Swain: Stata module to correct the SEM chi-square overidentification test in small sample sizes or complex models. Statistical Software Components S457617, Boston College Department of Economics.

Swain corrects the chi-square overidentification test (i.e., likelihood ratio test of fit) for structural equation models whethr with or without latent variables. The chi-square statistic is asymptotically correct; however, it does not behave as expected in small samples and/or when the model is complex (cf. Herzog, Boomsma, & Reinecke, 2007). Thus, particularly in situations where the ratio of sample size (n) to the number of parameters estimated (p) is relatively small (i.e., the p to n ratio is large), the chi-square test will tend to overreject correctly specified models. To obtain a closer approximation to the distribution of the chi-square statistic, Swain (1975) developed a correction; this scaling factor, which converges to 1 asymptotically, is multiplied with the chi-square statistic. The correction better approximates the chi-square distribution resulting in more appropriate Type 1 reject error rates (see Herzog & Boomsma, 2009; Herzog, et al., 2007).

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Factors associated with latent tuberculosis among asylum seekers in Switzerland: a cross-sectional study in Vaud County.

BACKGROUND: Screening and treatment of latent tuberculosis infection (LTBI) in asylum seekers (AS) may prevent future cases of tuberculosis. As the screening with Interferon Gamma Release Assay (IGRA) is costly, the objective of this study was to assess which factors were associated with LTBI and to define a score allowing the selection of AS with the highest risk of LTBI. METHODS: In across-sectional study, AS seekers recently arrived in Vaud County, after screening for tuberculosis at the border were offered screening for LTBI with T-SPOT.TB and questionnaire on potentially risk factors. The factors associated with LTBI were analyzed by univariate and multivariate regression. RESULTS: Among 393 adult AS, 98 (24.93%) had a positive IGRA response, five of them with active tuberculosis previously undetected. Six factors associated with LTBI were identified in multivariate analysis: origin, travel conditions, marital status, cough, age and prior TB exposure. Their combination leads to a robust LTBI predictive score. CONCLUSIONS: The prevalence of LTBI and active tuberculosis in AS is high. A predictive score integrating six factors could identify the asylum seekers with the highest risk for LTBI.

Association of the Epstein-Barr virus latent membrane protein 1 with lipid rafts is mediated through its N-terminal region.

The latent membrane protein 1 (LMP1) encoded by the Epstein-Barr virus acts like a constitutively activated receptor of the tumor necrosis factor receptor (TNFR) family and is enriched in lipid rafts. We showed that LMP1 is targeted to lipid rafts in transfected HEK 293 cells, and that the endogenous TNFR-associated factor 3 binds LMP1 and is recruited to lipid rafts upon LMP1 expression. An LMP1 mutant lacking the C-terminal 55 amino acids (Cdelta55) behaves like the wild-type (WT) LMP1 with respect to membrane localization. In contrast, a mutant with a deletion of the 25 N-terminal residues (Ndelta25) does not concentrate in lipid rafts but still binds TRAF3, demonstrating that cell localization of LMP1 was not crucial for TRAF3 localization. Moreover, Ndelta25 inhibited WT LMP1-mediated induction of the transcription factors NF-kappaB and AP-1. Morphological data indicate that Ndelta25 hampers WT LMP1 plasma membrane localization, thus blocking LMP1 function.

CHARACTERIZATION OF EPSTEIN-BARR VIRUS-ENCODED LATENT MEMBRANE PROTEIN 1

Le virus d'Epstein-Barr (EBV), un virus de la famille des gammaherpesvirus, infecte plus de 95% de la population adulte mondiale. EBV est associé à plusieurs types de cancers dont le lymphome de Hodgkin, le lymphome de Burkitt et le carcinome nasopharyngé. La protéine membranaire de latence 1 (LMP1), l'oncogène principal d'EBV, est une protéine membranaire intégrale composée d'une petite extrémité N-terminale cytoplasmique, six segments transmembranaires (TMs) lié par de petites boucles et un long domaine C-terminale cytoplasmique. Le gène de LMP1, BNLF-1, est très polymorphe et plusieurs variants de la protéine LMP1 ont été décrits. Parmi les variants de LMP1 la majeure différence décrite est leur capacité à activer le facteur de transcription NF-κB. Nous avons défini des polymorphismes permettant aux variants d'avoir une activation accrue de NF-κB comparé au prototype B95-8 LMP1. Tous les polymorphismes cruciaux identifiés dans notre étude se trouvent dans les TMs 4 et 5 de LMP1. Nous avons étudié l'implication de chaque paire de TMs dans l'association à la membrane, l'auto-agrégation, la liaison aux partenaires cellulaires de LMP1 TRAF3 et β-TrCP, ainsi que pour NF-κB. De plus, nous avons décrit un nouveau rôle pour LMP1 consistant à inhiber l'activation contrôlée par MAVS de ISRE et du promoteur d'IFNβ. En résumé, nous avons observé que les différentes paires de TMs, ainsi que les deux boucles intracellulaires, ne sont pas équivalents. Dans l'ensemble, notre étude a montré que les TMs jouent un rôle clé dans les interactions protéine-protéine et la signalisation et qu'ils peuvent être considérés comme des régulateurs essentiels des activités de LMP1.

