this specialized foot design control peak foot pressures in such giant animals? And how does body size, such as during ontogenetic growth, influence foot pressures? We addressed these questions by studying foot pressure distributions in elephant feet and their correlation with body mass and centre of pressure trajectories, using statistical parametric mapping (SPM), a neuro-imaging technology. Our results show a positive correlation between body mass and peak pressures, with the highest pressures dominated by the distal ends of the lateral toes (digits 3, 4 and 5). We also demonstrate that pressure reduction in the elephant digital cushion is a complex interaction of its viscoelastic tissue structure and its centre of pressure trajectories, because there is a tendency to avoid rear 'heel' contact as an elephant grows. Using SPM, we present a complete map of pressure distributions in elephant feet during ontogeny by performing statistical analysis at the pixel level across the entire plantar/palmar surface. We hope that our study will build confidence in the potential clinical and scaling applications of mammalian foot pressures, given our findings in support of a link between regional peak pressures and pathogenesis in elephant feet.

Localized N20 Component of Somatosensory Evoked Magnetic Fields in Frontoparietal Brain Tumor Patients Using Noise-Normalized Approaches.

PubMed

Elaina, Nor Safira; Malik, Aamir Saeed; Shams, Wafaa Khazaal; Badruddin, Nasreen; Abdullah, Jafri Malin; Reza, Mohammad Faruque

2018-06-01

To localize sensorimotor cortical activation in 10 patients with frontoparietal tumors using quantitative magnetoencephalography (MEG) with noise-normalized approaches. Somatosensory evoked magnetic fields (SEFs) were elicited in 10 patients with somatosensory tumors and in 10 control participants using electrical stimulation of the median nerve via the right and left wrists. We localized the N20m component of the SEFs using dynamic statistical parametric mapping (dSPM) and standardized low-resolution brain electromagnetic tomography (sLORETA) combined with 3D magnetic resonance imaging (MRI). The obtained coordinates were compared between groups. Finally, we statistically evaluated the N20m parameters across hemispheres using non-parametric statistical tests. The N20m sources were accurately localized to Brodmann area 3b in all members of the control group and in seven of the patients; however, the sources were shifted in three patients relative to locations outside the primary somatosensory cortex (SI). Compared with the affected (tumor) hemispheres in the patient group, N20m amplitudes and the strengths of the current sources were significantly lower in the unaffected hemispheres and in both hemispheres of the control group. These results were consistent for both dSPM and sLORETA approaches. Tumors in the sensorimotor cortex lead to cortical functional reorganization and an increase in N20m amplitude and current-source strengths. Noise-normalized approaches for MEG analysis that are integrated with MRI show accurate and reliable localization of sensorimotor function.

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

PubMed

Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

2016-01-01

Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

NASA Astrophysics Data System (ADS)

Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

2011-03-01

An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping

PubMed Central

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-01-01

Background Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. Methods The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). Results A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. Conclusion The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques. PMID:18312639

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping.

PubMed

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-02-29

Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques.

Estimating trends in the global mean temperature record

NASA Astrophysics Data System (ADS)

Poppick, Andrew; Moyer, Elisabeth J.; Stein, Michael L.

2017-06-01

Given uncertainties in physical theory and numerical climate simulations, the historical temperature record is often used as a source of empirical information about climate change. Many historical trend analyses appear to de-emphasize physical and statistical assumptions: examples include regression models that treat time rather than radiative forcing as the relevant covariate, and time series methods that account for internal variability in nonparametric rather than parametric ways. However, given a limited data record and the presence of internal variability, estimating radiatively forced temperature trends in the historical record necessarily requires some assumptions. Ostensibly empirical methods can also involve an inherent conflict in assumptions: they require data records that are short enough for naive trend models to be applicable, but long enough for long-timescale internal variability to be accounted for. In the context of global mean temperatures, empirical methods that appear to de-emphasize assumptions can therefore produce misleading inferences, because the trend over the twentieth century is complex and the scale of temporal correlation is long relative to the length of the data record. We illustrate here how a simple but physically motivated trend model can provide better-fitting and more broadly applicable trend estimates and can allow for a wider array of questions to be addressed. In particular, the model allows one to distinguish, within a single statistical framework, between uncertainties in the shorter-term vs. longer-term response to radiative forcing, with implications not only on historical trends but also on uncertainties in future projections. We also investigate the consequence on inferred uncertainties of the choice of a statistical description of internal variability. While nonparametric methods may seem to avoid making explicit assumptions, we demonstrate how even misspecified parametric statistical methods, if attuned to the important characteristics of internal variability, can result in more accurate uncertainty statements about trends.

Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA.

PubMed

Festing, M F

2001-01-01

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An "experiment" is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, while other "factorial" designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.

A Bootstrap Algorithm for Mixture Models and Interval Data in Inter-Comparisons

DTIC Science & Technology

2001-07-01

parametric bootstrap. The present algorithm will be applied to a thermometric inter-comparison, where data cannot be assumed to be normally distributed. 2 Data...experimental methods, used in each laboratory) often imply that the statistical assumptions are not satisfied, as for example in several thermometric ...triangular). Indeed, in thermometric experiments these three probabilistic models can represent several common stochastic variabilities for

The use of algorithmic behavioural transfer functions in parametric EO system performance models

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.

2015-10-01

The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach and architecture are described in detail, and example results based on a practical application are then given which illustrate the performance benefits. Finally, conclusions are drawn and comments given regarding the benefits and uses of the new approach.

Investigation of the Effects of High-Intensity, Intermittent Exercise and Unanticipation on Trunk and Lower Limb Biomechanics During a Side-Cutting Maneuver Using Statistical Parametric Mapping.

PubMed

Whyte, Enda F; Richter, Chris; OʼConnor, Siobhan; Moran, Kieran A

2018-06-01

Whyte, EF, Richter, C, O'Connor, S, and Moran, KA. Investigation of the effects of high-intensity, intermittent exercise and unanticipation on trunk and lower limb biomechanics during a side-cutting maneuver using statistical parametric mapping. J Strength Cond Res 32(6): 1583-1593, 2018-Anterior cruciate ligament (ACL) injuries frequently occur during side-cutting maneuvers when fatigued or reacting to the sporting environment. Trunk and hip biomechanics are proposed to influence ACL loading during these activities. However, the effects of fatigue and unanticipation on the biomechanics of the kinetic chain may be limited by traditional discrete point analysis. We recruited 28 male, varsity, Gaelic footballers (21.7 ± 2.2 years; 178.7 ± 14.6 m; 81.8 ± 11.4 kg) to perform anticipated and unanticipated side-cutting maneuvers before and after a high-intensity, intermittent exercise protocol (HIIP). Statistical parametric mapping (repeated-measures analysis of varience) identified differences in phases of trunk and stance leg biomechanics during weight acceptance. Unanticipation resulted in less trunk flexion (p < 0.001) and greater side flexion away from the direction of cut (p < 0.001). This led to smaller (internal) knee flexor and greater (internal) knee extensor (p = 0.002-0.007), hip adductor (p = 0.005), and hip external rotator (p = 0.007) moments. The HIIP resulted in increased trunk flexion (p < 0.001) and side flexion away from the direction of cut (p = 0.038), resulting in smaller (internal) knee extensor moments (p = 0.006). One interaction effect was noted demonstrating greater hip extensor moments in the unanticipated condition post-HIIP (p = 0.025). Results demonstrate that unanticipation resulted in trunk kinematics considered an ACL injury risk factor. A subsequent increase in frontal and transverse plane hip loading and sagittal plane knee loading was observed, which may increase ACL strain. Conversely, HIIP-induced trunk kinematic alterations resulted in reduced sagittal plane knee and subsequent ACL loading. Therefore, adequate hip and knee control is important during unanticipated side-cutting maneuvers.

Reconstructing missing information on precipitation datasets: impact of tails on adopted statistical distributions.

NASA Astrophysics Data System (ADS)

Pedretti, Daniele; Beckie, Roger Daniel

2014-05-01

Missing data in hydrological time-series databases are ubiquitous in practical applications, yet it is of fundamental importance to make educated decisions in problems involving exhaustive time-series knowledge. This includes precipitation datasets, since recording or human failures can produce gaps in these time series. For some applications, directly involving the ratio between precipitation and some other quantity, lack of complete information can result in poor understanding of basic physical and chemical dynamics involving precipitated water. For instance, the ratio between precipitation (recharge) and outflow rates at a discharge point of an aquifer (e.g. rivers, pumping wells, lysimeters) can be used to obtain aquifer parameters and thus to constrain model-based predictions. We tested a suite of methodologies to reconstruct missing information in rainfall datasets. The goal was to obtain a suitable and versatile method to reduce the errors given by the lack of data in specific time windows. Our analyses included both a classical chronologically-pairing approach between rainfall stations and a probability-based approached, which accounted for the probability of exceedence of rain depths measured at two or multiple stations. Our analyses proved that it is not clear a priori which method delivers the best methodology. Rather, this selection should be based considering the specific statistical properties of the rainfall dataset. In this presentation, our emphasis is to discuss the effects of a few typical parametric distributions used to model the behavior of rainfall. Specifically, we analyzed the role of distributional "tails", which have an important control on the occurrence of extreme rainfall events. The latter strongly affect several hydrological applications, including recharge-discharge relationships. The heavy-tailed distributions we considered were parametric Log-Normal, Generalized Pareto, Generalized Extreme and Gamma distributions. The methods were first tested on synthetic examples, to have a complete control of the impact of several variables such as minimum amount of data required to obtain reliable statistical distributions from the selected parametric functions. Then, we applied the methodology to precipitation datasets collected in the Vancouver area and on a mining site in Peru.

Mathematical models of cytotoxic effects in endpoint tumor cell line assays: critical assessment of the application of a single parametric value as a standard criterion to quantify the dose-response effects and new unexplored proposal formats.

PubMed

Calhelha, Ricardo C; Martínez, Mireia A; Prieto, M A; Ferreira, Isabel C F R

2017-10-23

The development of convenient tools for describing and quantifying the effects of standard and novel therapeutic agents is essential for the research community, to perform more precise evaluations. Although mathematical models and quantification criteria have been exchanged in the last decade between different fields of study, there are relevant methodologies that lack proper mathematical descriptions and standard criteria to quantify their responses. Therefore, part of the relevant information that can be drawn from the experimental results obtained and the quantification of its statistical reliability are lost. Despite its relevance, there is not a standard form for the in vitro endpoint tumor cell lines' assays (TCLA) that enables the evaluation of the cytotoxic dose-response effects of anti-tumor drugs. The analysis of all the specific problems associated with the diverse nature of the available TCLA used is unfeasible. However, since most TCLA share the main objectives and similar operative requirements, we have chosen the sulforhodamine B (SRB) colorimetric assay for cytotoxicity screening of tumor cell lines as an experimental case study. In this work, the common biological and practical non-linear dose-response mathematical models are tested against experimental data and, following several statistical analyses, the model based on the Weibull distribution was confirmed as the convenient approximation to test the cytotoxic effectiveness of anti-tumor compounds. Then, the advantages and disadvantages of all the different parametric criteria derived from the model, which enable the quantification of the dose-response drug-effects, are extensively discussed. Therefore, model and standard criteria for easily performing the comparisons between different compounds are established. The advantages include a simple application, provision of parametric estimations that characterize the response as standard criteria, economization of experimental effort and enabling rigorous comparisons among the effects of different compounds and experimental approaches. In all experimental data fitted, the calculated parameters were always statistically significant, the equations proved to be consistent and the correlation coefficient of determination was, in most of the cases, higher than 0.98.

How To Eliminate Narcissism Overnight: DSM-V and the Death of Narcissistic Personality Disorder.

PubMed

Pies, Ronald

2011-02-01

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition appears likely to eliminate the diagnosis of narcissistic personality disorder. There are significant problems with the discriminant validity of the current narcissistic personality disorder critiera set; furthermore, the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition's narrow focus on "grandiosity" probably contributes to the wide disparity between low narcissistic personality disorder prevalence rates in epidemiological studies and high rates of narcissistic personality disorder in clinical practice. Nevertheless, the best course of action may be to refine the narcissistic personality disorder criteria, followed by careful field testing and a search for biomarkers, rather than wholesale elimination of the narcissistic personality disorder category. The construct of "malignant narcissism" is also worthy of more intense empirical investigation.

Feature extraction and classification algorithms for high dimensional data

NASA Technical Reports Server (NTRS)

Lee, Chulhee; Landgrebe, David

1993-01-01

Feature extraction and classification algorithms for high dimensional data are investigated. Developments with regard to sensors for Earth observation are moving in the direction of providing much higher dimensional multispectral imagery than is now possible. In analyzing such high dimensional data, processing time becomes an important factor. With large increases in dimensionality and the number of classes, processing time will increase significantly. To address this problem, a multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage. Several truncation criteria are developed and the relationship between thresholds and the error caused by the truncation is investigated. Next an approach to feature extraction for classification is proposed based directly on the decision boundaries. It is shown that all the features needed for classification can be extracted from decision boundaries. A characteristic of the proposed method arises by noting that only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is introduced. The proposed feature extraction algorithm has several desirable properties: it predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal means or equal covariances as some previous algorithms do. In addition, the decision boundary feature extraction algorithm can be used both for parametric and non-parametric classifiers. Finally, some problems encountered in analyzing high dimensional data are studied and possible solutions are proposed. First, the increased importance of the second order statistics in analyzing high dimensional data is recognized. By investigating the characteristics of high dimensional data, the reason why the second order statistics must be taken into account in high dimensional data is suggested. Recognizing the importance of the second order statistics, there is a need to represent the second order statistics. A method to visualize statistics using a color code is proposed. By representing statistics using color coding, one can easily extract and compare the first and the second statistics.

Metabolic syndrome and its components among university students in Kenya.

