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Regression
Kinds of Regression Terms modified by Regression Selected AbstractsPARTIAL REGRESSION OF DUODENAL LESIONS OF INTESTINAL FOLLICULAR LYMPHOMA AFTER ANTIBIOTIC TREATMENTDIGESTIVE ENDOSCOPY, Issue 4 2010Tomonori Yaguchi A 51-year-old man was referred to our hospital because of duodenal lesions of lymphoma. Endoscopy showed multiple tiny smooth whitish granules in the second portion of the duodenum including the papilla of Vater. Biopsy specimens showed medium-sized centrocyte-like cells forming lymphoid follicles, and immunohistology showed positive staining for bcl-2 and CD10. A small bowel series showed multiple granular lesions extending from the second portion of the duodenum to the proximal jejunum and the proximal ileum. On the basis of these findings, the tumor was diagnosed as stage I follicular lymphoma (FL). Although the patient was negative for Helicobacter pylori, he underwent antibiotic treatment. The lesions improved 3 months after antibiotic treatment, but biopsy specimens showed residual lymphoma cells. The patient therefore received combination chemotherapy with rituximab. Endoscopy 4 months later showed regression of FL, and there was no evidence of recurrence during 3 years of follow up. The partial regression of duodenal lesions of intestinal FL may be due to the effect of antibiotic treatment. [source] PREDICTIVE VALUE OF ENDOSCOPY AND ENDOSCOPIC ULTRASONOGRAPHY FOR REGRESSION OF GASTRIC DIFFUSE LARGE B-CELL LYMPHOMAS AFTER HELICOBACTER PYLORI ERADICATIONDIGESTIVE ENDOSCOPY, Issue 4 2009Akira Tari Background:, Some gastric diffuse large B-cell lymphomas have been reported to regress completely after the successful eradication of Helicobacter pylori. The aim of this study was to investigate the clinical characteristics of gastric diffuse large B-cell lymphomas without any detectable mucosa-associated lymphoid tissue (MALT) lymphoma that went into complete remission after successful H. pylori eradication. Patients and Methods:, We examined the effect of H. pylori eradication in 15 H. pylori -positive gastric diffuse large B-cell lymphoma patients without any evidence of an associated MALT lymphoma (clinical stage I by the Lugano classification) by endoscopic examination including biopsies, endoscopic ultrasonography, computed tomography, and bone marrow aspiration. Results:,H. pylori eradication was successful in all the patients and complete remission was achieved in four patients whose clinical stage was I. By endoscopic examination, these gastric lesions appeared to be superficial. The depth by endoscopic ultrasonography was restricted to the mucosa in two patients and to the shallow portion of the submucosa in the other two patients. All four patients remained in complete remission for 7,100 months. Conclusion:, In gastric diffuse large B-cell lymphomas without a concomitant MALT lymphoma but associated with H. pylori infection, only superficial cases and lesions limited to the shallow portion of the submucosa regressed completely after successful H. pylori eradication. The endoscopic appearance and the rating of the depth of invasion by endosonography are both valuable for predicting the efficacy of H. pylori eradication in treating gastric diffuse large B-cell lymphomas. [source] INCORPORATING TECHNOLOGY DIFFUSION, FACTOR MOBILITY AND STRUCTURAL CHANGE INTO CROSS-REGION GROWTH REGRESSION: AN APPLICATION TO CHINA,JOURNAL OF REGIONAL SCIENCE, Issue 3 2010Laixiang Sun ABSTRACT This paper advocates a spatial dynamic model that introduces technology diffusion, factor mobility, and structural change into the cross-region growth regression. The spatial setting is derived from theory rather than spatial statistical tests. An application of this model to the study of cross-province growth in China over the period 1980,2005 indicates that incomes are spatially correlated, which highlights the significance of technology diffusion and factor mobility. Furthermore, the integration of neoclassical growth empirics and the structural change perspective of development economics provide a much improved account of interprovincial variations in income levels and economic growth. [source] OLS ESTIMATION AND THE t TEST REVISITED IN RANK-SIZE RULE REGRESSION,JOURNAL OF REGIONAL SCIENCE, Issue 4 2008Yoshihiko Nishiyama ABSTRACT The rank-size rule and Zipf's law for city sizes have been traditionally examined by means of OLS estimation and the t test. This paper studies the accurate and approximate properties of the OLS estimator and obtains the distribution of the t statistic under the assumption of Zipf's law (i.e., Pareto distribution). Indeed, we show that the t statistic explodes asymptotically even under the null, indicating that a mechanical application of the t test yields a serious type I error. To overcome this problem, critical regions of the t test are constructed to test the Zipf's law. Using these corrected critical regions, we can conclude that our results are in favor of the Zipf's law for many more countries than in the previous researches such as Rosen and Resnick (1980) or Soo (2005). By using the same database as that used in Soo (2005), we demonstrate that the Zipf law is rejected for only one of 24 countries under our test whereas it is rejected for 23 of 24 countries under the usual t test. We