Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Angiogenesis-related gene expression profile with independent prognostic value in advanced ovarian carcinoma.

BACKGROUND Ovarian carcinoma is the most important cause of gynecological cancer-related mortality in Western societies. Despite the improved median overall survival in patients receiving chemotherapy regimens such as paclitaxel and carboplatin combination, relapse still occurs in most advanced diseased patients. Increased angiogenesis is associated with rapid recurrence and decreased survival in ovarian cancer. This study was planned to identify an angiogenesis-related gene expression profile with prognostic value in advanced ovarian carcinoma patients. METHODOLOGY/PRINCIPAL FINDINGS RNAs were collected from formalin-fixed paraffin-embedded samples of 61 patients with III/IV FIGO stage ovarian cancer who underwent surgical cytoreduction and received a carboplatin plus paclitaxel regimen. Expression levels of 82 angiogenesis related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. A 34-gene-profile which was able to predict the overall survival of ovarian carcinoma patients was identified. After a leave-one-out cross validation, the profile distinguished two groups of patients with different outcomes. Median overall survival and progression-free survival for the high risk group was 28.3 and 15.0 months, respectively, and was not reached by patients in the low risk group at the end of follow-up. Moreover, the profile maintained an independent prognostic value in the multivariate analysis. The hazard ratio for death was 2.3 (95% CI, 1.5 to 3.2; p<0.001). CONCLUSIONS/SIGNIFICANCE It is possible to generate a prognostic model for advanced ovarian carcinoma based on angiogenesis-related genes using formalin-fixed paraffin-embedded samples. The present results are consistent with the increasing weight of angiogenesis genes in the prognosis of ovarian carcinoma.

Modern statistical models for forensic fingerprint examinations : a critical review

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basicfunctionality has seen some conceptual improvement, containing now some facilitiesto work with and represent ilr bases built from balances, and an elaborated subsys-tem for dealing with several kinds of irregular data: (rounded or structural) zeroes,incomplete observations and outliers. The general approach to these irregularities isbased on subcompositions: for an irregular datum, one can distinguish a “regular” sub-composition (where all parts are actually observed and the datum behaves typically)and a “problematic” subcomposition (with those unobserved, zero or rounded parts, orelse where the datum shows an erratic or atypical behaviour). Systematic classificationschemes are proposed for both outliers and missing values (including zeros) focusing onthe nature of irregularities in the datum subcomposition(s).To compute statistics with values missing at random and structural zeros, a projectionapproach is implemented: a given datum contributes to the estimation of the desiredparameters only on the subcompositon where it was observed. For data sets withvalues below the detection limit, two different approaches are provided: the well-knownimputation technique, and also the projection approach.To compute statistics in the presence of outliers, robust statistics are adapted to thecharacteristics of compositional data, based on the minimum covariance determinantapproach. The outlier classification is based on four different models of outlier occur-rence and Monte-Carlo-based tests for their characterization. Furthermore the packageprovides special plots helping to understand the nature of outliers in the dataset.Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator,robustness, rounded zeros

Using 3D surface datasets to understand landslide evolution: From analogue models to real case study

Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.

Visualització de models fusionats

L’objectiu principal d’aquest projecte era implementar la visualització 3D demodels fusionats i aplicar totes les tècniques possibles per realitzar aquesta fusió. Aquestes tècniques s’integraran en la plataforma de visualització i processament de dades mèdiques STARVIEWER. Per assolir l’ objectiu principal s’ han definit els següents objectius específics:1- estudiar els algoritmes de visualització de models simples i analitzar els diferents paràmetres a tenir en compte. 2- ampliació de la tècnica de visualització bàsica seleccionada per tal de suportar els models fusionats. 3- avaluar i compar tots els mètodes implementats per poder determinar quin ofereix les millors visualitzacions

Prevalence and factors associated with circadian blood pressure patterns in hypertensive patients.