PubMed

Mbugua, Samuel Mungai; Kimani, Samuel Thuo; Munyoki, Gilbert

2017-11-28

Metabolic syndrome refers to a cluster of interrelated disorders which occur together causing an increase in the risk of developing cardiovascular disease and diabetes. The university population is an understudied group despite the increase in the frequency of related disorders and metabolic risk factors e.g. obesity and diabetes, majorly due to the assumption that they are in their most active phase of life therefore healthy. This study looked at metabolic syndrome, the sedentary lifestyles and dietary habits present among university students attending Mount Kenya University, main campus. Stratified sampling was used to select participants. Self-administered questionnaires were issued to participants after a signed consent had been obtained following which clinical assessments and biochemical measures were performed. They included blood pressure, fasting blood glucose, triglycerides, high density lipoprotein-cholesterol, anthropometric measurements; height, weight, BMI and waist circumference. Pearson's chi-square tests and non-parametric independent t-test were used to analyze the prevalence of metabolic syndrome criteria per gender, the number of metabolic syndrome criteria per BMI and prevalence of metabolic syndrome criteria per BMI category. The study established that 1.9% of the participants met the criteria for diagnosis of metabolic syndrome according to HJSS criteria. Among the elements, there was statistical difference in gender BMI and waist circumference. 11.8% of subjects had two metabolic syndrome components while 3.1% had three components while none of the subjects had all six components. Elevated triglycerides was the most prevalent defining component for metabolic syndrome. There is a statistically significant relationship between sedentary lifestyle and dietary habits as risk factors to metabolic syndrome. Young adults in university have begun developing metabolic syndrome and the risk of developing the syndrome continues to increase with the components being reported in early age. Educational initiatives to encourage healthy eating should be conducted within school premises in order to reinforce the message on healthy diets and physical exercise. Pre-admission screening to identify at risk students should be conducted. Targeted interventions development through a mandatory extra co-curricular program should be enforced to positively engage those at risk.

Redefining autism spectrum disorder using DSM-5: the implications of the proposed DSM-5 criteria for autism spectrum disorders.

PubMed

Young, Robyn L; Rodi, Melissa L

2014-04-01

A number of changes were made to pervasive developmental disorders (PDDs) in the recently released diagnostic and statistical manual of mental disorders (APA, Diagnostic and statistical manual of mental disorders, American Psychiatric Publishing, Arlington, VA, 2013). Of the 210 participants in the present study who met DSM-IV-TR criteria for a PDD [i.e., autistic disorder, Asperger's disorder and pervasive developmental disorder-not otherwise specified (PDD-NOS)], only 57.1% met DSM-5 criteria (specificity = 1.0) for autism spectrum disorder when criteria were applied concurrently during diagnostic assessment. High-functioning individuals (i.e., Asperger's disorder and PDD-NOS) were less likely to meet DSM-5 criteria than those with autistic disorder. A failure to satisfy all three criteria in the social-communication domain was the most common reason for exclusion (39%). The implications of these results are discussed.

Tryptophan Hydroxylase 2 Gene Polymorphism in Anxiety and Depressive Disorder in Kashmiri Population

PubMed Central

Shoib, Sheikh; Shah, Tabindah; Mushtaq, Sahil

2014-01-01

Background: The gene of tryptophan hydroxylase is widely recognized as a major candidate gene in many psychiatric disorders. However, no study has been done which investigates tryptophan hydroxylase 2 gene polymorphism in anxiety and depressive disorders in Kashmiri population (India). Objectives: To study tryptophan hydroxylase 2 (TPH2) C 11993 A gene polymorphism in anxiety and depressive disorders. Method: Sixty patients of depression disorder, 60 patients of anxiety disorder and 40 unrelated healthy volunteers (control) were studied in a case control design. Polymorphism was determined using polymerase chain reaction (PCR) and agarose gel electrophoresis after digestion with HAP II enzyme. Genotypes and allele frequencies were compared using Chi-square tests, Fischer’s exact test, odds ratio, 95% confidence interval (C.I) and p-value of <0.05 was considered to be statistical significant. Results: The mean age ± SD of anxiety, depression and control group was 32.73±10.99, 32.20±10 and 29.75±10.12 respectively and the difference was found to be statistically non significant (p=0.349).The mean HAM-A (Hamilton rating scale for anxiety) score and HAM-D (Hamilton rating scale for depression) score was high in both groups (anxiety and depression) and found to be statistically significant (p=0.001).Depression group had AA genotype (55.2%) than control (37.5%) and was found to be statistically non significant (p=0.890).Comparison of allelic frequency revealed no association of A allele in anxiety group (76.67%) compared with control (75.5%) and was found to be statistically non significant (p= 0.866), OR 1.09 (0.56-2.11). Conclusion: TPH2C 11993 A gene was not found to be associated with major depressive disorder (MDD) and anxiety disorder in Kashmiri population. PMID:25121048

Directional statistics-based reflectance model for isotropic bidirectional reflectance distribution functions.

PubMed

Nishino, Ko; Lombardi, Stephen

2011-01-01

We introduce a novel parametric bidirectional reflectance distribution function (BRDF) model that can accurately encode a wide variety of real-world isotropic BRDFs with a small number of parameters. The key observation we make is that a BRDF may be viewed as a statistical distribution on a unit hemisphere. We derive a novel directional statistics distribution, which we refer to as the hemispherical exponential power distribution, and model real-world isotropic BRDFs as mixtures of it. We derive a canonical probabilistic method for estimating the parameters, including the number of components, of this novel directional statistics BRDF model. We show that the model captures the full spectrum of real-world isotropic BRDFs with high accuracy, but a small footprint. We also demonstrate the advantages of the novel BRDF model by showing its use for reflection component separation and for exploring the space of isotropic BRDFs.

A generalized Benford's law for JPEG coefficients and its applications in image forensics

NASA Astrophysics Data System (ADS)

Fu, Dongdong; Shi, Yun Q.; Su, Wei

2007-02-01

In this paper, a novel statistical model based on Benford's law for the probability distributions of the first digits of the block-DCT and quantized JPEG coefficients is presented. A parametric logarithmic law, i.e., the generalized Benford's law, is formulated. Furthermore, some potential applications of this model in image forensics are discussed in this paper, which include the detection of JPEG compression for images in bitmap format, the estimation of JPEG compression Qfactor for JPEG compressed bitmap image, and the detection of double compressed JPEG image. The results of our extensive experiments demonstrate the effectiveness of the proposed statistical model.

Changes in cerebral metabolism in patients with a minimally conscious state responding to zolpidem

PubMed Central

Chatelle, Camille; Thibaut, Aurore; Gosseries, Olivia; Bruno, Marie-Aurélie; Demertzi, Athena; Bernard, Claire; Hustinx, Roland; Tshibanda, Luaba; Bahri, Mohamed A.; Laureys, Steven

2014-01-01

Background: Zolpidem, a short-acting non-benzodiazepine GABA agonist hypnotic, has been shown to induce paradoxical responses in some patients with disorders of consciousness (DOC), leading to recovery of arousal and cognitive abilities. We here assessed zolpidem-induced changes in regional brain metabolism in three patients with known zolpidem response in chronic post-anoxic minimally conscious state (MCS). Methods: [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) and standardized clinical assessments using the Coma Recovery Scale-Revised were performed after administration of 10 mg zolpidem or placebo in a randomized double blind 2-day protocol. PET data preprocessing and comparison with a healthy age-matched control group were performed using statistical parametric mapping (SPM8). Results: Behaviorally, all patients recovered functional communication after administration of zolpidem (i.e., emergence from the MCS). FDG-PET showed increased metabolism in dorsolateral prefrontal and mesiofrontal cortices after zolpidem but not after placebo administration. Conclusion: Our data show a metabolic activation of prefrontal areas, corroborating the proposed mesocircuit hypothesis to explain the paradoxical effect of zolpidem observed in some patients with DOC. It also suggests the key role of the prefrontal cortices in the recovery of functional communication and object use in hypoxic patients with chronic MCS. PMID:25520636

Medical decision-making capacity in cognitively impaired Parkinson's disease patients without dementia.

PubMed

Martin, Roy C; Okonkwo, Ozioma C; Hill, Joni; Griffith, H Randall; Triebel, Kristen; Bartolucci, Alfred; Nicholas, Anthony P; Watts, Ray L; Stover, Natividad; Harrell, Lindy E; Clark, David; Marson, Daniel C

2008-10-15

Little is currently known about the higher order functional skills of patients with Parkinson disease and cognitive impairment. Medical decision-making capacity (MDC) was assessed in patients with Parkinson's disease (PD) with cognitive impairment and dementia. Participants were 16 patients with PD and cognitive impairment without dementia (PD-CIND), 16 patients with PD dementia (PDD), and 22 healthy older adults. All participants were administered the Capacity to Consent to Treatment Instrument (CCTI), a standardized capacity instrument assessing MDC under five different consent standards. Parametric and nonparametric statistical analyses were utilized to examine capacity performance on the consent standards. In addition, capacity outcomes (capable, marginally capable, or incapable outcomes) on the standards were identified for the two patient groups. Relative to controls, PD-CIND patients demonstrated significant impairment on the understanding treatment consent standard, clinically the most stringent CCTI standard. Relative to controls and PD-CIND patients, PDD patients were impaired on the three clinical standards of understanding, reasoning, and appreciation. The findings suggest that impairment in decisional capacity is already present in cognitively impaired patients with PD without dementia and increases as these patients develop dementia. Clinicians and researchers should carefully assess decisional capacity in all patients with PD with cognitive impairment. (c) 2008 Movement Disorder Society.

Damping of spin-dipole mode and generation of quadrupole mode excitations in a spin-orbit coupled Bose-Einstein condensate

NASA Astrophysics Data System (ADS)

Li, Chuan-Hsun; Blasing, David; Chen, Yong

2017-04-01

In cold atom systems, spin excitations have been shown to be a sensitive probe of interactions and quantum statistical effects, and can be used to study spin transport in both Fermi and Bose gases. In particular, spin-dipole mode (SDM) is a type of excitation that can generate a spin current without a net mass current. We present recent measurements and analysis of SDM in a disorder-free, interacting three-dimensional (3D) 87Rb Bose-Einstein condensate (BEC) by applying spin-dependent synthetic electric fields to actuate head-on collisions between two BECs of different spin states. We experimentally study and compare the behaviors of the system following SDM excitations in the presence as well as absence of synthetic 1D spin-orbit coupling (SOC). We find that in the absence of SOC, SDM is relatively weakly damped, accompanied with collision-induced thermalization which heats up the atomic cloud. However, in the presence of SOC, we find that SDM is more strongly damped with reduced thermalization, and observe excitation of a quadrupole mode that exhibits BEC shape oscillation even after SDM is damped out. Such a mode conversion bears analogies with the Beliaev coupling process or the parametric frequency down conversion of light in nonlinear optics.

Levels of heavy metals and essential minerals in hair samples of children with autism in Oman: a case-control study.

PubMed

Al-Farsi, Yahya M; Waly, Mostafa I; Al-Sharbati, Marwan M; Al-Shafaee, Mohammed A; Al-Farsi, Omar A; Al-Khaduri, Maha M; Gupta, Ishita; Ouhtit, Allal; Al-Adawi, Samir; Al-Said, Mona F; Deth, Richard C

2013-02-01

Toxic levels of heavy metals and low levels of essential minerals have been suggested to play a critical role in the pathogenesis of autism spectrum disorders (ASD). This study documents the levels of heavy metals and essential minerals in hair samples of children with ASD in Muscat, the urbanized capital of Oman, Muscat. The study included 27 children with ASD and 27 matched non-ASD controls. Parental interviews were held and dietary intake questionnaires completed in conjunction with the collection of hair samples. Analysis of heavy metals and essential minerals was carried out by inductively coupled plasma mass spectrometry. Chi-square analysis and non-parametric Fisher's exact tests were used to assess statistical significance. Children with ASD had significantly higher levels of all 11 analyzed heavy metals in their hair samples (P < 0.05), ranging from 150 to 365 % of control levels. ASD children also had significantly higher levels of essential minerals sulfur, sodium, magnesium, potassium, zinc, and iron, but lower levels of calcium and copper in their hair samples. This study corroborates data from previous studies in different parts of the world indicating the presence of elevated levels of heavy metals and selective depletion of essential minerals in the hair of children with ASD.

Psychiatric comorbidities of adults with early- and late-onset attention-deficit/hyperactivity disorder.

PubMed

Lin, Yu-Ju; Yang, Li-Kuang; Gau, Susan Shur-Fen

2016-06-01

We evaluated the psychiatric comorbidities in adults who were diagnosed with Diagnostic and Statistical Manual of Mental disorders, 5th edition attention-deficit/hyperactivity disorder as a function of recalled symptom onset before and after the age of 7 years and whether the childhood attention-deficit/hyperactivity disorder symptoms were associated with psychiatric comorbidities. In all, 214 adults who were diagnosed with Diagnostic and Statistical Manual of Mental disorders, 5th edition attention-deficit/hyperactivity disorder and 174 non-attention-deficit/hyperactivity disorder controls (aged 17-40 years) received psychiatric interviews to confirm their previous and current attention-deficit/hyperactivity disorder status and other psychiatric diagnoses. Demographics and risks of lifetime psychiatric disorders were compared among three groups: (1) attention-deficit/hyperactivity disorder, onset <7 years (early-onset); (2) attention-deficit/hyperactivity disorder, onset between 7 and 12 years (late-onset) and (3) non-attention-deficit/hyperactivity disorder controls. We also tested the effects of attention-deficit/hyperactivity disorder symptoms on the risk of later psychiatric comorbidities by Cox regression analyses. Regardless of the age of onset, attention-deficit/hyperactivity disorder was significantly associated with a wide range of psychiatric comorbidities. There were similar comorbid patterns between early- and late-onset attention-deficit/hyperactivity disorder. Regardless of attention-deficit/hyperactivity disorder diagnosis, increased severity of attention-deficit/hyperactivity disorder symptoms was associated with higher risks of oppositional defiant disorder, conduct disorder, dysthymia and sleep disorder but not major depression, which was associated with the attention-deficit/hyperactivity disorder diagnosis. Our findings suggest that elevating the threshold of age of onset to 12 years in Diagnostic and Statistical Manual of Mental disorders, 5th edition would not over-diagnose attention-deficit/hyperactivity disorder in the adult population. Recalled childhood attention-deficit/hyperactivity disorder symptom severity was correlated with conduct disorder, oppositional defiant disorder, dysthymia and sleep disorders. © The Royal Australian and New Zealand College of Psychiatrists 2015.