also propose a more efficient estimation procedure and provide empirical applications of the theory for some countries. [source] DIAGNOSING ORDER PLANNING PERFORMANCE AT A NAVY MAINTENANCE AND REPAIR ORGANIZATION, USING LOGISTIC REGRESSIONPRODUCTION AND OPERATIONS MANAGEMENT, Issue 4 2003JORIS M. KEIZERS We present a tool to diagnose the behavior of planners in complex production processes and to establish improvement potential for the delivery performance by changing the planning behavior. Scientific literature on production control offers valuable knowledge, but the complexity of real-life processes makes it impossible to directly apply this knowledge in real-life. The presented tool identifies possible deficiencies in the current way of managing the business processes, by matching the scientific knowledge on order planning with data reflecting the real-life processes via logistic regression. A case study at a maintenance organization illustrates the diagnosis tool. [source] HURLEY ON REASON-RESPONSIVENESS, REGRESSION, AND RESPONSIBILITYANALYTIC PHILOSOPHY, Issue 3 2005Kasper Lippert-Rasmussen First page of article [source] DELETE-2 AND DELETE-3 JACKKNIFE PROCEDURES FOR UNMASKING IN REGRESSIONAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 1 2010Michael A. Martin Summary Single-case deletion regression diagnostics have been used widely to discover unusual data points, but such approaches can fail in the presence of multiple unusual data points and as a result of masking. We propose a new approach to the use of single-case deletion diagnostics that involves applying these diagnostics to delete-2 and delete-3 jackknife replicates of the data, and considering the percentage of times among these replicates that points are flagged as unusual as an indicator of their influence. By considering replicates that exclude certain collections of points, subtle masking effects can be uncovered. [source] UPPER BOUNDS ON THE MINIMUM COVERAGE PROBABILITY OF CONFIDENCE INTERVALS IN REGRESSION AFTER MODEL SELECTIONAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 3 2009Paul Kabaila Summary We consider a linear regression model, with the parameter of interest a specified linear combination of the components of the regression parameter vector. We suppose that, as a first step, a data-based model selection (e.g. by preliminary hypothesis tests or minimizing the Akaike information criterion , AIC) is used to select a model. It is common statistical practice to then construct a confidence interval for the parameter of interest, based on the assumption that the selected model had been given to us,a priori. This assumption is false, and it can lead to a confidence interval with poor coverage properties. We provide an easily computed finite-sample upper bound (calculated by repeated numerical evaluation of a double integral) to the minimum coverage probability of this confidence interval. This bound applies for model selection by any of the following methods: minimum AIC, minimum Bayesian information criterion (BIC), maximum adjusted,R2, minimum Mallows' CP and,t -tests. The importance of this upper bound is that it delineates general categories of design matrices and model selection procedures for which this confidence interval has poor coverage properties. This upper bound is shown to be a finite-sample analogue of an earlier large-sample upper bound due to Kabaila and Leeb. [source] COVARIATE-ADJUSTED REGRESSION FOR LONGITUDINAL DATA INCORPORATING CORRELATION BETWEEN REPEATED MEASUREMENTSAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 3 2009Danh V. Nguyen Summary We propose an estimation method that incorporates the correlation/covariance structure between repeated measurements in covariate-adjusted regression models for distorted longitudinal data. In this distorted data setting, neither the longitudinal response nor (possibly time-varying) predictors are directly observable. The unobserved response and predictors are assumed to be distorted/contaminated by unknown functions of a common observable confounder. The proposed estimation methodology adjusts for the distortion effects both in estimation of the covariance structure and in the regression parameters using generalized least squares. The finite-sample performance of the proposed estimators is studied numerically by means of simulations. The consistency and convergence rates of the proposed estimators are also established. The proposed method is illustrated with an application to data from a longitudinal study of cognitive and social development in children. [source] SEMIPARAMETRIC REGRESSION AND GRAPHICAL MODELSAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 1 2009M. P. Wand Summary Semiparametric regression models that use spline basis functions with penalization have graphical model representations. This link is more powerful than previously established mixed model representations of semiparametric regression, as a larger class of models can be accommodated. Complications such as missingness and measurement error are more naturally handled within the graphical model architecture. Directed acyclic graphs, also known as Bayesian networks, play a prominent role. Graphical model-based Bayesian ,inference engines', such as bugs and vibes, facilitate fitting and inference. Underlying these are Markov chain Monte Carlo schemes and recent developments in variational approximation theory and methodology. [source] INVOLVEMENT OF PROLYLCARBOXYPEPTIDASE IN THE EFFECT OF RUTAECARPINE ON THE REGRESSION OF MESENTERIC ARTERY HYPERTROPHY IN RENOVASCULAR HYPERTENSIVE RATSCLINICAL AND EXPERIMENTAL PHARMACOLOGY AND PHYSIOLOGY, Issue 3 2009Xu-Ping Qin SUMMARY 1Previous studies indicate that rutaecarpine blocks increases in blood pressure and inhibits vascular hypertrophy in experimentally hypertensive rats. The aim of the present study was to determine whether the effects of rutaecarpine are related to activation of prolylcarboxypeptidase (PRCP). 