881 resultados para Geographic Regression Discontinuity


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Our mental representation of the world is far from objective. For example, western Canadians estimate the locations of North American cities to be too far to the west. This bias could be due to a reference point effect, in which people estimate more space between places close to them than far from them, or to representational pseudoneglect, in which neurologically intact individuals favor the left side of space when asked to image a scene.We tested whether either or both of these biases influence the geographic world representations of neurologically intact young adults from Edmonton and Ottawa, which are in western and eastern Canada, respectively. Individuals were asked to locate NorthAmerican cities on a two-dimensional grid. Both groups revealed effects of representational pseudoneglect in this novel paradigm, but they also each exhibited reference point effects. These results inform theories in both cognitive psychology and neuroscience.

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Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

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This is the final report of the of IowAccess Project 8, which designed and implemented a geospatial data infrastructure for Iowa, including a formalized coordination body, a coordination staff, and enhanced data clearing house, and a statewide GIS training and education effort.

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The relationship between hypoxic stress, autophagy, and specific cell-mediated cytotoxicity remains unknown. This study shows that hypoxia-induced resistance of lung tumor to cytolytic T lymphocyte (CTL)-mediated lysis is associated with autophagy induction in target cells. In turn, this correlates with STAT3 phosphorylation on tyrosine 705 residue (pSTAT3) and HIF-1α accumulation. Inhibition of autophagy by siRNA targeting of either beclin1 or Atg5 resulted in impairment of pSTAT3 and restoration of hypoxic tumor cell susceptibility to CTL-mediated lysis. Furthermore, inhibition of pSTAT3 in hypoxic Atg5 or beclin1-targeted tumor cells was found to be associated with the inhibition Src kinase (pSrc). Autophagy-induced pSTAT3 and pSrc regulation seemed to involve the ubiquitin proteasome system and p62/SQSTM1. In vivo experiments using B16-F10 melanoma tumor cells indicated that depletion of beclin1 resulted in an inhibition of B16-F10 tumor growth and increased tumor apoptosis. Moreover, in vivo inhibition of autophagy by hydroxychloroquine in B16-F10 tumor-bearing mice and mice vaccinated with tyrosinase-related protein-2 peptide dramatically increased tumor growth inhibition. Collectively, this study establishes a novel functional link between hypoxia-induced autophagy and the regulation of antigen-specific T-cell lysis and points to a major role of autophagy in the control of in vivo tumor growth.

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Drainage-basin and channel-geometry multiple-regression equations are presented for estimating design-flood discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at stream sites on rural, unregulated streams in Iowa. Design-flood discharge estimates determined by Pearson Type-III analyses using data collected through the 1990 water year are reported for the 188 streamflow-gaging stations used in either the drainage-basin or channel-geometry regression analyses. Ordinary least-squares multiple-regression techniques were used to identify selected drainage-basin and channel-geometry regions. Weighted least-squares multiple-regression techniques, which account for differences in the variance of flows at different gaging stations and for variable lengths in station records, were used to estimate the regression parameters. Statewide drainage-basin equations were developed from analyses of 164 streamflow-gaging stations. Drainage-basin characteristics were quantified using a geographic-information-system (GIS) procedure to process topographic maps and digital cartographic data. The significant characteristics identified for the drainage-basin equations included contributing drainage area, relative relief, drainage frequency, and 2-year, 24-hour precipitation intensity. The average standard errors of prediction for the drainage-basin equations ranged from 38.6% to 50.2%. The GIS procedure expanded the capability to quantitatively relate drainage-basin characteristics to the magnitude and frequency of floods for stream sites in Iowa and provides a flood-estimation method that is independent of hydrologic regionalization. Statewide and regional channel-geometry regression equations were developed from analyses of 157 streamflow-gaging stations. Channel-geometry characteristics were measured on site and on topographic maps. Statewide and regional channel-geometry regression equations that are dependent on whether a stream has been channelized were developed on the basis of bankfull and active-channel characteristics. The significant channel-geometry characteristics identified for the statewide and regional regression equations included bankfull width and bankfull depth for natural channels unaffected by channelization, and active-channel width for stabilized channels affected by channelization. The average standard errors of prediction ranged from 41.0% to 68.4% for the statewide channel-geometry equations and from 30.3% to 70.0% for the regional channel-geometry equations. Procedures provided for applying the drainage-basin and channel-geometry regression equations depend on whether the design-flood discharge estimate is for a site on an ungaged stream, an ungaged site on a gaged stream, or a gaged site. When both a drainage-basin and a channel-geometry regression-equation estimate are available for a stream site, a procedure is presented for determining a weighted average of the two flood estimates.

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INTRODUCTION: Triple-negative breast cancers (TNBCs) are characterised by lack of expression of hormone receptors and epidermal growth factor receptor 2 (HER-2). As they frequently express epidermal growth factor receptors (EGFRs), anti-EGFR therapies are currently assessed for this breast cancer subtype as an alternative to treatments that target HER-2 or hormone receptors. Recently, EGFR-activating mutations have been reported in TNBC specimens in an East Asian population. Because variations in the frequency of EGFR-activating mutations in East Asians and other patients with lung cancer have been described, we evaluated the EGFR mutational profile in tumour samples from European patients with TNBC. METHODS: We selected from a DNA tumour bank 229 DNA samples isolated from frozen, histologically proven and macrodissected invasive TNBC specimens from European patients. PCR and high-resolution melting (HRM) analyses were used to detect mutations in exons 19 and 21 of EGFR. The results were then confirmed by bidirectional sequencing of all samples. RESULTS: HRM analysis allowed the detection of three EGFR exon 21 mutations, but no exon 19 mutations. There was 100% concordance between the HRM and sequencing results. The three patients with EGFR exon 21 abnormal HRM profiles harboured the rare R836R SNP, but no EGFR-activating mutation was identified. CONCLUSIONS: This study highlights variations in the prevalence of EGFR mutations in TNBC. These variations have crucial implications for the design of clinical trials involving anti-EGFR treatments in TNBC and for identifying the potential target population.