Ambulatory blood pressure (BP) monitoring has become useful in the diagnosis and management of hypertensive individuals. In addition to 24-hour values, the circadian variation of BP adds prognostic significance in predicting cardiovascular outcome. However, the magnitude of circadian BP patterns in large studies has hardly been noticed. Our aims were to determine the prevalence of circadian BP patterns and to assess clinical conditions associated with the nondipping status in groups of both treated and untreated hypertensive subjects, studied separately. Clinical data and 24-hour ambulatory BP monitoring were obtained from 42,947 hypertensive patients included in the Spanish Society of Hypertension Ambulatory Blood Pressure Monitoring Registry. They were 8384 previously untreated and 34,563 treated hypertensives. Twenty-four-hour ambulatory BP monitoring was performed with an oscillometric device (SpaceLabs 90207). A nondipping pattern was defined when nocturnal systolic BP dip was <10% of daytime systolic BP. The prevalence of nondipping was 41% in the untreated group and 53% in treated patients. In both groups, advanced age, obesity, diabetes mellitus, and overt cardiovascular or renal disease were associated with a blunted nocturnal BP decline (P<0.001). In treated patients, nondipping was associated with the use of a higher number of antihypertensive drugs but not with the time of the day at which antihypertensive drugs were administered. In conclusion, a blunted nocturnal BP dip (the nondipping pattern) is common in hypertensive patients. A clinical pattern of high cardiovascular risk is associated with nondipping, suggesting that the blunted nocturnal BP dip may be merely a marker of high cardiovascular risk.

Phase III trial of consolidation therapy with yttrium-90-ibritumomab tiuxetan compared with no additional therapy after first remission in advanced follicular lymphoma.

PURPOSE: We conducted an international, randomized, phase III trial to evaluate the efficacy and safety of consolidation with yttrium-90 ((90)Y)-ibritumomab tiuxetan in patients with advanced-stage follicular lymphoma in first remission. PATIENTS AND METHODS: Patients with CD20(+) stage III or IV follicular lymphoma, who achieved a complete response (CR)/unconfirmed CR (CRu) or partial response (PR) after first-line induction treatment, were randomly assigned to receive (90)Y-ibritumomab tiuxetan (rituximab 250 mg/m(2) on day -7 and day 0 followed on day 0 by (90)Y-ibritumomab tiuxetan 14.8 MBq/kg; maximum of 1,184 MBq) or no further treatment (control). The primary end point was progression-free survival (PFS), which was calculated from the time of random assignment. RESULTS: A total of 414 patients (consolidation, n = 208; control, n = 206) were enrolled at 77 centers. (90)Y-ibritumomab tiuxetan consolidation significantly prolonged median PFS (after a median observation time of 3.5 years) in all patients (36.5 v 13.3 months in control arm; hazard ratio [HR] = 0.465; P &lt; .0001) and regardless of whether patients achieved PR (29.3 v 6.2 months in control arm; HR = 0.304; P &lt; .0001) or CR/CRu (53.9 v 29.5 months in control arm; HR = 0.613; P = .0154) after induction treatment. Median PFS with consolidation was prolonged in all Follicular Lymphoma International Prognostic Index risk subgroups. After (90)Y-ibritumomab tiuxetan consolidation, 77% of patients in PR after induction converted to CR/CRu, resulting in a final CR rate of 87%. The most common toxicity with (90)Y-ibritumomab tiuxetan was hematologic, and grade 3 or 4 infections occurred in 8% of patients. CONCLUSION: Consolidation of first remission with (90)Y-ibritumomab tiuxetan in advanced-stage follicular lymphoma is highly effective with no unexpected toxicities, prolonging PFS by 2 years and resulting in high PR-to-CR conversion rates regardless of type of first-line induction treatment.

Diagnosi basada en models tenint en compte els retards en xarxes de comunicació

Els mètodes de detecció, diagnosi i aïllament de fallades (Fault Detection and Isolation - FDI) basats en la redundància analítica (és a dir, la comparació del comportament actual del procés amb l’esperat, obtingut mitjançant un model matemàtic del mateix), són àmpliament utilitzats per al diagnòstic de sistemes quan el model matemàtic està disponible. S’ha implementat un algoritme per implementar aquesta redundància analítica a partir del model de la plana conegut com a Anàlisi Estructural

Models a Espanya, Pais Basc: Norma vasca de autoprotección

Ponència presentada a la Jornada plans d'autoprotecció