[How to start a neuroimaging study].

PubMed

Narumoto, Jin

2012-06-01

In order to help researchers understand how to start a neuroimaging study, several tips are described in this paper. These include 1) Choice of an imaging modality, 2) Statistical method, and 3) Interpretation of the results. 1) There are several imaging modalities available in clinical research. Advantages and disadvantages of each modality are described. 2) Statistical Parametric Mapping, which is the most common statistical software for neuroimaging analysis, is described in terms of parameter setting in normalization and level of significance. 3) In the discussion section, the region which shows a significant difference between patients and normal controls should be discussed in relation to the neurophysiology of the disease, making reference to previous reports from neuroimaging studies in normal controls, lesion studies and animal studies. A typical pattern of discussion is described.

Applications of quantum entropy to statistics

NASA Astrophysics Data System (ADS)

Silver, R. N.; Martz, H. F.

This paper develops two generalizations of the maximum entropy (ME) principle. First, Shannon classical entropy is replaced by von Neumann quantum entropy to yield a broader class of information divergences (or penalty functions) for statistics applications. Negative relative quantum entropy enforces convexity, positivity, non-local extensivity and prior correlations such as smoothness. This enables the extension of ME methods from their traditional domain of ill-posed in-verse problems to new applications such as non-parametric density estimation. Second, given a choice of information divergence, a combination of ME and Bayes rule is used to assign both prior and posterior probabilities. Hyperparameters are interpreted as Lagrange multipliers enforcing constraints. Conservation principles are proposed to act statistical regularization and other hyperparameters, such as conservation of information and smoothness. ME provides an alternative to hierarchical Bayes methods.

Personality disorder traits, risk factors, and suicide ideation among older adults.

PubMed

Jahn, Danielle R; Poindexter, Erin K; Cukrowicz, Kelly C

2015-11-01

Personality disorder traits are relatively prevalent among older adults, and can be associated with complex and chronic difficulties, including suicide risk. However, there is a lack of research regarding personality disorders and suicide ideation in older adults. Depressive symptoms and hopelessness may be important to the relation between personality disorders and suicide risk. Additionally, variables from the interpersonal theory of suicide, perceived burdensomeness and thwarted belongingness, may be critical risk factors for suicide in this population. We hypothesized that perceived burdensomeness and thwarted belongingness, theory-based variables, would act as parallel mediators of the relation between personality disorder traits and suicide ideation, whereas depressive symptoms and hopelessness would not. The hypothesis was tested in a sample of 143 older adults recruited from a primary care setting. Participants completed self-report questionnaires of personality traits, suicide ideation, depressive symptoms, hopelessness, perceived burdensomeness, and thwarted belongingness. Findings from a non-parametric bootstrapping procedure indicated that perceived burdensomeness, thwarted belongingness, and depressive symptoms mediated the relation between total personality disorder traits and suicide ideation. Hopelessness did not act as a mediator. These findings indicate that perceived burdensomeness, thwarted belongingness, and depressive symptoms are likely important risk factors for suicide ideation among older adults. Clinicians should be aware of these issues when assessing and treating suicide risk among older adults.

Changes in the pattern of substance abuse after the onset of psychosis.

PubMed

Kaiser, Roland; Löhrer, Frank; Morgan, Vera; Hambrecht, Martin

2005-06-01

The aim of this study was to examine early signs of psychosis in patients suffering from both drug dependence and schizophrenia, compared to a control group of drug-addicted patients without a comorbid psychotic disorder, and to assess whether the presence of these signs was related to changes in the pattern of substance abuse. In a rehabilitation hospital for young addicts, 32 patients with a comorbid diagnosis of schizophrenia and 30 patients without the diagnosis of a psychotic disorder, were assessed using the Interview for the Retrospective Assessment of the Onset of Schizophrenia. Information relating to 64 signs of early psychosis was collected from every patient. From the 64 signs, five groups of symptoms were defined: non-specific and precursor symptoms; non-specific and depressive symptoms; negative symptoms; positive symptoms; and impaired social adjustment. The semiquantitative pattern of substance abuse for each 1-year interval over the previous 10 years was investigated using the categories of chapter F1 of ICD-10 and including an additional category "biological drugs". The relationship between the pattern of substance abuse and the presence of early signs was assessed using anova and non-parametric statistical methods. The results indicate that the defined pathological symptomatology greatly influences the pattern of consumption of psychoactive substances in both the psychosis group and the control group. The group factor exerted the greatest influence within the categories "biological drugs" and "other stimulants", where the "psychosis and addiction group" consumed significantly more than the control group. There is a subgroup of non-psychotic addicted patients whose pattern of psychoactive substance abuse is similar to that found in addicted patients suffering from schizophrenia. It may be helpful to systematically identify this subgroup with regard to possible therapeutic implications, particularly with regard to possible pharmacological treatment options.

Methylphenidate-Elicited Dopamine Increases in Ventral Striatum Are Associated with Long-Term Symptom Improvement in Adults with Attention Deficit Hyperactivity Disorder

PubMed Central

Volkow, Nora D.; Wang, Gene-Jack; Tomasi, Dardo; Kollins, Scott H.; Wigal, Tim L.; Newcorn, Jeffrey H.; Telang, Frank W.; Fowler, Joanna S.; Logan, Jean; Wong, Christopher T.; Swanson, James M.

2012-01-01

Stimulant medications, such as methylphenidate, which are effective treatments for attention deficit hyperactivity disorder (ADHD), enhance brain dopamine signaling. However, the relationship between regional brain dopamine enhancement and treatment response has not been evaluated. Here, we assessed whether the dopamine increases elicited by methylphenidate are associated with long-term clinical response. We used a prospective design to study 20 treatment-naive adults with ADHD who were evaluated before treatment initiation and after 12 months of clinical treatment with a titrated regimen of oral methylphenidate. Methylphenidate-induced dopamine changes were evaluated with positron emission tomography and [11C]raclopride (D2/D3 receptor radioligand sensitive to competition with endogenous dopamine). Clinical responses were assessed using the Conners' Adult ADHD Rating Scale and revealed a significant reduction in symptoms of inattention and hyperactivity with long-term methylphenidate treatment. A challenge dose of 0.5 mg/kg intravenous methylphenidate significantly increased dopamine in striatum (assessed as decreases in D2/D3 receptor availability). In the ventral striatum, these dopamine increases were associated with the reductions in ratings of symptoms of inattention with clinical treatment. Statistical parametric mapping additionally showed dopamine increases in prefrontal and temporal cortices with intravenous methylphenidate that were also associated with decreases in symptoms of inattention. Our findings indicate that dopamine enhancement in ventral striatum (the brain region involved with reward and motivation) was associated with therapeutic response to methylphenidate, further corroborating the relevance of the dopamine reward/motivation circuitry in ADHD. It also provides preliminary evidence that methylphenidate-elicited dopamine increases in prefrontal and temporal cortices may also contribute to the clinical response. PMID:22262882

A phase I study of low-pressure hyperbaric oxygen therapy for blast-induced post-concussion syndrome and post-traumatic stress disorder.

PubMed

Harch, Paul G; Andrews, Susan R; Fogarty, Edward F; Amen, Daniel; Pezzullo, John C; Lucarini, Juliette; Aubrey, Claire; Taylor, Derek V; Staab, Paul K; Van Meter, Keith W

2012-01-01

This is a preliminary report on the safety and efficacy of 1.5 ATA hyperbaric oxygen therapy (HBOT) in military subjects with chronic blast-induced mild to moderate traumatic brain injury (TBI)/post-concussion syndrome (PCS) and post-traumatic stress disorder (PTSD). Sixteen military subjects received 40 1.5 ATA/60 min HBOT sessions in 30 days. Symptoms, physical and neurological exams, SPECT brain imaging, and neuropsychological and psychological testing were completed before and within 1 week after treatment. Subjects experienced reversible middle ear barotrauma (5), transient deterioration in symptoms (4), and reversible bronchospasm (1); one subject withdrew. Post-treatment testing demonstrated significant improvement in: symptoms, neurological exam, full-scale IQ (+14.8 points; p<0.001), WMS IV Delayed Memory (p=0.026), WMS-IV Working Memory (p=0.003), Stroop Test (p<0.001), TOVA Impulsivity (p=0.041), TOVA Variability (p=0.045), Grooved Pegboard (p=0.028), PCS symptoms (Rivermead PCSQ: p=0.0002), PTSD symptoms (PCL-M: p<0.001), depression (PHQ-9: p<0.001), anxiety (GAD-7: p=0.007), quality of life (MPQoL: p=0.003), and self-report of percent of normal (p<0.001), SPECT coefficient of variation in all white matter and some gray matter ROIs after the first HBOT, and in half of white matter ROIs after 40 HBOT sessions, and SPECT statistical parametric mapping analysis (diffuse improvements in regional cerebral blood flow after 1 and 40 HBOT sessions). Forty 1.5 ATA HBOT sessions in 1 month was safe in a military cohort with chronic blast-induced PCS and PTSD. Significant improvements occurred in symptoms, abnormal physical exam findings, cognitive testing, and quality-of-life measurements, with concomitant significant improvements in SPECT.

Gender differences in alpha-[(11)C]MTrp brain trapping, an index of serotonin synthesis, in medication-free individuals with major depressive disorder: a positron emission tomography study.

PubMed

Frey, Benicio N; Skelin, Ivan; Sakai, Yojiro; Nishikawa, Masami; Diksic, Mirko

2010-08-30

Women are at higher risk than men for developing major depressive disorder (MDD), but the mechanisms underlying this higher risk are unknown. Here, we report proportionally normalized alpha-[(11)C]methyl-L-tryptophan brain trapping constant (alpha-[(11)C]MTrp K*(N)), an index of serotonin synthesis, in 25 medication-free individuals with MDD and in 25 gender- and age-matched healthy subjects who were studied using positron emission tomography (PET). Comparisons of alpha-[(11)C]MTrp K*(N) values between the men and women were conducted at the voxel and cluster levels using Statistical Parametric Mapping 2 (SPM2) analysis. In addition, the alpha-[(11)C]MTrp K*(N) values on both sides of the brain were extracted and compared to identify the left to right differences, as well as the gender differences. Women with MDD displayed higher alpha-[(11)C]MTrp K*(N) than men in the inferior frontal gyrus, anterior cingulate cortex (ACC), parahippocampal gyrus, precuneus, superior parietal lobule, and occipital lingual gyrus. In a matched group of normal subjects the gender differences were opposite from those found in MDD patients. Significant hemispheric differences in fronto-limbic structures between men and women with MDD were also observed. The K*(N) extracted from the volumes identified in MDD patients and in male and female normal subjects suggested no significant differences between males and females. In conclusion, depressed women have higher serotonin synthesis in multiple regions of the prefrontal cortex and limbic system involved with mood regulation, as compared with depressed men. Gender differences in brain serotonin synthesis may be related to higher risk for MDD in women. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

The characteristics of autonomic nervous system disorders in burning mouth syndrome and Parkinson disease.

PubMed

Koszewicz, Magdalena; Mendak, Magdalena; Konopka, Tomasz; Koziorowska-Gawron, Ewa; Budrewicz, Sławomir

2012-01-01

To conduct a clinical electrophysiologic evaluation of autonomic nervous system functions in patients with burning mouth syndrome and Parkinson disease and estimate the type and intensity of the autonomic dysfunction. The study involved 83 subjects-33 with burning mouth syndrome, 20 with Parkinson disease, and 30 controls. The BMS group included 27 women and 6 men (median age, 60.0 years), and the Parkinson disease group included 15 women and 5 men (median age, 66.5 years). In the control group, there were 20 women and 10 men (median age, 59.0 years). All patients were subjected to autonomic nervous system testing. In addition to the Low autonomic disorder questionnaire, heart rate variability (HRV), deep breathing (exhalation/inspiration [E/I] ratio), and sympathetic skin response (SSR) tests were performed in all cases. Parametric and nonparametric tests (ANOVA, Kruskal-Wallis, and Scheffe tests) were used in the statistical analysis. The mean values for HRV and E/I ratios were significantly lower in the burning mouth syndrome and Parkinson disease groups. Significant prolongation of SSR latency in the foot was revealed in both burning mouth syndrome and Parkinson disease patients, and lowering of the SSR amplitude occurred in only the Parkinson disease group. The autonomic questionnaire score was significantly higher in burning mouth syndrome and Parkinson disease patients than in the control subjects, with the Parkinson disease group having the highest scores. In patients with burning mouth syndrome, a significant impairment of both the sympathetic and parasympathetic nervous systems was found but sympathetic/parasympathetic balance was preserved. The incidence and intensity of autonomic nervous system dysfunction was similar in patients with burning mouth syndrome and Parkinson disease, which may suggest some similarity in their pathogeneses.

Methylphenidate-Elicited Dopamine Increases in Ventral Striatum Are Associated with Long-Term Symptom Improvement in Adults with Attention Deficit Hyperactivity Disorder

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volkow N. D.; Wang G.; Volkow, N.D.