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When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

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Logistic regression is included into the analysis techniques which are valid for observationalmethodology. However, its presence at the heart of thismethodology, and more specifically in physical activity and sports studies, is scarce. With a view to highlighting the possibilities this technique offers within the scope of observational methodology applied to physical activity and sports, an application of the logistic regression model is presented. The model is applied in the context of an observational design which aims to determine, from the analysis of use of the playing area, which football discipline (7 a side football, 9 a side football or 11 a side football) is best adapted to the child"s possibilities. A multiple logistic regression model can provide an effective prognosis regarding the probability of a move being successful (reaching the opposing goal area) depending on the sector in which the move commenced and the football discipline which is being played.

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OBJECTIVE: To identify prevalence of and factors associated with intentional use of HIV risk reduction practices by men who have sex with men during anal intercourse with casual partners. METHODS: Cross-sectional survey pertaining to the Swiss HIV behavioral surveillance system, using an anonymous self-administered questionnaire in a self-selected sample of men who have sex with men (n = 2953). Multinomial regression was used to estimate factors associated with reporting either "no or inconsistent condom use" or "one or more risk reduction practices" over "consistent condom use." RESULTS: 57.2% reported anal intercourse with casual partner(s) over the last 12 months. Of these, 24.0% declared having used a risk reduction practice (73.8% of those who did not use condoms consistently). HIV-positive people were more likely to have done so. Most predictors were similarly associated to both regression categories. Four significant predictors were common to both regression categories: Internet partner seeking, age, age squared, and the interaction between HIV status positive and number of partners. The only association that differed markedly between the 2 regression categories was having a number of partners above median, significantly associated with the risk reduction category. CONCLUSIONS: Although condom use is the most frequent protection strategy in anal intercourse with casual partners, risk reduction practices are highly prevalent. However, there are no clear differences regarding predictors between risk reduction practices and inconsistent or no condom use. This suggests that risk reduction is an opportunistic response rather than a strategy per se.

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This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

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BACKGROUND: Hirschsprung's disease is a congenital gut motility disorder, characterised by the absence of the enteric ganglion cells along the distal gut. The aim of this study was to describe the epidemiology of Hirschsprung's disease, including additional congenital anomalies, total prevalence, trends, and association with maternal age. METHODS: Cases of Hirschsprung's disease delivered during 1980 to 2009 notified to 31 European Surveillance of Congenital Anomaly registers formed the population-based case-series. Prevalence rates and 95% confidence intervals were calculated as the number of cases per 10,000 births. Multilevel Poisson regression was performed to investigate trends in prevalence, geographical variation and the association with maternal age. RESULTS: There were 1,322 cases of Hirschsprung's disease among 12,146,210 births. The total prevalence was 1.09 (95% confidence interval, 1.03-1.15) per 10,000 births and there was a small but significant increase in prevalence over time (relative risk = 1.01; 95% credible interval, 1.00-1.02; p = 0.004). There was evidence of geographical heterogeneity in prevalence (p < 0.001). Excluding 146 (11.0%) cases with chromosomal anomalies or genetic syndromes, there were 1,176 cases (prevalence = 0.97; 95% confidence interval, 0.91-1.03 per 10,000 births), of which 137 (11.6%) had major structural anomalies. There was no evidence of a significant increased risk of Hirschsprung's disease in cases born to women aged ≥35 years compared with those aged 25 to 29 (relative risk = 1.09; 95% credible interval, 0.91-1.31; p = 0.355). CONCLUSION: This large population-based study found evidence of a small increasing trend in Hirschsprung's disease and differences in prevalence by geographic location. There was also no evidence of an association with maternal age. Birth Defects Research (Part A), 100:695-702, 2014. © 2014 Wiley Periodicals, Inc.

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BACKGROUND: We assessed the impact of a multicomponent worksite health promotion program for0 reducing cardiovascular risk factors (CVRF) with short intervention, adjusting for regression towards the mean (RTM) affecting such nonexperimental study without control group. METHODS: A cohort of 4,198 workers (aged 42 +/- 10 years, range 16-76 years, 27% women) were analyzed at 3.7-year interval and stratified by each CVRF risk category (low/medium/high blood pressure [BP], total cholesterol [TC], body mass index [BMI], and smoking) with RTM and secular trend adjustments. Intervention consisted of 15 min CVRF screening and individualized counseling by health professionals to medium- and high-risk individuals, with eventual physician referral. RESULTS: High-risk groups participants improved diastolic BP (-3.4 mm Hg [95%CI: -5.1, -1.7]) in 190 hypertensive patients, TC (-0.58 mmol/l [-0.71, -0.44]) in 693 hypercholesterolemic patients, and smoking (-3.1 cig/day [-3.9, -2.3]) in 808 smokers, while systolic BP changes reflected RTM. Low-risk individuals without counseling deteriorated TC and BMI. Body weight increased uniformly in all risk groups (+0.35 kg/year). CONCLUSIONS: In real-world conditions, short intervention program participants in high-risk groups for diastolic BP, TC, and smoking improved their CVRF, whereas low-risk TC and BMI groups deteriorated. Future programs may include specific advises to low-risk groups to maintain a favorable CVRF profile.

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A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.