Comparison of quantiferon-TB gold with tuberculin skin test for detecting latent tuberculosis infection prior to liver transplantation.

Screening for latent tuberculosis infection (LTBI) is recommended prior to organ transplantation. The Quantiferon-TB Gold assay (QFT-G) may be more accurate than the tuberculin skin test (TST) in the detection of LTBI. We prospectively compared the results of QFT-G to TST in patients with chronic liver disease awaiting transplantation. Patients were screened for LTBI with both the QFT-G test and a TST. Concordance between test results and predictors of a discordant result were determined. Of the 153 evaluable patients, 37 (24.2%) had a positive TST and 34 (22.2%) had a positive QFT-G. Overall agreement between tests was 85.1% (kappa= 0.60, p < 0.0001). Discordant test results were seen in 12 TST positive/QFT-G negative patients and in 9 TST negative/QFT-G positive patients. Prior BCG vaccination was not associated with discordant test results. Twelve patients (7.8%), all with a negative TST, had an indeterminate result of the QFT-G and this was more likely in patients with a low lymphocyte count (p = 0.01) and a high MELD score (p = 0.001). In patients awaiting liver transplantation, both the TST and QFT-G were comparable for the diagnosis of LTBI with reasonable concordance between tests. Indeterminate QFT-G result was more likely in those with more advanced liver disease.

Infection latente a M. tuberculosis, mise a jour 2011 [Latent M. tuberculosis infection, update 2011].

It is estimated that one third of the world population is latently infected by Mycobacterium tuberculosis and thus at risk of reactivation. Latent tuberculosis (TB) impact in Switzerland is often overlooked. Diagnosis and prophylaxis are insufficiently undertaken, especially for people at higher risk of reactivation due to immunosuppression. Interferon-gamma release assays replace tuberculosis skin tests for diagnosis of latent infection in adults. It is still recommended to treat prophylactically a case of latent TB infection with 9 months of isoniazid; however therapy with rifampicin for 4 months, currently an alternative option, is linked to improved adherence and favorable cost-benefit ratio.

Sex-related and non-sex-related comorbidity subtypes of tic disorders: a latent class approach.

BACKGROUND AND PURPOSE: Recent evidence suggests that there may be more than one Gilles de la Tourette syndrome (GTS)/tic disorder phenotype. However, little is known about the common patterns of these GTS/tic disorder-related comorbidities. In addition, sex-specific phenomenological data of GTS/tic disorder-affected adults are rare. Therefore, this community-based study used latent class analyses (LCA) to investigate sex-related and non-sex-related subtypes of GTS/tic disorders and their most common comorbidities. METHODS: The data were drawn from the PsyCoLaus study (n = 3691), a population-based survey conducted in Lausanne, Switzerland. LCA were performed on the data of 80 subjects manifesting motor/vocal tics during their childhood/adolescence. Comorbid attention-deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder, depressive, phobia and panic symptoms/syndromes comprised the selected indicators. The resultant classes were characterized by psychosocial correlates. RESULTS: In LCA, four latent classes provided the best fit to the data. We identified two male-related classes. The first class exhibited both ADHD and depression. The second class comprised males with only depression. Class three was a female-related class depicting obsessive thoughts/compulsive acts, phobias and panic attacks. This class manifested high psychosocial impairment. Class four had a balanced sex proportion and comorbid symptoms/syndromes such as phobias and panic attacks. The complementary occurrence of comorbid obsessive thoughts/compulsive acts and ADHD impulsivity was remarkable. CONCLUSIONS: To the best of our knowledge, this is the first study applying LCA to community data of GTS symptoms/tic disorder-affected persons. Our findings support the utility of differentiating GTS/tic disorder subphenotypes on the basis of comorbid syndromes.