Stimulant medications, such as methylphenidate, which are effective treatments for attention deficit hyperactivity disorder (ADHD), enhance brain dopamine signaling. However, the relationship between regional brain dopamine enhancement and treatment response has not been evaluated. Here, we assessed whether the dopamine increases elicited by methylphenidate are associated with long-term clinical response. We used a prospective design to study 20 treatment-naive adults with ADHD who were evaluated before treatment initiation and after 12 months of clinical treatment with a titrated regimen of oral methylphenidate. Methylphenidate-induced dopamine changes were evaluated with positron emission tomography and [{sup 11}C]raclopride (D{sub 2}/D{sub 3} receptor radioligand sensitivemore » to competition with endogenous dopamine). Clinical responses were assessed using the Conners Adult ADHD Rating Scale and revealed a significant reduction in symptoms of inattention and hyperactivity with long-term methylphenidate treatment. A challenge dose of 0.5 mg/kg intravenous methylphenidate significantly increased dopamine in striatum (assessed as decreases in D{sub 2}/D{sub 3} receptor availability). In the ventral striatum, these dopamine increases were associated with the reductions in ratings of symptoms of inattention with clinical treatment. Statistical parametric mapping additionally showed dopamine increases in prefrontal and temporal cortices with intravenous methylphenidate that were also associated with decreases in symptoms of inattention. Our findings indicate that dopamine enhancement in ventral striatum (the brain region involved with reward and motivation) was associated with therapeutic response to methylphenidate, further corroborating the relevance of the dopamine reward/motivation circuitry in ADHD. It also provides preliminary evidence that methylphenidate-elicited dopamine increases in prefrontal and temporal cortices may also contribute to the clinical response.« less

Clinical correlations of grey matter reductions in the caudate nucleus of adults with attention deficit hyperactivity disorder

PubMed Central

Montes, Luis Guillermo Almeida; Ricardo-Garcell, Josefina; De La Torre, Lázaro Barajas; Alcántara, Hugo Prado; García, Reyna Beatriz Martínez; Fernández-Bouzas, Antonio; Acosta, David Ávila

2010-01-01

Background Magnetic resonance imaging (MRI) studies have shown decreased caudate volumes in individuals with attention deficit hyperactivity disorder (ADHD). However, most of these studies have been carried out in male children. Very little research has been done in adults, and the results obtained in children are difficult to extrapolate to adults. We sought to compare the volume of the caudate of adults with ADHD with that of healthy controls; we also compared these volumes between men and women. Methods We performed an MRI scan on 20 adults with ADHD (10 men and 10 women) aged 25–35 years and 20 healthy controls matched by age and sex. We used voxel-based morphometry with the DARTEL algorithm for image analyses. We used the specifically designed Friederichsen, Almeida, Serrano, Cortes Test (FASCT) to measure the severity of ADHD; both the self-reported (FASCT-SR) and the observer (FASCT-O) versions were used. Results The statistical parametric map showed a smaller region with low grey matter volume and a smaller concentration of grey matter in this region of the right caudate in ADHD patients than in health controls, both in the entire sample and within each sex. There was a significant correlation between the volume of this region of the caudate with the number of DSM IV-TR criteria, as well as with the total scores and most of the factors of the FASCT-SR and FASCT-O scales. A separate correlation analysis by sex gave similar results. Limitations The study design was cross-sectional. Conclusion The region of the right caudate with low grey matter volume was smaller in adults with ADHD in both sexes and was correlated with ADHD severity. PMID:20569650

A review of the literature on contingency management in the treatment of substance use disorders, 2009–2014

PubMed Central

Davis, Danielle R.; Kurti, Allison N.; Skelly, Joan M.; Redner, Ryan; White, Thomas J.; Higgins, Stephen T.

2017-01-01

This report describes a systematic literature review of voucher and related monetary-based contingency management (CM) interventions for substance use disorders (SUDs) over 5.2 years (November 2009 through December 2014). Reports were identified using the search engine PubMed, expert consultations, and published bibliographies. For inclusion, reports had to (a) involve monetary-based CM; (b) appear in a peer-reviewed journal; (c) include an experimental comparison condition; (d) describe an original study; (e) assess efficacy using inferential statistics; (f) use a research design allowing treatment effects to be attributed to CM. Sixty-nine reports met inclusion criteria and were categorized into 7 research trends: (1) extending CM to special populations, (2) parametric studies, (3) extending CM to community clinics, (4) combining CM with pharmacotherapies, (5) incorporating technology into CM, (6) investigating longer-term outcomes, (7) using CM as a research tool. The vast majority (59/69, 86%) of studies reported significant (p < 0.05) during-treatment effects. Twenty-eight (28/59, 47%) of those studies included at least one follow-up visit after CM was discontinued, with eight (8/28, 29%) reporting significant (p < 0.05) effects. Average effect size (Cohen’s d) during treatment was 0.62 (95% CI: 0.54, 0.70) and post-treatment it was 0.26 (95% CI: 0.11, 0.41). Overall, the literature on voucher-based CM over the past 5 years documents sustained growth, high treatment efficacy, moderate to large effect sizes during treatment that weaken but remain evident following treatment termination, and breadth across a diverse set of SUDs, populations, and settings consistent with and extending results from prior reviews. PMID:27514250

Association between a serotonin transporter promoter polymorphism (5HTTLPR) and personality disorder traits in a community sample.

PubMed

Blom, Rianne M; Samuels, Jack F; Riddle, Mark A; Joseph Bienvenu, O; Grados, Marco A; Reti, Irving M; Eaton, William W; Liang, Kung-Yee; Nestadt, Gerald

2011-09-01

The serotonin transporter (SERT) polymorphism (5HTTLPR) has been reported to be associated with several psychiatric conditions. Specific personality disorders could be intermediate factors in the known relationship between 5HTTLPR and psychiatric disorders. This is the first study to test the association between this polymorphism and dimensions of all DSM-IV personality disorders in a community sample. 374 white participants were assessed by clinical psychologists using the International Personality Disorder Examination (IPDE). Associations between dimensions of each DSM-IV personality disorder and the long (l) and short (s) alleles of the 5HTTLPR were evaluated using non-parametric tests and regression models. The s allele of the 5HTTLPR polymorphism was significantly associated with higher avoidant personality trait scores in the whole sample. Males with the s allele had a significantly lower likelihood of higher obsessive-compulsive personality disorder (OCPD) trait scores, whereas females with the s allele were likely to have higher OCPD personality trait scores. This paper provides preliminary data on the relationship between personality disorders and the 5HTTLPR polymorphism. The relationship of the s allele and avoidant PD is consistent with findings of a nonspecific relationship of this polymorphism to anxiety and depressive disorders. Concerning the unusual sexual dimorphic result with OCPD, several hypotheses are presented. These findings need further replication, including a more detailed study of additional variants in SERT. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling the World Health Organization Disability Assessment Schedule II using non-parametric item response models.

PubMed

Galindo-Garre, Francisca; Hidalgo, María Dolores; Guilera, Georgina; Pino, Oscar; Rojo, J Emilio; Gómez-Benito, Juana

2015-03-01

The World Health Organization Disability Assessment Schedule II (WHO-DAS II) is a multidimensional instrument developed for measuring disability. It comprises six domains (getting around, self-care, getting along with others, life activities and participation in society). The main purpose of this paper is the evaluation of the psychometric properties for each domain of the WHO-DAS II with parametric and non-parametric Item Response Theory (IRT) models. A secondary objective is to assess whether the WHO-DAS II items within each domain form a hierarchy of invariantly ordered severity indicators of disability. A sample of 352 patients with a schizophrenia spectrum disorder is used in this study. The 36 items WHO-DAS II was administered during the consultation. Partial Credit and Mokken scale models are used to study the psychometric properties of the questionnaire. The psychometric properties of the WHO-DAS II scale are satisfactory for all the domains. However, we identify a few items that do not discriminate satisfactorily between different levels of disability and cannot be invariantly ordered in the scale. In conclusion the WHO-DAS II can be used to assess overall disability in patients with schizophrenia, but some domains are too general to assess functionality in these patients because they contain items that are not applicable to this pathology. Copyright © 2014 John Wiley & Sons, Ltd.

Deep space network software cost estimation model

NASA Technical Reports Server (NTRS)

Tausworthe, R. C.

1981-01-01

A parametric software cost estimation model prepared for Jet PRopulsion Laboratory (JPL) Deep Space Network (DSN) Data System implementation tasks is described. The resource estimation mdel modifies and combines a number of existing models. The model calibrates the task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software life-cycle statistics.

Cost Modeling for Space Telescope

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2011-01-01

Parametric cost models are an important tool for planning missions, compare concepts and justify technology investments. This paper presents on-going efforts to develop single variable and multi-variable cost models for space telescope optical telescope assembly (OTA). These models are based on data collected from historical space telescope missions. Standard statistical methods are used to derive CERs for OTA cost versus aperture diameter and mass. The results are compared with previously published models.

Certified Reduced Basis Model Characterization: a Frequentistic Uncertainty Framework

DTIC Science & Technology

2011-01-11

14) It then follows that the Legendre coefficient random vector, (Z [0], Z [1], . . . , Z [I])(ω), is (I+1)– variate normally distributed with mean (δ...I. Note each two-sided inequality represents two constraints. 3. PDE-Based Statistical Inference We now proceed to the parametrized partial...appearance of defects or geometric variations relative to an initial baseline, or perhaps manufacturing departures from nominal specifications; if our

Parabose Squeezed Operator and Its Applications

NASA Astrophysics Data System (ADS)

Yang, Wei-Min; Jing, Si-Cong

2001-03-01

By virtue of the parabose squeezed operator, propagator of a parabose parametric amplifier, explicit forms of parabose squeezed number states and normalization factors of excitation states on a parabose squeezed vacuum state are calculated, which generalize the relevant results from ordinary Bose statistics to the parabose case. The project supported by National Natural Science Foundation of China under Grant Nos 19771077, 10075042, and LWTZ 1298 of the Chinese Academy of Sciences

Quantum noise in SIS mixers

NASA Astrophysics Data System (ADS)

Zorin, A. B.

1985-03-01

In the present, quantum-statistical analysis of SIS heterodyne mixer performance, the conventional three-port model of the mixer circuit and the microscopic theory of superconducting tunnel junctions are used to derive a general expression for a noise parameter previously used for the case of parametric amplifiers. This expression is numerically evaluated for various quasiparticle current step widths, dc bias voltages, local oscillator powers, signal frequencies, signal source admittances, and operation temperatures.

Effects of Breast Cancer Chemotherapy Agents on Brain Activity in Rats: Functional Imaging Studies

DTIC Science & Technology

2011-04-29

and in a small region of the striatum. Visual stimulation produced bilateral activation of the superior colliculus, lateral geniculate and a small...pattern was seen in the lateral geniculate . These results demonstrate the feasibility of using brain activation by parametric sensory stimulation as...both the right and left lateral geniculate functional ROIs (25% and 29%, respectively). There were smaller but not statistically significant decreases

3D Simulation as a Learning Environment for Acquiring the Skill of Self-Management: An Experience Involving Spanish University Students of Education

ERIC Educational Resources Information Center

Cela-Ranilla, Jose María; Esteve-Gonzalez, Vanessa; Esteve-Mon, Francesc; Gisbert-Cervera, Merce

2014-01-01

In this study we analyze how 57 Spanish university students of Education developed a learning process in a virtual world by conducting activities that involved the skill of self-management. The learning experience comprised a serious game designed in a 3D simulation environment. Descriptive statistics and non-parametric tests were used in the…

Parametric design of pressure-relieving foot orthosis using statistics-based finite element method.

PubMed

Cheung, Jason Tak-Man; Zhang, Ming

2008-04-01

Custom-molded foot orthoses are frequently prescribed in routine clinical practice to prevent or treat plantar ulcers in diabetes by reducing the peak plantar pressure. However, the design and fabrication of foot orthosis vary among clinical practitioners and manufacturers. Moreover, little information about the parametric effect of different combinations of design factors is available. As an alternative to the experimental approach, therefore, computational models of the foot and footwear can provide efficient evaluations of different combinations of structural and material design factors on plantar pressure distribution. In this study, a combined finite element and Taguchi method was used to identify the sensitivity of five design factors (arch type, insole and midsole thickness, insole and midsole stiffness) of foot orthosis on peak plantar pressure relief. From the FE predictions, the custom-molded shape was found to be the most important design factor in reducing peak plantar pressure. Besides the use of an arch-conforming foot orthosis, the insole stiffness was found to be the second most important factor for peak pressure reduction. Other design factors, such as insole thickness, midsole stiffness and midsole thickness, contributed to less important roles in peak pressure reduction in the given order. The statistics-based FE method was found to be an effective approach in evaluating and optimizing the design of foot orthosis.

Modality-Driven Classification and Visualization of Ensemble Variance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no informationmore » about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.« less

Change detection in the dynamics of an intracellular protein synthesis model using nonlinear Kalman filtering.

PubMed

Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel

2015-10-01

A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).

Hybrid modeling as a QbD/PAT tool in process development: an industrial E. coli case study.

PubMed

von Stosch, Moritz; Hamelink, Jan-Martijn; Oliveira, Rui

2016-05-01

Process understanding is emphasized in the process analytical technology initiative and the quality by design paradigm to be essential for manufacturing of biopharmaceutical products with consistent high quality. A typical approach to developing a process understanding is applying a combination of design of experiments with statistical data analysis. Hybrid semi-parametric modeling is investigated as an alternative method to pure statistical data analysis. The hybrid model framework provides flexibility to select model complexity based on available data and knowledge. Here, a parametric dynamic bioreactor model is integrated with a nonparametric artificial neural network that describes biomass and product formation rates as function of varied fed-batch fermentation conditions for high cell density heterologous protein production with E. coli. Our model can accurately describe biomass growth and product formation across variations in induction temperature, pH and feed rates. The model indicates that while product expression rate is a function of early induction phase conditions, it is negatively impacted as productivity increases. This could correspond with physiological changes due to cytoplasmic product accumulation. Due to the dynamic nature of the model, rational process timing decisions can be made and the impact of temporal variations in process parameters on product formation and process performance can be assessed, which is central for process understanding.

