55 research outputs found
Adaptively truncated maximum likehood regression with asymmetric errors
We assume that the error model belongs to a location-scale family of distributions. Since in the asymmetric case the mean response is very often the parameter of interest and scale is a main component of mean, we do not assume that scale is a nuisance parameter. First, we show how to convert an ordinary robust estimate for the usual model with symmetric errors to an estimate for the more general model with asymmetric errors. Then, in order to improve efficiency, we introduce the truncated maximum likelihood or TML-estimator. A TML-estimate is computed in three steps: first, an initial high breakdown point estimate is computed; then, observations that are unlikely under the estimated model are rejected; finally, the maximum likelihood estimate is computed with the retained observations. The rejection rule used in the second step is based on a cut-off parameter that can be tuned to attain the desired efficiency while maintaining the breakdown point of the initial estimator (e.g., 50%). Optionally, one can use a new adaptive cut-off that, asymptotically, does not reject any observation when the data are generated according to the model. Under the model, the influence function of this adaptive TML-estimator (or ATML-estimator) coincides with the influence function of the maximum likelihood estimator. The ATML-estimator is, therefore, fully efficient at the model; nevertheless, its breakdown point is not smaller than the breakdown point of the initial estimator. We evaluate the TML- and ATML-estimators for finite sample sizes with the help of simulations and discuss an example with real data. [authors]]]>
eng
oai:serval.unil.ch:BIB_EC87BF75EEE8
2022-05-07T01:29:32Z
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https://serval.unil.ch/notice/serval:BIB_EC87BF75EEE8
Organisational black holes
Hameri, A.-P.
info:eu-repo/semantics/conferenceObject
inproceedings
2001-04
IT Strategy Summit, Scottsdale, Arizona, USA
eng
oai:serval.unil.ch:BIB_EC87F7DA08C2
2022-05-07T01:29:32Z
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https://serval.unil.ch/notice/serval:BIB_EC87F7DA08C2
Monoclonal antibodies against recombinant-MAGE-1 protein identify a cross-reacting 72-kDa antigen which is co-expressed with MAGE-1 protein in melanoma cells
info:doi:10.1002/(sici)1097-0215(19960729)67:3<417::aid-ijc17>3.0.co;2-4
info:eu-repo/semantics/altIdentifier/doi/10.1002/(sici)1097-0215(19960729)67:3<417::aid-ijc17>3.0.co;2-4
info:eu-repo/semantics/altIdentifier/pmid/8707418
Carrel, S.
Schreyer, M.
Spagnoli, G.
Cerottini, J. C.
Rimoldi, D.
info:eu-repo/semantics/article
article
1996-07
International Journal of Cancer, vol. 67, no. 3, pp. 417-22
info:eu-repo/semantics/altIdentifier/pissn/0020-7136
<![CDATA[The MAGE-1 gene codes for tumor-associated peptides recognized by cytolytic T lymphocytes in association with MHC-class-1 molecules such as HLA-A1 and HLA-Cw16. In the course of a study aiming at the immunohistochemical detection of the MAGE-1 gene product in tumor samples, 2 mouse monoclonal antibodies (MAbs) directed against a full-length recombinant MAGE-1 fusion protein were found to react strongly not only with the 46-kDa MAGE-1 protein, but also with a 72-kDa product in immunoblots of lysates obtained from several MAGE-1-mRNA-positive melanoma cell lines. Pre-incubation of the antibodies with the recombinant MAGE-1 fusion protein abolished their reactivity both with MAGE-1 protein and with the 72-kDa product, thus confirming the occurrence of antigenic determinant(s) shared by the 2 proteins. The 72-kDa protein is not an alternative product of MAGE-1, since it was still detected in lysates of a MAGE-1 loss variant derived from a MAGE-1-positive melanoma cell line. Moreover, the 72-kDa protein does not appear to be a product of the other members of the MAGE gene family known to be expressed in tumors (such as MAGE-2, -3, -4 and -12). Interestingly, expression of the 72-kDa protein was found to be correlated with that of MAGE-1 protein. Thus, in 30 tumor cell lines analyzed by immunoblotting and RT-PCR, the 72-kDa protein was never detected in MAGE-1-mRNA-negative cell lines, while it was co-expressed with MAGE-1 protein in 12 out of 15 cell lines expressing MAGE-1. Furthermore, the 72-kDa protein was detected in lysates of human testis, the only normal tissue known to express MAGE-1. Finally, treatment of MAGE-1-mRNA-negative cell lines with 5-Aza-2'-deoxycytidine, a hypomethylating agent known to induce MAGE-1 expression, resulted in the expression of the 72-kDa protein. Taken collectively, these findings suggest that expression of the gene encoding the 72-kDa protein identified in this study through antigenic determinant(s) shared with MAGE-1 protein is regulated in a way similar to that of MAGE-1
Robust Estimation of the Generalized Loggamma Model. The R Package robustloggamma
robustloggamma is an R package for robust estimation and inference in the
generalized loggamma model. We briefly introduce the model, the estimation
procedures and the computational algorithms. Then, we illustrate the use of the
package with the help of a real data set.Comment: Accepted in Journal of Statistical Softwar
A Meta-Analysis of Acupuncture for Chronic Pain
Patel M (Route de Saint-Loup 4, 1290 Versoix, Switzerland), Gutzwiller F, Paccaud F and Marazzi A. A meta-analysis of acupuncture for chronic pain. International Journal of Epidemiology 1989, 18: 900-906. Results of 14 randomized controlled trials of acupuncture for chronic pain were pooled in a meta-analysis and analysed in three subgroups according to site of pain; and in two subgroups each according to type to trial, type of treatment, type of control, ‘blindness' of participating agents, trial size, and type of journal in which results were published. While few individual trials had statistically significant results, pooled results of many subgroups attained statistical significance in favour of acupuncture. Various potential sources of bias, including problems with blindness, precluded a conclusive finding although most results apparently favoured acupunctur
High hyperdiploid acute lymphoblastic leukemia in adults shows clonal heterogeneity and chromosomal instability at diagnosis and during the course of the disease
AIRO Breast Cancer Group Best Clinical Practice 2022 Update
