Bayesian Estimation for Performance Measures of Two Diagnostic Tests in the Presence of Verification Bias

Sensitivity and specificity are measures that allow us to evaluate the performance of a diagnostic test. In practice, it is common to have situations where a proportion of selected individuals cannot have the real state of the disease verified, since the verification could be an invasive procedure, as occurs with biopsy. This happens, as a special case, in the diagnosis of prostate cancer, or in any other situation related to risks, that is, not practicable, nor ethical, or in situations with high cost. For this case, it is common to use diagnostic tests based only on the information of verified individuals. This procedure can lead to biased results or workup bias. In this paper, we introduce a Bayesian approach to estimate the sensitivity and the specificity for two diagnostic tests considering verified and unverified individuals, a result that generalizes the usual situation based on only one diagnostic test.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Verification of the role of the low level jets in Amazon squall lines

In this study we present a climatology of the Amazon squall lines (ASLs), between the years 2000 and 2008, using satellite imagery and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses. The ASLs we are interested in are typically formed along the northern coast of Brazil and sometimes propagate for long distances inland. Results show that, on average, an ASL occurs every 2 days. ASLs are more frequent between April and June and less frequent between October and November. The years of 2005 and 2006 showed 25% more cases than the other years. This might be related to an increase of the Atlantic sea surface temperature. Of the total number of ASL cases, 54% propagated less than 170 km, 26% propagated between 170 and 400 km, and 20% propagated more than 400 km. We also studied the occurrence of low level jets (LLJs) associated with the coastal ASLs. Although LLJs are always present in the environment before the formation of the ASL and even on days without ASL cases, important differences were found, mainly related to the LLJ depths. (C) 2010 Elsevier B.V. All rights reserved.

Perpendicular exchange bias in IrMn/Pt/[Co/Pt](3) multilayers with cone magnetization

The perpendicular exchange bias and magnetic anisotropy were investigated in IrMn/Pt/[Co/Pt](3) multilayers through the analysis of in-plane and out-of-plane magnetization hysteresis loops. A phenomenological model was used to simulate the in-plane curves and the effective perpendicular anisotropies were obtained employing the area method. The canted state anisotropy was introduced by taking into account the first and second uniaxial anisotropy terms of the ferromagnet with the corresponding uniaxial anisotropy direction allowed to make a nonzero angle with the film`s normal. This angle, obtained from the fittings, was of approximately 15 degrees for IrMn/[Co/Pt](3) film and decreases with the introduction of Pt in the IrMn/Pt/[Co/Pt](3) system, indicating that the Pt interlayer leads to a predominant perpendicular anisotropy. A maximum of the out-of-plane anisotropy was found between 0.5 and 0.6 nm of Pt, whereas a maximum of the perpendicular exchange bias was found at 0.3 nm. These results are very similar to those obtained for IrMn/Cu/[Co/Pt](3) system; however, the decrease of the exchange bias with the spacer thickness is more abrupt and the enhacement of the perpendicular anisotropy is higher for the case of Cu spacer as compared with that of Pt spacer. The existence of a maximum in the perpendicular exchange bias as a function of the Pt layer thickness was attributed to the predominance of the enhancement of exchange bias due to more perpendicular Co moment orientation over the exponential decrease of the ferromagnetic/antiferromagnetic exchange coupling and, consequently, of the exchange-bias field. (C) 2011 Elsevier B.V. All rights reserved.

Thermal dependence of the zero-bias conductance through a nanostructure

We show that the conductance of a quantum wire side-coupled to a quantum dot, with a gate potential favoring the formation of a dot magnetic moment, is a universal function of the temperature. Universality prevails even if the currents through the dot and the wire interfere. We apply this result to the experimental data of Sato et al. (Phys. Rev. Lett., 95 (2005) 066801). Copyright (C) EPLA, 2009

A WAVELET-BASED SPEAKER VERIFICATION ALGORITHM

This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

Bias-corrected estimators for dispersion models with dispersion covariates

In this paper we discuss bias-corrected estimators for the regression and the dispersion parameters in an extended class of dispersion models (Jorgensen, 1997b). This class extends the regular dispersion models by letting the dispersion parameter vary throughout the observations, and contains the dispersion models as particular case. General formulae for the O(n(-1)) bias are obtained explicitly in dispersion models with dispersion covariates, which generalize previous results obtained by Botter and Cordeiro (1998), Cordeiro and McCullagh (1991), Cordeiro and Vasconcellos (1999), and Paula (1992). The practical use of the formulae is that we can derive closed-form expressions for the O(n(-1)) biases of the maximum likelihood estimators of the regression and dispersion parameters when the information matrix has a closed-form. Various expressions for the O(n(-1)) biases are given for special models. The formulae have advantages for numerical purposes because they require only a supplementary weighted linear regression. We also compare these bias-corrected estimators with two different estimators which are also bias-free to order O(n(-1)) that are based on bootstrap methods. These estimators are compared by simulation. (C) 2011 Elsevier B.V. All rights reserved.

Bias correction in a multivariate normal regression model with general parameterization

This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.