School furniture and work surface lighting impacts on the body posture of Paraíba's public school students.

PubMed

da Silva, Luiz Bueno; Coutinho, Antonio Souto; da Costa Eulálio, Eliza Juliana; Soares, Elaine Victor Gonçalves

2012-01-01

The main objective of this study is to evaluate the impact of school furniture and work surface lighting on the body posture of public Middle School students from Paraíba (Brazil). The survey was carried out in two public schools and the target population for the study included 8th grade groups involving a total of 31 students. Brazilian standards for lighting levels, the CEBRACE standards for furniture measurements and the Postural Assessment Software (SAPO) for the postural misalignment assay were adopted for the measurements comparison. The statistic analysis includes analyses of parametric and non-parametric correlations. The results show that the students' most affected parts of the body were the spine, the regions of the knees and head and neck, with 90% of the total number of students presenting postural misalignment. The lighting levels were usually found below 300 lux, below recommended levels. The statistic analysis show that the more adequate the furniture seems to be to the user, the less the user will complain of pain. Such results indicate the need of investments in more suitable school furniture and structural reforms aimed at improving the lighting in the classrooms, which could fulfill the students' profile and reduce their complaints.

Does bad inference drive out good?

PubMed

Marozzi, Marco

2015-07-01

The (mis)use of statistics in practice is widely debated, and a field where the debate is particularly active is medicine. Many scholars emphasize that a large proportion of published medical research contains statistical errors. It has been noted that top class journals like Nature Medicine and The New England Journal of Medicine publish a considerable proportion of papers that contain statistical errors and poorly document the application of statistical methods. This paper joins the debate on the (mis)use of statistics in the medical literature. Even though the validation process of a statistical result may be quite elusive, a careful assessment of underlying assumptions is central in medicine as well as in other fields where a statistical method is applied. Unfortunately, a careful assessment of underlying assumptions is missing in many papers, including those published in top class journals. In this paper, it is shown that nonparametric methods are good alternatives to parametric methods when the assumptions for the latter ones are not satisfied. A key point to solve the problem of the misuse of statistics in the medical literature is that all journals have their own statisticians to review the statistical method/analysis section in each submitted paper. © 2015 Wiley Publishing Asia Pty Ltd.

rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.

PubMed

Shi, Yang; Chinnaiyan, Arul M; Jiang, Hui

2015-07-01

High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Parametric estimate of the relative photon yields from the glasma and the quark-gluon plasma in heavy-ion collisions

DOE PAGES

Berges, Jürgen; Reygers, Klaus; Tanji, Naoto; ...

2017-05-09

Recent classical-statistical numerical simulations have established the “bottom-up” thermalization scenario of Baier et al. [Phys. Lett. B 502, 51 (2001)] as the correct weak coupling effective theory for thermalization in ultrarelativistic heavy-ion collisions. In this paper, we perform a parametric study of photon production in the various stages of this bottom-up framework to ascertain the relative contribution of the off-equilibrium “glasma” relative to that of a thermalized quark-gluon plasma. Taking into account the constraints imposed by the measured charged hadron multiplicities at Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC), we find that glasma contributions are importantmore » especially for large values of the saturation scale at both energies. Finally, these nonequilibrium effects should therefore be taken into account in studies where weak coupling methods are employed to compute photon yields.« less

Parametric study of variation in cargo-airplane performance related to progression from current to spanloader designs

NASA Technical Reports Server (NTRS)

Toll, T. A.

1980-01-01

A parametric analysis was made to investigate the relationship between current cargo airplanes and possible future designs that may differ greatly in both size and configuration. The method makes use of empirical scaling laws developed from statistical studies of data from current and advanced airplanes and, in addition, accounts for payload density, effects of span distributed load, and variations in tail area ratio. The method is believed to be particularly useful for exploratory studies of design and technology options for large airplanes. The analysis predicts somewhat more favorable variations of the ratios of payload to gross weight and block fuel to payload as the airplane size is increased than has been generally understood from interpretations of the cube-square law. In terms of these same ratios, large all wing (spanloader) designs show an advantage over wing-fuselage designs.

Sensitivity to imputation models and assumptions in receiver operating characteristic analysis with incomplete data

PubMed Central

Karakaya, Jale; Karabulut, Erdem; Yucel, Recai M.

2015-01-01

Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms. PMID:26379316

Assessing T cell clonal size distribution: a non-parametric approach.

PubMed

Bolkhovskaya, Olesya V; Zorin, Daniil Yu; Ivanchenko, Mikhail V

2014-01-01

Clonal structure of the human peripheral T-cell repertoire is shaped by a number of homeostatic mechanisms, including antigen presentation, cytokine and cell regulation. Its accurate tuning leads to a remarkable ability to combat pathogens in all their variety, while systemic failures may lead to severe consequences like autoimmune diseases. Here we develop and make use of a non-parametric statistical approach to assess T cell clonal size distributions from recent next generation sequencing data. For 41 healthy individuals and a patient with ankylosing spondylitis, who undergone treatment, we invariably find power law scaling over several decades and for the first time calculate quantitatively meaningful values of decay exponent. It has proved to be much the same among healthy donors, significantly different for an autoimmune patient before the therapy, and converging towards a typical value afterwards. We discuss implications of the findings for theoretical understanding and mathematical modeling of adaptive immunity.

A concordance index for matched case-control studies with applications in cancer risk.

PubMed

Brentnall, Adam R; Cuzick, Jack; Field, John; Duffy, Stephen W

2015-02-10

In unmatched case-control studies, the area under the receiver operating characteristic (ROC) curve (AUC) may be used to measure how well a variable discriminates between cases and controls. The AUC is sometimes used in matched case-control studies by ignoring matching, but it lacks interpretation because it is not based on an estimate of the ROC for the population of interest. We introduce an alternative measure of discrimination that is the concordance of risk factors conditional on the matching factors. Parametric and non-parametric estimators are given for different matching scenarios, and applied to real data from breast and lung cancer case-control studies. Diagnostic plots to verify the constancy of discrimination over matching factors are demonstrated. The proposed simple measure is easy to use, interpret, more efficient than unmatched AUC statistics and may be applied to compare the conditional discrimination performance of risk factors. Copyright © 2014 John Wiley & Sons, Ltd.

NASA's X-Plane Database and Parametric Cost Model v 2.0

NASA Technical Reports Server (NTRS)

Sterk, Steve; Ogluin, Anthony; Greenberg, Marc

2016-01-01

The NASA Armstrong Cost Engineering Team with technical assistance from NASA HQ (SID)has gone through the full process in developing new CERs from Version #1 to Version #2 CERs. We took a step backward and reexamined all of the data collected, such as dependent and independent variables, cost, dry weight, length, wingspan, manned versus unmanned, altitude, Mach number, thrust, and skin. We used a well- known statistical analysis tool called CO$TAT instead of using "R" multiple linear or the "Regression" tool found in Microsoft Excel(TradeMark). We setup an "array of data" by adding 21" dummy variables;" we analyzed the standard error (SE) and then determined the "best fit." We have parametrically priced-out several future X-planes and compared our results to those of other resources. More work needs to be done in getting "accurate and traceable cost data" from historical X-plane records!

Parametrically coupled fermionic oscillators: Correlation functions and phase-space description

NASA Astrophysics Data System (ADS)

Ghosh, Arnab

2015-01-01

A fermionic analog of a parametric amplifier is used to describe the joint quantum state of the two interacting fermionic modes. Based on a two-mode generalization of the time-dependent density operator, time evolution of the fermionic density operator is determined in terms of its two-mode Wigner and P function. It is shown that the equation of motion of the Wigner function corresponds to a fermionic analog of Liouville's equation. The equilibrium density operator for fermionic fields developed by Cahill and Glauber is thus extended to a dynamical context to show that the mathematical structures of both the correlation functions and the weight factors closely resemble their bosonic counterpart. It has been shown that the fermionic correlation functions are marked by a characteristic upper bound due to Fermi statistics, which can be verified in the matter wave counterpart of photon down-conversion experiments.

When Will the Antarctic Ozone Hole Recover?

NASA Technical Reports Server (NTRS)

Newman, Paul A.

2006-01-01

The Antarctic ozone hole demonstrates large-scale, man-made affects on our atmosphere. Surface observations now show that human produced ozone depleting substances (ODSs) are declining. The ozone hole should soon start to diminish because of this decline. In this talk we will demonstrate an ozone hole parametric model. This model is based upon: 1) a new algorithm for estimating 61 and Br levels over Antarctica and 2) late-spring Antarctic stratospheric temperatures. This parametric model explains 95% of the ozone hole area's variance. We use future ODS levels to predict ozone hole recovery. Full recovery to 1980 levels will occur in approximately 2068. The ozone hole area will very slowly decline over the next 2 decades. Detection of a statistically significant decrease of area will not occur until approximately 2024. We further show that nominal Antarctic stratospheric greenhouse gas forced temperature change should have a small impact on the ozone hole.

When Will the Antarctic Ozone Hole Recover?

NASA Technical Reports Server (NTRS)

Newman, Paul A.; Nash, Eric R.; Kawa, S. Randolph; Montzka, Stephen A.; Schauffler, Sue

2006-01-01

The Antarctic ozone hole demonstrates large-scale, man-made affects on our atmosphere. Surface observations now show that human produced ozone depleting substances (ODSs) are declining. The ozone hole should soon start to diminish because of this decline. Herein we demonstrate an ozone hole parametric model. This model is based upon: 1) a new algorithm for estimating C1 and Br levels over Antarctica and 2) late-spring Antarctic stratospheric temperatures. This parametric model explains 95% of the ozone hole area s variance. We use future ODS levels to predict ozone hole recovery. Full recovery to 1980 levels will occur in approximately 2068. The ozone hole area will very slowly decline over the next 2 decades. Detection of a statistically significant decrease of area will not occur until approximately 2024. We further show that nominal Antarctic stratospheric greenhouse gas forced temperature change should have a small impact on the ozone hole.

Assessing noninferiority in a three-arm trial using the Bayesian approach.

PubMed

Ghosh, Pulak; Nathoo, Farouk; Gönen, Mithat; Tiwari, Ram C

2011-07-10

Non-inferiority trials, which aim to demonstrate that a test product is not worse than a competitor by more than a pre-specified small amount, are of great importance to the pharmaceutical community. As a result, methodology for designing and analyzing such trials is required, and developing new methods for such analysis is an important area of statistical research. The three-arm trial consists of a placebo, a reference and an experimental treatment, and simultaneously tests the superiority of the reference over the placebo along with comparing this reference to an experimental treatment. In this paper, we consider the analysis of non-inferiority trials using Bayesian methods which incorporate both parametric as well as semi-parametric models. The resulting testing approach is both flexible and robust. The benefit of the proposed Bayesian methods is assessed via simulation, based on a study examining home-based blood pressure interventions. Copyright © 2011 John Wiley & Sons, Ltd.

Polariton Pattern Formation and Photon Statistics of the Associated Emission

NASA Astrophysics Data System (ADS)

Whittaker, C. E.; Dzurnak, B.; Egorov, O. A.; Buonaiuto, G.; Walker, P. M.; Cancellieri, E.; Whittaker, D. M.; Clarke, E.; Gavrilov, S. S.; Skolnick, M. S.; Krizhanovskii, D. N.

2017-07-01

We report on the formation of a diverse family of transverse spatial polygon patterns in a microcavity polariton fluid under coherent driving by a blue-detuned pump. Patterns emerge spontaneously as a result of energy-degenerate polariton-polariton scattering from the pump state to interfering high-order vortex and antivortex modes, breaking azimuthal symmetry. The interplay between a multimode parametric instability and intrinsic optical bistability leads to a sharp spike in the value of second-order coherence g(2 )(0 ) of the emitted light, which we attribute to the strongly superlinear kinetics of the underlying scattering processes driving the formation of patterns. We show numerically by means of a linear stability analysis how the growth of parametric instabilities in our system can lead to spontaneous symmetry breaking, predicting the formation and competition of different pattern states in good agreement with experimental observations.

Location tests for biomarker studies: a comparison using simulations for the two-sample case.

PubMed

Scheinhardt, M O; Ziegler, A

2013-01-01

Gene, protein, or metabolite expression levels are often non-normally distributed, heavy tailed and contain outliers. Standard statistical approaches may fail as location tests in this situation. In three Monte-Carlo simulation studies, we aimed at comparing the type I error levels and empirical power of standard location tests and three adaptive tests [O'Gorman, Can J Stat 1997; 25: 269 -279; Keselman et al., Brit J Math Stat Psychol 2007; 60: 267- 293; Szymczak et al., Stat Med 2013; 32: 524 - 537] for a wide range of distributions. We simulated two-sample scenarios using the g-and-k-distribution family to systematically vary tail length and skewness with identical and varying variability between groups. All tests kept the type I error level when groups did not vary in their variability. The standard non-parametric U-test performed well in all simulated scenarios. It was outperformed by the two non-parametric adaptive methods in case of heavy tails or large skewness. Most tests did not keep the type I error level for skewed data in the case of heterogeneous variances. The standard U-test was a powerful and robust location test for most of the simulated scenarios except for very heavy tailed or heavy skewed data, and it is thus to be recommended except for these cases. The non-parametric adaptive tests were powerful for both normal and non-normal distributions under sample variance homogeneity. But when sample variances differed, they did not keep the type I error level. The parametric adaptive test lacks power for skewed and heavy tailed distributions.