Introduction: Breast cancer is the most common tumor in women and represents the leading cause of cancer death. Radiation therapy plays a key-role in the treatment of all breast cancer stages. Therefore, the adoption of evidence-based treatments is warranted, to ensure equity of access and standardization of care in clinical practice.Method: This national document on the highest evidence-based available data was developed and endorsed by the Italian Association of Radiation and Clinical Oncology (AIRO) Breast Cancer Group.We analyzed literature data regarding breast radiation therapy, using the SIGN (Scottish Intercollegiate Guidelines Network) methodology (www.sign.ac.uk). Updated findings from the literature were examined, including the highest levels of evidence (meta-analyses, randomized trials, and international guidelines) with a significant impact on clinical practice. The document deals with the role of radiation therapy in the treatment of primary breast cancer, local relapse, and metastatic disease, with focus on diagnosis, staging, local and systemic therapies, and follow up. Information is given on indications, techniques, total doses, and fractionations.Results: An extensive literature review from 2013 to 2021 was performed. The work was organized according to a general index of different topics and most chapters included individual questions and, when possible, synoptic and summary tables. Indications for radiation therapy in breast cancer were examined and integrated with other oncological treatments. A total of 50 questions were analyzed and answered.Four large areas of interest were investigated: (1) general strategy (multidisciplinary approach, contraindications, preliminary assessments, staging and management of patients with electronic devices); (2) systemic therapy (primary, adjuvant, in metastatic setting); (3) clinical aspects (invasive, non-invasive and micro-invasive carcinoma; particular situations such as young and elderly patients, breast cancer in males and cancer during pregnancy; follow up with possible acute and late toxicities; loco-regional relapse and metastatic disease); (4) technical aspects (radiation after conservative surgery or mastectomy, indications for boost, lymph node radiotherapy and partial breast irradiation).Appendixes about tumor bed boost and breast and lymph nodes contouring were implemented, including a dedicated web application. The scientific work was reviewed and validated by an expert group of breast cancer key-opinion leaders.Conclusions: Optimal breast cancer management requires a multidisciplinary approach sharing therapeutic strategies with the other involved specialists and the patient, within a coordinated and dedicated clinical path. In recent years, the high-level quality radiation therapy has shown a significant impact on local control and survival of breast cancer patients. Therefore, it is necessary to offer and guarantee accurate treatments according to the best standards of evidence-based medicine
Bootstrap tests for robust means of asymmetric distributions with unequal shapes
Bootstrap procedures for testing equality of robust means in the one-, two-, and multi-sample problems for asymmetrically distributed data with unequal shapes are described. The emphasis is on parametric procedures, but some results are provided for nonparametric procedures as well. In the parametric framework, it is assumed that a model with two parameters, shape and scale, can be used to approximatively describe the populations. Examples are contaminated Lognormal, Weibull, Gamma, and Pareto distributions. Robust estimators of the parameters are supposed to be available; the robust mean is then defined as the asymptotic value of the robust estimate of the model mean. In the nonparametric framework, the robust mean is the asymptotic value of some estimate that does not depend on a parametric model, e.g., a trimmed mean. A studentized test statistic is explored with the help of examples on simulated and real data. In order to estimate the null model, criteria for robust constrained model fitting, the constraint being the null hypothesis, are introduced and discussed. In the nonparametric case, a robust version of exponential tilting is provided. Parametric, semiparametric, and nonparametric bootstrap schemes for the computation of finite sample distributions are considered. The examples illustrate procedures that can be useful in practice. [Author]]]>
Statistical Distributions
eng
oai:serval.unil.ch:BIB_75B27B7BBF76
2022-08-13T01:23:13Z
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https://serval.unil.ch/notice/serval:BIB_75B27B7BBF76
Apport de la ponction de sang foetal au diagnostic prénatal
Vial, Y.
Hohlfeld, P.
info:eu-repo/semantics/article
article
1997
Médecine et hygiène, vol. 55, no. 2162, pp. 930-934
info:eu-repo/semantics/altIdentifier/pissn/0025-6749
<![CDATA[Le prélèvement de sang foetal, de par sa simplicité, son très faible risque et la rapidité d'obtention des résultats d'analyse est devenu la technique de choix pour tous les diagnostics prénatals pratiqués dons la deuxième moitié de la grossesse (caryotype, infection, bien-être foetal et maladies héréditaires). Son emploi a ouvert les portes de la thérapeutique foetale, permettant les transfusions intravasculaires in utero, et des traitements pharmacologiques spécifiques
Improving the Efficiency of Robust Estimators for the Generalized Linear Model
The distance constrained maximum likelihood procedure (DCML) optimally combines a robust estimator with the maximum likelihood estimator with the purpose of improving its small sample efficiency while preserving a good robustness level. It has been published for the linear model and is now extended to the GLM. Monte Carlo experiments are used to explore the performance of this extension in the Poisson regression case. Several published robust candidates for the DCML are compared; the modified conditional maximum likelihood estimator starting with a very robust minimum density power divergence estimator is selected as the best candidate. It is shown empirically that the DCML remarkably improves its small sample efficiency without loss of robustness. An example using real hospital length of stay data fitted by the negative binomial regression model is discussed
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