Risk factors of latent tuberculosis infection among asylum-seekers recently arrived in Switzerland : A pilot study in Vaud county

Background: Asylum seekers may have a higher rate of latenttuberculosis infection (LTBI) than resident populations in Westerncountries. LTBI can be detected by an Interferon Gamma ReleaseAssay (IGRA). Screening asylum seekers at highest risk for LTBI orfuture tuberculosis by IGRA could be considered. The aims of this pilotstudy were to assess the prevalence and the risk factors of LTBI amonga group of asylum seekers recently arrived in Switzerland.Methods: A prospective cross-sectional study was performed amongadult asylum seekers, staying in two migrant centers of the Vaud county,Switzerland, after a first screening for active tuberculosis at the border.The participants were offered IGRA screening using T-SPOT.TB andwere questioned about risk factors associated with LTBI. Migrants with apositive test had a chest radiograph and a medical examination. Thosewith active tuberculosis were excluded and were treated. The migrantswith LTBI received a preventive treatment, if indicated. The risk factorswere analyzed by univariate and multivariate logistical regression.Results: Among 788 migrants recently arrived, 639 were adults, 393agreed to be screened (61.50%) and 98 of them had a positive T-SPOT.TB (24.93%) of which 5 (5.1%) had an active tuberculosis (previouslynot detected at the border), and 2 had already been treated for activetuberculosis. In univariate analysis, the major risk factors associatedwith LTBI were country of origin and travel conditions. Compared withmigrants from Balkanic countries, migrants from Africa had an OR forLTBI of 3.68, migrants from Asia an OR of 4.3 and migrants fromFormer Soviet Union an OR of 4.5. Migrants who crossed severalborders before arriving in Switzerland had an OR of LTBI of 2.49compared with migrants who came directly from the home country.Age, cough and prior exposure to tuberculosis had a non-significantinfluence on the rate of test positivity. In multivariate analysis, thecombination of country of origin, travel conditions, age, cough andexposure to tuberculosis resulted in a score with optimal predictivevalue (Roc = 81%).Conclusions: Asylum seekers recently arrived in Vaud county had ahigh prevalence of LTBI and active tuberculosis. The major risk factorswere country of origin and travel conditions. Selecting for screening byIGRA the asylum seekers with the highest risk factors seems possible.

Validation de la version française de l'échelle de contrôle de Levenson (IPC), influence de variables démographiques et de la personnalité

We have examined the internal validity of the Levenson's locus of control scales (IPC, Internal, Powerful others and Chances), translated by Loas et al. (1994). The impact of different demographic variables on the Levenson's locus of control scales was assessed. After, we studied the relation between the IPC scales and the NEO PI R, personality inventory that measures the big five. A large sample (n=200) of subjects of different age, gender and profession and a sample of Swiss students (n=161) responding anonymously were used. The reliability of the IPC scale is acceptable. The analyses of the impact of the demographic variables show that gender and level of education have an influence on the I (intern) scale. Age, gender, level of education and profession have an impact on the P (powerful others) scale. The analyses of the relationship between locus of control and personality showed that there was a negative correlation between I (intern) and Neuroticism and a positive correlation between I and Extraversion and Consciousness. The P (powerful others) scale correlate positively with Neuroticism and negatively with Openness and Agreability. The C scale (chance) correlate positively with Neuroticism. Our study also gives the researchers and the practitioner a reference score table according to the gender, the age, the level of education and the profession.

How to Measure Scope Variables when no Metrics Exist : Application to Landscape Quality Measurement and Hedonic Price Evaluation

Landscape is an example of a non-market good where no metrics exist to measure its quality. The paper proposes an original methodology to nevertheless estimate scope variables in those circumstances, allowing then to better test if people's willingnesstopay for such good is sensitive to the scope. The methodology is based on techniques developed in the context of multicriteria decision analysis. It is applied to assess the quality of the landscape of several Swiss alpine resorts. This assessment is then used as an explanatory variable in a hedonic price function to explain the rent of apartments and to derive an implicit price of the landscape quality.

Social meets molecular: Combining phylogenetic and latent class analyses to understand HIV-1 transmission in Switzerland.

Switzerland has a complex human immunodeficiency virus (HIV) epidemic involving several populations. We examined transmission of HIV type 1 (HIV-1) in a national cohort study. Latent class analysis was used to identify socioeconomic and behavioral groups among 6,027 patients enrolled in the Swiss HIV Cohort Study between 2000 and 2011. Phylogenetic analysis of sequence data, available for 4,013 patients, was used to identify transmission clusters. Concordance between sociobehavioral groups and transmission clusters was assessed in correlation and multiple correspondence analyses. A total of 2,696 patients were infected with subtype B, 203 with subtype C, 196 with subtype A, and 733 with recombinant subtypes (mainly CRF02_AG and CRF01_AE). Latent class analysis identified 8 patient groups. Most transmission clusters of subtype B were shared between groups of gay men (groups 1-3) or between the heterosexual groups "heterosexual people of lower socioeconomic position" (group 4) and "injection drug users" (group 8). Clusters linking homosexual and heterosexual groups were associated with "older heterosexual and gay people on welfare" (group 5). "Migrant women in heterosexual partnerships" (group 6) and "heterosexual migrants on welfare" (group 7) shared non-B clusters with groups 4 and 5. Combining approaches from social and molecular epidemiology can provide insights into HIV-1 transmission and inform the design of prevention strategies.