Markovian Dynamics of Josephson Parametric Amplification

NASA Astrophysics Data System (ADS)

Kaiser, Waldemar; Haider, Michael; Russer, Johannes A.; Russer, Peter; Jirauschek, Christian

2017-09-01

In this work, we derive the dynamics of the lossy DC pumped non-degenerate Josephson parametric amplifier (DCPJPA). The main element in a DCPJPA is the superconducting Josephson junction. The DC bias generates the AC Josephson current varying the nonlinear inductance of the junction. By this way the Josephson junction acts as the pump oscillator as well as the time varying reactance of the parametric amplifier. In quantum-limited amplification, losses and noise have an increased impact on the characteristics of an amplifier. We outline the classical model of the lossy DCPJPA and derive the available noise power spectral densities. A classical treatment is not capable of including properties like spontaneous emission which is mandatory in case of amplification at the quantum limit. Thus, we derive a quantum mechanical model of the lossy DCPJPA. Thermal losses are modeled by the quantum Langevin approach, by coupling the quantized system to a photon heat bath in thermodynamic equilibrium. The mode occupation in the bath follows the Bose-Einstein statistics. Based on the second quantization formalism, we derive the Heisenberg equations of motion of both resonator modes. We assume the dynamics of the system to follow the Markovian approximation, i.e. the system only depends on its actual state and is memory-free. We explicitly compute the time evolution of the contributions to the signal mode energy and give numeric examples based on different damping and coupling constants. Our analytic results show, that this model is capable of including thermal noise into the description of the DC pumped non-degenerate Josephson parametric amplifier.

Analysis of survival in breast cancer patients by using different parametric models

NASA Astrophysics Data System (ADS)

Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

2017-09-01

In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

Proposal for a biometrics of the cortical surface: a statistical method for relative surface distance metrics

NASA Astrophysics Data System (ADS)

Bookstein, Fred L.

1995-08-01

Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

PubMed

Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model

PubMed Central

Austin, Peter C.

2017-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest. PMID:29321694

Anxiety disorders are independently associated with suicide ideation and attempts: propensity score matching in two epidemiological samples.

PubMed

Thibodeau, Michel A; Welch, Patrick G; Sareen, Jitender; Asmundson, Gordon J G

2013-10-01

Research suggests that suicidal behavior in individuals with anxiety disorders is attributable to co-occurring risk factors, such as depression. We argue that these conclusions are founded primarily in statistical adjustments that may obscure independent associations. We explored independent associations between specific anxiety disorders and suicide attempts and ideation by means of propensity score matching, a process that simulates a case-control study by creating matched groups that differ in group status (e.g., diagnosis of a specific anxiety disorder) but that are statistically equivalent on observed covariates. We made use of the National Comorbidity Survey Replication (NCS-R) and the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), which include a total of 43,935 adults. Diagnoses included agoraphobia without panic disorder, generalized anxiety disorder, panic disorder with or without agoraphobia, posttraumatic stress disorder, social anxiety disorder, and specific phobia. Each anxiety disorder was (95% confidence intervals) associated with increased odds of lifetime suicide attempts (odds ratios 3.57-6.64 [NCS-R], 3.03-7.00 [NESARC]) and suicidal ideation (odds ratios 2.62-4.87 [NCS-R], 3.34-10.57 [NESARC]). Odds ratios for each disorder remained statistically significant after matching on diagnostic status of dysthymia, major depressive disorder, alcohol abuse/dependence, substance abuse/dependence, bipolar disorder I, bipolar disorder II, all other anxiety disorders, and on sociodemographic variables. This is the first report to present evidence that each anxiety disorder is associated with suicide ideation and suicide attempts beyond the effects of co-occurring mental disorders. These findings warrant consideration in assessment, intervention, and related policies. © 2013 Wiley Periodicals, Inc.

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies.

PubMed

Häggström, Ida; Beattie, Bradley J; Schmidtlein, C Ross

2016-06-01

To develop and evaluate a fast and simple tool called dpetstep (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. The tool was developed in matlab using both new and previously reported modules of petstep (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). dpetstep was 8000 times faster than MC. Dynamic images from dpetstep had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dpetstep and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dpetstep images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dpetstep images and noise properties agreed better with MC. The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dpetstep to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dpetstep can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.

Does income inequality get under the skin? A multilevel analysis of depression, anxiety and mental disorders in Sao Paulo, Brazil.

PubMed

Chiavegatto Filho, Alexandre Dias Porto; Kawachi, Ichiro; Wang, Yuan Pang; Viana, Maria Carmen; Andrade, Laura Helena Silveira Guerra

2013-11-01

Test the original income inequality theory, by analysing its association with depression, anxiety and any mental disorders. We analysed a sample of 3542 individuals aged 18 years and older selected through a stratified, multistage area probability sample of households from the São Paulo Metropolitan Area. Mental disorder symptoms were assessed using the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. Bayesian multilevel logistic models were performed. Living in areas with medium and high-income inequality was statistically associated with increased risk of depression, relative to low-inequality areas (OR 1.76; 95% CI 1.21 to 2.55, and 1.53; 95% CI 1.07 to 2.19, respectively). The same was not true for anxiety (OR 1.25; 95% CI 0.90 to 1.73, and OR 1.07; 95% CI 0.79 to 1.46). In the case of any mental disorder, results were mixed. In general, our findings were consistent with the income inequality theory, that is, people living in places with higher income inequality had an overall higher odd of mental disorders, albeit not always statistically significant. The fact that depression, but not anxiety, was statistically significant could indicate a pathway by which inequality influences health.

Personality disorders and the DSM-5: Scientific and extra-scientific factors in the maintenance of the status quo.

PubMed

Gøtzsche-Astrup, Oluf; Moskowitz, Andrew

2016-02-01

The aim of this study was to review and discuss the evidence for dimensional classification of personality disorders and the historical and sociological bases of psychiatric nosology and research. Categorical and dimensional conceptualisations of personality disorder are reviewed, with a focus on the Diagnostic and Statistical Manual of Mental Disorders-system's categorisation and the Five-Factor Model of personality. This frames the events leading up to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, personality disorder debacle, where the implementation of a hybrid model was blocked in a last-minute intervention by the American Psychiatric Association Board of Trustees. Explanations for these events are discussed, including the existence of invisible colleges of researchers and the fear of risking a 'scientific revolution' in psychiatry. A failure to recognise extra-scientific factors at work in classification of mental illness can have a profound and long-lasting influence on psychiatric nosology. In the end it was not scientific factors that led to the failure of the hybrid model of personality disorders, but opposing forces within the mental health community in general and the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, Task Force in particular. Substantial evidence has accrued over the past decades in support of a dimensional model of personality disorders. The events surrounding the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, Personality and Personality Disorders Work Group show the difficulties in reconciling two different worldviews with a hybrid model. They also indicate the future of a psychiatric nosology that will be increasingly concerned with dimensional classification of mental illness. As such, the road is paved for more substantial changes to personality disorder classification in the International Classification of Diseases, 11th Revision, in 2017. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Shared and disorder-specific task-positive and default mode network dysfunctions during sustained attention in paediatric Attention-Deficit/Hyperactivity Disorder and obsessive/compulsive disorder.

PubMed

Norman, Luke J; Carlisi, Christina O; Christakou, Anastasia; Cubillo, Ana; Murphy, Clodagh M; Chantiluke, Kaylita; Simmons, Andrew; Giampietro, Vincent; Brammer, Michael; Mataix-Cols, David; Rubia, Katya

2017-01-01

Patients with Attention-Deficit/Hyperactivity Disorder (ADHD) and obsessive/compulsive disorder (OCD) share problems with sustained attention, and are proposed to share deficits in switching between default mode and task positive networks. The aim of this study was to investigate shared and disorder-specific brain activation abnormalities during sustained attention in the two disorders. Twenty boys with ADHD, 20 boys with OCD and 20 age-matched healthy controls aged between 12 and 18 years completed a functional magnetic resonance imaging (fMRI) version of a parametrically modulated sustained attention task with a progressively increasing sustained attention load. Performance and brain activation were compared between groups. Only ADHD patients were impaired in performance. Group by sustained attention load interaction effects showed that OCD patients had disorder-specific middle anterior cingulate underactivation relative to controls and ADHD patients, while ADHD patients showed disorder-specific underactivation in left dorsolateral prefrontal cortex/dorsal inferior frontal gyrus (IFG). ADHD and OCD patients shared left insula/ventral IFG underactivation and increased activation in posterior default mode network relative to controls, but had disorder-specific overactivation in anterior default mode regions, in dorsal anterior cingulate for ADHD and in anterior ventromedial prefrontal cortex for OCD. In sum, ADHD and OCD patients showed mostly disorder-specific patterns of brain abnormalities in both task positive salience/ventral attention networks with lateral frontal deficits in ADHD and middle ACC deficits in OCD, as well as in their deactivation patterns in medial frontal DMN regions. The findings suggest that attention performance in the two disorders is underpinned by disorder-specific activation patterns.

[Clinical study of comparing comorbidity between depression and neurological disorder with depressive disorder].

PubMed

Zhang, Jing; He, Mao-Lin; Li, Shun-Wei

2010-01-26

To compare the clinical traits in comorbidity between depression and neurological disorder with depressive disorder and explore the characteristic of the outpatients with neurological disorder comorbidity in depression. According to Diagnosis and Statistic Manual for Mental Disorder-IV (DSM-IV) criteria, outpatients were diagnosed as depressive disorder at Departments of Neurology and Psychology. We used HAMD-17 scale to evaluate the patient's severity. There was no statistical difference in severity of depression in two groups. But the clinical traits showed significant differences between two outpatient groups: the outpatients with neurological disorder comorbidity in depression were elder, had more somatic disorders and a higher retard symptom factor score while the other are relative younger, have less physical disorders and higher the core symptom factor score on the other hand. The patients of comorbidity between depression and neurological disorders have unique clinical traits. Thus it will be helpful to improve the identification of diagnosis and choose an appropriate treatment if we know the differences well.

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

PubMed

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

Free energy and hidden barriers of the β-sheet structure of prion protein.

PubMed

Paz, S Alexis; Abrams, Cameron F

2015-10-13

On-the-fly free-energy parametrization is a new collective variable biasing approach akin to metadynamics with one important distinction: rather than acquiring an accelerated distribution via a history-dependent bias potential, sampling on this distribution is achieved from the beginning of the simulation using temperature-accelerated molecular dynamics. In the present work, we compare the performance of both approaches to compute the free-energy profile along a scalar collective variable measuring the H-bond registry of the β-sheet structure of the mouse Prion protein. Both methods agree on the location of the free-energy minimum, but free-energy profiles from well-tempered metadynamics are subject to a much higher degree of statistical noise due to hidden barriers. The sensitivity of metadynamics to hidden barriers is shown to be a consequence of the history dependence of the bias potential, and we detail the nature of these barriers for the prion β-sheet. In contrast, on-the-fly parametrization is much less sensitive to these barriers and thus displays improved convergence behavior relative to that of metadynamics. While hidden barriers are a frequent and central issue in free-energy methods, on-the-fly free-energy parametrization appears to be a robust and preferable method to confront this issue.

Impact Response Comparison Between Parametric Human Models and Postmortem Human Subjects with a Wide Range of Obesity Levels.

PubMed

Zhang, Kai; Cao, Libo; Wang, Yulong; Hwang, Eunjoo; Reed, Matthew P; Forman, Jason; Hu, Jingwen

2017-10-01

Field data analyses have shown that obesity significantly increases the occupant injury risks in motor vehicle crashes, but the injury assessment tools for people with obesity are largely lacking. The objectives of this study were to use a mesh morphing method to rapidly generate parametric finite element models with a wide range of obesity levels and to evaluate their biofidelity against impact tests using postmortem human subjects (PMHS). Frontal crash tests using three PMHS seated in a vehicle rear seat compartment with body mass index (BMI) from 24 to 40 kg/m 2 were selected. To develop the human models matching the PMHS geometry, statistical models of external body shape, rib cage, pelvis, and femur were applied to predict the target geometry using age, sex, stature, and BMI. A mesh morphing method based on radial basis functions was used to rapidly morph a baseline human model into the target geometry. The model-predicted body excursions and injury measures were compared to the PMHS tests. Comparisons of occupant kinematics and injury measures between the tests and simulations showed reasonable correlations across the wide range of BMI levels. The parametric human models have the capability to account for the obesity effects on the occupant impact responses and injury risks. © 2017 The Obesity Society.

Alternative evaluation metrics for risk adjustment methods.

PubMed

Park, Sungchul; Basu, Anirban

2018-06-01

Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk-adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high-expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk-adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013-2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution-based estimators achieve higher group-level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual-level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade-off in selecting an appropriate risk-adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors. Copyright © 2018 John Wiley & Sons, Ltd.

Non-parametric methods for cost-effectiveness analysis: the central limit theorem and the bootstrap compared.

PubMed

Nixon, Richard M; Wonderling, David; Grieve, Richard D

2010-03-01

Cost-effectiveness analyses (CEA) alongside randomised controlled trials commonly estimate incremental net benefits (INB), with 95% confidence intervals, and compute cost-effectiveness acceptability curves and confidence ellipses. Two alternative non-parametric methods for estimating INB are to apply the central limit theorem (CLT) or to use the non-parametric bootstrap method, although it is unclear which method is preferable. This paper describes the statistical rationale underlying each of these methods and illustrates their application with a trial-based CEA. It compares the sampling uncertainty from using either technique in a Monte Carlo simulation. The experiments are repeated varying the sample size and the skewness of costs in the population. The results showed that, even when data were highly skewed, both methods accurately estimated the true standard errors (SEs) when sample sizes were moderate to large (n>50), and also gave good estimates for small data sets with low skewness. However, when sample sizes were relatively small and the data highly skewed, using the CLT rather than the bootstrap led to slightly more accurate SEs. We conclude that while in general using either method is appropriate, the CLT is easier to implement, and provides SEs that are at least as accurate as the bootstrap. (c) 2009 John Wiley & Sons, Ltd.

Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Lee, Tai Sing

2014-01-01

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition. PMID:24555451

Pig brain stereotaxic standard space: mapping of cerebral blood flow normative values and effect of MPTP-lesioning.

PubMed

Andersen, Flemming; Watanabe, Hideaki; Bjarkam, Carsten; Danielsen, Erik H; Cumming, Paul

2005-07-15

The analysis of physiological processes in brain by position emission tomography (PET) is facilitated when images are spatially normalized to a standard coordinate system. Thus, PET activation studies of human brain frequently employ the common stereotaxic coordinates of Talairach. We have developed an analogous stereotaxic coordinate system for the brain of the Gottingen miniature pig, based on automatic co-registration of magnetic resonance (MR) images obtained in 22 male pigs. The origin of the pig brain stereotaxic space (0, 0, 0) was arbitrarily placed in the centroid of the pineal gland as identified on the average MRI template. The orthogonal planes were imposed using the line between stereotaxic zero and the optic chiasm. A series of mean MR images in the coronal, sagittal and horizontal planes were generated. To test the utility of the common coordinate system for functional imaging studies of minipig brain, we calculated cerebral blood flow (CBF) maps from normal minipigs and from minipigs with a syndrome of parkisonism induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-poisoning. These maps were transformed from the native space into the common stereotaxic space. After global normalization of these maps, an undirected search for differences between the groups was then performed using statistical parametric mapping. Using this method, we detected a statistically significant focal increase in CBF in the left cerebellum of the MPTP-lesioned group. We expect the present approach to be of general use in the statistical parametric mapping of CBF and other physiological parameters in living pig brain.

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

PubMed Central

Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

2016-01-01

Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

Effects of Inaccurate Identification of Interictal Epileptiform Discharges in Concurrent EEG-fMRI

NASA Astrophysics Data System (ADS)

Gkiatis, K.; Bromis, K.; Kakkos, I.; Karanasiou, I. S.; Matsopoulos, G. K.; Garganis, K.

2017-11-01

Concurrent continuous EEG-fMRI is a novel multimodal technique that is finding its way into clinical practice in epilepsy. EEG timeseries are used to identify the timing of interictal epileptiform discharges (IEDs) which is then included in a GLM analysis in fMRI to localize the epileptic onset zone. Nevertheless, there are still some concerns about its reliability concerning BOLD changes correlated with IEDs. Even though IEDs are identified by an experienced neurologist-epiliptologist, the reliability and concordance of the mark-ups is depending on many factors including the level of fatigue, the amount of time that he spent or, in some cases, even the screen that is being used for the display of timeseries. This investigation is aiming to unravel the effect of misidentification or inaccuracy in the mark-ups of IEDs in the fMRI statistical parametric maps. Concurrent EEG-fMRI was conducted in six subjects with various types of epilepsy. IEDs were identified by an experienced neurologist-epiliptologist. Analysis of EEG was performed with EEGLAB and analysis of fMRI was conducted in FSL. Preliminary results revealed lower statistical significance for missing events or larger period of IEDs than the actual ones and the introduction of false positives and false negatives in statistical parametric maps when random events were included in the GLM on top of the IEDs. Our results suggest that mark-ups in EEG for simultaneous EEG-fMRI should be done with caution from an experienced and restful neurologist as it affects the fMRI results in various and unpredicted ways.

Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS).

PubMed

Akhtar, Sohail; Shah, Syed Wadood Ali; Rafiq, M; Khan, Ajmal

2016-01-01

This article compares the study design and statistical methods used in 2005, 2010 and 2015 of Pakistan Journal of Medical Sciences (PJMS). Only original articles of PJMS were considered for the analysis. The articles were carefully reviewed for statistical methods and designs, and then recorded accordingly. The frequency of each statistical method and research design was estimated and compared with previous years. A total of 429 articles were evaluated (n=74 in 2005, n=179 in 2010, n=176 in 2015) in which 171 (40%) were cross-sectional and 116 (27%) were prospective study designs. A verity of statistical methods were found in the analysis. The most frequent methods include: descriptive statistics (n=315, 73.4%), chi-square/Fisher's exact tests (n=205, 47.8%) and student t-test (n=186, 43.4%). There was a significant increase in the use of statistical methods over time period: t-test, chi-square/Fisher's exact test, logistic regression, epidemiological statistics, and non-parametric tests. This study shows that a diverse variety of statistical methods have been used in the research articles of PJMS and frequency improved from 2005 to 2015. However, descriptive statistics was the most frequent method of statistical analysis in the published articles while cross-sectional study design was common study design.

Screening for atypical suicide risk with person fit statistics among people presenting to alcohol and other drug treatment.

PubMed

Conrad, Kendon J; Bezruczko, Nikolaus; Chan, Ya-Fen; Riley, Barth; Diamond, Guy; Dennis, Michael L

2010-01-15

Symptoms of internalizing disorders (depression, anxiety, somatic, trauma) are the major risk factors for suicide. Atypical suicide risk is characterized by people with few or no symptoms of internalizing disorders. In persons screened at intake to alcohol or other drug (AOD) treatment, this research examined whether person fit statistics would support an atypical subtype at high risk for suicide that did not present with typical depression and other internalizing disorders. Symptom profiles of the prototypical, typical, and atypical persons, as defined using fit statistics, were tested on 7408 persons entering AOD treatment using the Global Appraisal of Individual Needs (GAIN; Dennis et al., 2003a,b). Of those with suicide symptoms, the findings were as expected with the atypical group being higher on suicide and lower on symptoms of internalizing disorders. In addition, the atypical group was similar or lower on substance problems, symptoms of externalizing disorders, and crime and violence. Person fit statistics were useful in identifying persons with atypical suicide profiles and in enlightening aspects of existing theory concerning atypical suicidal ideation. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Women's perceived work environment after stress-related rehabilitation: experiences from the ReDO project.

PubMed

Wästberg, Birgitta A; Erlandsson, Lena-Karin; Eklund, Mona

2016-01-01

The study aimed to investigate (a) if women's perceptions of their work environment changed during a 16-week rehabilitation period and at a 12-month follow-up; (b) whether such changes were related to outcomes in terms of return to work, well-being and valued occupations. Eighty-four gainfully employed women on sick-leave due to stress-related disorders responded to instruments assessing perceptions of the work environment, well-being (self-esteem, self-mastery, quality of life, perceived stress, self-rated health) and perceived occupational value. Data about return to work were collected from registers. Non-parametric statistics were used. The increase in the women's ratings of their work environment was non-significant between baseline and completed rehabilitation but was statistically significant between baseline and the 12-month follow-up. No relationships were found between changes in perceptions of the work environment and outcomes after the rehabilitation. At the follow-up, however, there were associations between perceived work environment changes in a positive direction and return to work; improved self-esteem, self-mastery, quality of life, perceived occupational value and self-rated health; and reduced stress. It seems important to consider the work environment in rehabilitation for stress-related problems, and a follow-up appears warranted to detect changes and associations not visible immediately after rehabilitation. Work environment Perceptions of the work environment seem important for return to work, although other factors are likely to contribute as well. Perceptions of the work environment are associated with several aspects of well-being. When developing rehabilitation interventions a focus on the clients' perceptions of their work environment seems vital.

Revising the personality disorder diagnostic criteria for the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-V): consider the later life context.

PubMed

Balsis, Steve; Segal, Daniel L; Donahue, Cailin

2009-10-01

The categorical measurement approach implemented by the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) personality disorder (PD) diagnostic system is theoretically and pragmatically limited. As a result, many prominent psychologists now advocate for a shift away from this approach in favor of more conceptually sound dimensional measurement. This shift is expected to improve the psychometric properties of the personality disorder (PD) diagnostic system and make it more useful for clinicians and researchers. The current article suggests that despite the probable benefits of such a change, several limitations will remain if the new diagnostic system does not closely consider the context of later life. A failure to address the unique challenges associated with the assessment of personality in older adults likely will result in the continued limited validity, reliability, and utility of the Diagnostic and Statistical Manual of Mental Disorders (DSM) system for this growing population. This article discusses these limitations and their possible implications. (c) 2009 APA, all rights reserved.

Outcome Prediction of Consciousness Disorders in the Acute Stage Based on a Complementary Motor Behavioural Tool.

PubMed

Pignat, Jean-Michel; Mauron, Etienne; Jöhr, Jane; Gilart de Keranflec'h, Charlotte; Van De Ville, Dimitri; Preti, Maria Giulia; Meskaldji, Djalel E; Hömberg, Volker; Laureys, Steven; Draganski, Bogdan; Frackowiak, Richard; Diserens, Karin

2016-01-01

Attaining an accurate diagnosis in the acute phase for severely brain-damaged patients presenting Disorders of Consciousness (DOC) is crucial for prognostic validity; such a diagnosis determines further medical management, in terms of therapeutic choices and end-of-life decisions. However, DOC evaluation based on validated scales, such as the Revised Coma Recovery Scale (CRS-R), can lead to an underestimation of consciousness and to frequent misdiagnoses particularly in cases of cognitive motor dissociation due to other aetiologies. The purpose of this study is to determine the clinical signs that lead to a more accurate consciousness assessment allowing more reliable outcome prediction. From the Unit of Acute Neurorehabilitation (University Hospital, Lausanne, Switzerland) between 2011 and 2014, we enrolled 33 DOC patients with a DOC diagnosis according to the CRS-R that had been established within 28 days of brain damage. The first CRS-R assessment established the initial diagnosis of Unresponsive Wakefulness Syndrome (UWS) in 20 patients and a Minimally Consciousness State (MCS) in the remaining13 patients. We clinically evaluated the patients over time using the CRS-R scale and concurrently from the beginning with complementary clinical items of a new observational Motor Behaviour Tool (MBT). Primary endpoint was outcome at unit discharge distinguishing two main classes of patients (DOC patients having emerged from DOC and those remaining in DOC) and 6 subclasses detailing the outcome of UWS and MCS patients, respectively. Based on CRS-R and MBT scores assessed separately and jointly, statistical testing was performed in the acute phase using a non-parametric Mann-Whitney U test; longitudinal CRS-R data were modelled with a Generalized Linear Model. Fifty-five per cent of the UWS patients and 77% of the MCS patients had emerged from DOC. First, statistical prediction of the first CRS-R scores did not permit outcome differentiation between classes; longitudinal regression modelling of the CRS-R data identified distinct outcome evolution, but not earlier than 19 days. Second, the MBT yielded a significant outcome predictability in the acute phase (p<0.02, sensitivity>0.81). Third, a statistical comparison of the CRS-R subscales weighted by MBT became significantly predictive for DOC outcome (p<0.02). The association of MBT and CRS-R scoring improves significantly the evaluation of consciousness and the predictability of outcome in the acute phase. Subtle motor behaviour assessment provides accurate insight into the amount and the content of consciousness even in the case of cognitive motor dissociation.

Rapid computation of single PET scan rest-stress myocardial blood flow parametric images by table look up.

PubMed

Guehl, Nicolas J; Normandin, Marc D; Wooten, Dustin W; Rozen, Guy; Ruskin, Jeremy N; Shoup, Timothy M; Woo, Jonghye; Ptaszek, Leon M; Fakhri, Georges El; Alpert, Nathaniel M

2017-09-01

We have recently reported a method for measuring rest-stress myocardial blood flow (MBF) using a single, relatively short, PET scan session. The method requires two IV tracer injections, one to initiate rest imaging and one at peak stress. We previously validated absolute flow quantitation in ml/min/cc for standard bull's eye, segmental analysis. In this work, we extend the method for fast computation of rest-stress MBF parametric images. We provide an analytic solution to the single-scan rest-stress flow model which is then solved using a two-dimensional table lookup method (LM). Simulations were performed to compare the accuracy and precision of the lookup method with the original nonlinear method (NLM). Then the method was applied to 16 single scan rest/stress measurements made in 12 pigs: seven studied after infarction of the left anterior descending artery (LAD) territory, and nine imaged in the native state. Parametric maps of rest and stress MBF as well as maps of left (f LV ) and right (f RV ) ventricular spill-over fractions were generated. Regions of interest (ROIs) for 17 myocardial segments were defined in bull's eye fashion on the parametric maps. The mean of each ROI was then compared to the rest (K 1r ) and stress (K 1s ) MBF estimates obtained from fitting the 17 regional TACs with the NLM. In simulation, the LM performed as well as the NLM in terms of precision and accuracy. The simulation did not show that bias was introduced by the use of a predefined two-dimensional lookup table. In experimental data, parametric maps demonstrated good statistical quality and the LM was computationally much more efficient than the original NLM. Very good agreement was obtained between the mean MBF calculated on the parametric maps for each of the 17 ROIs and the regional MBF values estimated by the NLM (K 1map LM  = 1.019 × K 1 ROI NLM  + 0.019, R 2  = 0.986; mean difference = 0.034 ± 0.036 mL/min/cc). We developed a table lookup method for fast computation of parametric imaging of rest and stress MBF. Our results show the feasibility of obtaining good quality MBF maps using modest computational resources, thus demonstrating that the method can be applied in a clinical environment to obtain full quantitative MBF information. © 2017 American Association of Physicists in Medicine.

Evaluating the Impact of the Number of Satellite Altimeters Used in an Assimilative Ocean Prediction System

DTIC Science & Technology

2010-01-01

indicates the scaled MB, MB95 MB 1 N N j51 (O j O)2 2 4 3 5 1/2 , (12) or the biweight version, MBbw9 5 MBbw hhO j iibw , (13) and the x axis denotes...RMSEbwunbiased hhO j iibw . (15) To investigate the impact of outliers, results from both the Gaussian statistics [Eqs. (12) and (14)] and the non- parametric

Cost Estimation of Naval Ship Acquisition.

DTIC Science & Technology

1983-12-01

one a 9-sub- system model , the other a single total cost model . The models were developed using the linear least squares regression tech- nique with...to Linear Statistical Models , McGraw-Hill, 1961. 11. Helmer, F. T., Bibliography on Pricing Methodology and Cost Estimating, Dept. of Economics and...SUPPI.EMSaTARY NOTES IS. KWRo" (Cowaft. en tever aide of ..aesep M’ Idab~t 6 Week ONNa.) Cost estimation; Acquisition; Parametric cost estimate; linear

Statistically Characterizing Intra- and Inter-Individual Variability in Children with Developmental Coordination Disorder

ERIC Educational Resources Information Center

King, Bradley R.; Harring, Jeffrey R.; Oliveira, Marcio A.; Clark, Jane E.

2011-01-01

Previous research investigating children with Developmental Coordination Disorder (DCD) has consistently reported increased intra- and inter-individual variability during motor skill performance. Statistically characterizing this variability is not only critical for the analysis and interpretation of behavioral data, but also may facilitate our…

QCD Precision Measurements and Structure Function Extraction at a High Statistics, High Energy Neutrino Scattering Experiment:. NuSOnG

NASA Astrophysics Data System (ADS)

Adams, T.; Batra, P.; Bugel, L.; Camilleri, L.; Conrad, J. M.; de Gouvêa, A.; Fisher, P. H.; Formaggio, J. A.; Jenkins, J.; Karagiorgi, G.; Kobilarcik, T. R.; Kopp, S.; Kyle, G.; Loinaz, W. A.; Mason, D. A.; Milner, R.; Moore, R.; Morfín, J. G.; Nakamura, M.; Naples, D.; Nienaber, P.; Olness, F. I.; Owens, J. F.; Pate, S. F.; Pronin, A.; Seligman, W. G.; Shaevitz, M. H.; Schellman, H.; Schienbein, I.; Syphers, M. J.; Tait, T. M. P.; Takeuchi, T.; Tan, C. Y.; van de Water, R. G.; Yamamoto, R. K.; Yu, J. Y.

We extend the physics case for a new high-energy, ultra-high statistics neutrino scattering experiment, NuSOnG (Neutrino Scattering On Glass) to address a variety of issues including precision QCD measurements, extraction of structure functions, and the derived Parton Distribution Functions (PDF's). This experiment uses a Tevatron-based neutrino beam to obtain a sample of Deep Inelastic Scattering (DIS) events which is over two orders of magnitude larger than past samples. We outline an innovative method for fitting the structure functions using a parametrized energy shift which yields reduced systematic uncertainties. High statistics measurements, in combination with improved systematics, will enable NuSOnG to perform discerning tests of fundamental Standard Model parameters as we search for deviations which may hint of "Beyond the Standard Model" physics.

A generalized concept for cost-effective structural design. [Statistical Decision Theory applied to aerospace systems

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Hawk, J. D.

1975-01-01

A generalized concept for cost-effective structural design is introduced. It is assumed that decisions affecting the cost effectiveness of aerospace structures fall into three basic categories: design, verification, and operation. Within these basic categories, certain decisions concerning items such as design configuration, safety factors, testing methods, and operational constraints are to be made. All or some of the variables affecting these decisions may be treated probabilistically. Bayesian statistical decision theory is used as the tool for determining the cost optimum decisions. A special case of the general problem is derived herein, and some very useful parametric curves are developed and applied to several sample structures.

Examination of influential observations in penalized spline regression

NASA Astrophysics Data System (ADS)

Türkan, Semra

2013-10-01

In parametric or nonparametric regression models, the results of regression analysis are affected by some anomalous observations in the data set. Thus, detection of these observations is one of the major steps in regression analysis. These observations are precisely detected by well-known influence measures. Pena's statistic is one of them. In this study, Pena's approach is formulated for penalized spline regression in terms of ordinary residuals and leverages. The real data and artificial data are used to see illustrate the effectiveness of Pena's statistic as to Cook's distance on detecting influential observations. The results of the study clearly reveal that the proposed measure is superior to Cook's Distance to detect these observations in large data set.

Cosmological bounds on neutrino statistics

NASA Astrophysics Data System (ADS)

de Salas, P. F.; Gariazzo, S.; Laveder, M.; Pastor, S.; Pisanti, O.; Truong, N.

2018-03-01

We consider the phenomenological implications of the violation of the Pauli exclusion principle for neutrinos, focusing on cosmological observables such as the spectrum of Cosmic Microwave Background anisotropies, Baryon Acoustic Oscillations and the primordial abundances of light elements. Neutrinos that behave (at least partly) as bosonic particles have a modified equilibrium distribution function that implies a different influence on the evolution of the Universe that, in the case of massive neutrinos, can not be simply parametrized by a change in the effective number of neutrinos. Our results show that, despite the precision of the available cosmological data, only very weak bounds can be obtained on neutrino statistics, disfavouring a more bosonic behaviour at less than 2σ.

Statistical methods for astronomical data with upper limits. I - Univariate distributions

NASA Technical Reports Server (NTRS)

Feigelson, E. D.; Nelson, P. I.

1985-01-01

The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

Mental Disorder or "Normal Life Variation"? Why It Matters

ERIC Educational Resources Information Center

Jacobs, David H.

2014-01-01

"Diagnostic and Statistical Manual of Mental Disorders, fifth edition" ("DSM-5") promises a refined definition of mental disorder, which is tantamount to acknowledging that prior "DSM" definitions have failed to clarify what mental disorder is and why a person should be considered mentally disordered. Since the…

Proinflammatory cytokine levels in patients with conversion disorder.

PubMed

Tiyekli, Utkan; Calıyurt, Okan; Tiyekli, Nimet Dilek

2013-06-01

It was aimed to evaluate the relationship between proinflammatory cytokine levels and conversion disorder both commonly known as stress regulated. Baseline proinflammatory cytokine levels-[Tumour necrosis factor alpha (TNF-α), Interleukin-1 beta (IL-1β), Interleukin-6 (IL-6)]-were evaluated with enzyme-linked immunosorbent assay in 35 conversion disorder patients and 30 healthy controls. Possible changes in proinflammatory cytokine levels were evaluated again, after their acute phase in conversion disorder patients. Statistically significant decreased serum TNF-α levels were obtained in acute phase of conversion disorder. Those levels increased after acute conversion phase. There were no statistically significant difference observed between groups in serum IL-1β and (IL-6) levels. Stress associated with conversion disorder may suppress immune function in acute conversion phase and may have diagnostic and therapeutic value.

Full dimensional (15-dimensional) quantum-dynamical simulation of the protonated water-dimer III: Mixed Jacobi-valence parametrization and benchmark results for the zero point energy, vibrationally excited states, and infrared spectrum.

PubMed

Vendrell, Oriol; Brill, Michael; Gatti, Fabien; Lauvergnat, David; Meyer, Hans-Dieter

2009-06-21

Quantum dynamical calculations are reported for the zero point energy, several low-lying vibrational states, and the infrared spectrum of the H(5)O(2)(+) cation. The calculations are performed by the multiconfiguration time-dependent Hartree (MCTDH) method. A new vector parametrization based on a mixed Jacobi-valence description of the system is presented. With this parametrization the potential energy surface coupling is reduced with respect to a full Jacobi description, providing a better convergence of the n-mode representation of the potential. However, new coupling terms appear in the kinetic energy operator. These terms are derived and discussed. A mode-combination scheme based on six combined coordinates is used, and the representation of the 15-dimensional potential in terms of a six-combined mode cluster expansion including up to some 7-dimensional grids is discussed. A statistical analysis of the accuracy of the n-mode representation of the potential at all orders is performed. Benchmark, fully converged results are reported for the zero point energy, which lie within the statistical uncertainty of the reference diffusion Monte Carlo result for this system. Some low-lying vibrationally excited eigenstates are computed by block improved relaxation, illustrating the applicability of the approach to large systems. Benchmark calculations of the linear infrared spectrum are provided, and convergence with increasing size of the time-dependent basis and as a function of the order of the n-mode representation is studied. The calculations presented here make use of recent developments in the parallel version of the MCTDH code, which are briefly discussed. We also show that the infrared spectrum can be computed, to a very good approximation, within D(2d) symmetry, instead of the G(16) symmetry used before, in which the complete rotation of one water molecule with respect to the other is allowed, thus simplifying the dynamical problem.

Improved statistical assessment of a long-term groundwater-quality dataset with a non-parametric permutation method

NASA Astrophysics Data System (ADS)

Thomas, M. A.

2016-12-01

The Waste Isolation Pilot Plant (WIPP) is the only deep geological repository for transuranic waste in the United States. As the Science Advisor for the WIPP, Sandia National Laboratories annually evaluates site data against trigger values (TVs), metrics whose violation is indicative of conditions that may impact long-term repository performance. This study focuses on a groundwater-quality dataset used to redesign a TV for the Culebra Dolomite Member (Culebra) of the Permian-age Rustler Formation. Prior to this study, a TV violation occurred if the concentration of a major ion fell outside a range defined as the mean +/- two standard deviations. The ranges were thought to denote conditions that 95% of future values would fall within. Groundwater-quality data used in evaluating compliance, however, are rarely normally distributed. To create a more robust Culebra groundwater-quality TV, this study employed the randomization test, a non-parametric permutation method. Recent groundwater compositions considered TV violations under the original ion concentration ranges are now interpreted as false positives in light of the insignificant p-values calculated with the randomization test. This work highlights that the normality assumption can weaken as the size of a groundwater-quality dataset grows over time. Non-parametric permutation methods are an attractive option because no assumption about the statistical distribution is required and calculating all combinations of the data is an increasingly tractable problem with modern workstations. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. This research is funded by WIPP programs administered by the Office of Environmental Management (EM) of the U.S. Department of Energy. SAND2016-7306A

Efficient Statistically Accurate Algorithms for the Fokker-Planck Equation in Large Dimensions

NASA Astrophysics Data System (ADS)

Chen, N.; Majda, A.

2017-12-01

Solving the Fokker-Planck equation for high-dimensional complex turbulent dynamical systems is an important and practical issue. However, most traditional methods suffer from the curse of dimensionality and have difficulties in capturing the fat tailed highly intermittent probability density functions (PDFs) of complex systems in turbulence, neuroscience and excitable media. In this article, efficient statistically accurate algorithms are developed for solving both the transient and the equilibrium solutions of Fokker-Planck equations associated with high-dimensional nonlinear turbulent dynamical systems with conditional Gaussian structures. The algorithms involve a hybrid strategy that requires only a small number of ensembles. Here, a conditional Gaussian mixture in a high-dimensional subspace via an extremely efficient parametric method is combined with a judicious non-parametric Gaussian kernel density estimation in the remaining low-dimensional subspace. Particularly, the parametric method, which is based on an effective data assimilation framework, provides closed analytical formulae for determining the conditional Gaussian distributions in the high-dimensional subspace. Therefore, it is computationally efficient and accurate. The full non-Gaussian PDF of the system is then given by a Gaussian mixture. Different from the traditional particle methods, each conditional Gaussian distribution here covers a significant portion of the high-dimensional PDF. Therefore a small number of ensembles is sufficient to recover the full PDF, which overcomes the curse of dimensionality. Notably, the mixture distribution has a significant skill in capturing the transient behavior with fat tails of the high-dimensional non-Gaussian PDFs, and this facilitates the algorithms in accurately describing the intermittency and extreme events in complex turbulent systems. It is shown in a stringent set of test problems that the method only requires an order of O(100) ensembles to successfully recover the highly non-Gaussian transient PDFs in up to 6 dimensions with only small errors.

'DSM-V is taking away our identity': the reaction of the online community to the proposed changes in the diagnosis of Asperger's disorder.

PubMed

Giles, David C

2014-03-01

This article considers the fate of Asperger's disorder in the light of proposals for the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) to collapse Asperger's disorder along with other pervasive developmental disorders into a general spectrum of autism. It is argued that a powerful lay and scientific culture has evolved around the concept of Asperger's disorder, which has found a particularly compelling voice over the last decade in the online Asperger community, with websites such as Wrong Planet recruiting tens of thousands of members. In order to assess the impact of these proposed changes on the online Asperger community, 19 threads on the topic of Diagnostic and Statistical Manual of Mental Disorders (5th ed.) are analysed according to the arguments that community members put forward in favour of, or in opposition to, the proposals. Many members embrace the notion of the spectrum and have already coined a new identity - 'spectrumite' - to adapt to the diagnostic shift. Others, however, are suspicious of the motives behind the absorption of Asperger's disorder, and potential threats to the provision of services as well as the strong 'aspie' identity that reflects the large literature and the online public sphere around Asperger's disorder. To what extent this culture poses a challenge to the authority of the Diagnostic and Statistical Manual of Mental Disorders is uncertain at present.

Frequency-Dependence of Relative Permeability in Steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowler, N.

2006-03-06

A study to characterize metal plates by means of a model-based, broadband, four-point potential drop measurement technique has shown that the relative permeability of alloy 1018 low-carbon steel is complex and a function of frequency. A magnetic relaxation is observed at approximately 5 kHz. The relaxation can be described in terms of a parametric (Cole-Cole) model. Factors which influence the frequency, amplitude and breadth of the relaxation, such as applied current amplitude, sample geometry and disorder (e.g. percent carbon content and surface condition), are considered.

Binge Eating Disorder: A Review of a New "DSM" Diagnosis

ERIC Educational Resources Information Center

Myers, Laura L.; Wiman, Allison M.

2014-01-01

In 1994, binge eating disorder (BED) was introduced as a disorder requiring further study in the "American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders", fourth edition ("DSM-IV"). It is now listed as a distinct eating disorder in the "DSM-5", along with bulimia nervosa and anorexia…