2Renovascular hypertensive rats (Goldblatt two-kidney, one-clip (2K1C)) were developed using male Sprague-Dawley rats. Chronic treatment with rutaecarpine (10 or 40 mg/kg per day) or losartan (20 mg/kg per day) for 4 weeks to the hypertensive rats caused a sustained dose-dependent attenuation of increases in blood pressure, increased lumen diameter and decreased media thickness, which was accompanied by a similar reduction in the media cross-sectional area : lumen area ratio in mesenteric arteries compared with untreated hypertensive rats. 3Angiotensin (Ang) II expression was significantly increased in mesenteric arteries of hypertensive rats compared with sham-operated rats. No significant differences in plasma AngII levels were observed between untreated hypertensive and sham-operated rats. Hypertensive rats treated with high-dose rutaecarpine had significantly decreased Ang II levels in both the plasma and mesenteric arteries. 4Expression of PRCP protein or kallikrein mRNA was significantly inhibited in the right kidneys and mesenteric arteries of hypertensive rats. However, expression of PRCP protein and kallikrein mRNA was significantly increased after treatment with rutaecarpine or losartan (20 mg/kg per day). 5The data suggest that the repression of increases in systolic blood pressure and reversal of mesenteric artery remodelling by rutaecarpine may be related to increased expression of PRCP in the circulation and small arteries in 2K1C hypertensive rats. [source] HEDGING BY SEQUENTIAL REGRESSIONS REVISITEDMATHEMATICAL FINANCE, Issue 4 2009Almost 20 years ago Föllmer and Schweizer (1989) suggested a simple and influential scheme for the computation of hedging strategies in an incomplete market. Their approach of,local,risk minimization results in a sequence of one-period least squares regressions running recursively backward in time. In the meantime, there have been significant developments in the,global,risk minimization theory for semimartingale price processes. In this paper we revisit hedging by sequential regression in the context of global risk minimization, in the light of recent results obtained by ,erný and Kallsen (2007). A number of illustrative numerical examples are given. [source] RISK PREMIUM EFFECTS ON IMPLIED VOLATILITY REGRESSIONSTHE JOURNAL OF FINANCIAL RESEARCH, Issue 2 2010Leonidas S. Rompolis Abstract This article provides new insights into the sources of bias of option implied volatility to forecast its physical counterpart. We argue that this bias can be attributed to volatility risk premium effects. The latter are found to depend on high-order cumulants of the risk-neutral density. These cumulants capture the risk-averse behavior of investors in the stock and option markets for bearing the investment risk that is reflected in the deviations of the implied risk-neutral distribution from the normal distribution. We show that the bias of implied volatility to forecast its corresponding physical measure can be eliminated when the implied volatility regressions are adjusted for risk premium effects. The latter are captured mainly by the third-order risk-neutral cumulant. We also show that a substantial reduction of higher order risk-neutral cumulants biases to predict their corresponding physical cumulants is supported when adjustments for risk premium effects are made. [source] A NOTE ON CHARACTERIZATIONS OF DISTRIBUTIONS BY REGRESSIONS OF NON-ADJACENT GENERALIZED ORDER STATISTICSAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 1 2009Mariusz Bieniek Summary We investigate the problem of characterizations of distributions by regressions of generalized order statistics (GOSs) based on a continuous distribution function F. We show that F is uniquely determined if the regressions of a GOS given two other consecutive GOSs are known. [source] Gradient Estimation in Volume Data using 4D Linear RegressionCOMPUTER GRAPHICS FORUM, Issue 3 2000László Neumann In this paper a new gradient estimation method is presented which is based on linear regression. Previous contextual shading techniques try to fit an approximate function to a set of surface points in the neighborhood of a given voxel. Therefore a system of linear equations has to be solved using the computationally expensive Gaussian elimination. In contrast, our method approximates the density function itself in a local neighborhood with a 3D regression hyperplane. This approach also leads to a system of linear equations but we will show that it can be solved with an efficient convolution. Our method provides at each voxel location the normal vector and the translation of the regression hyperplane which are considered as a gradient and a filtered density value respectively. Therefore this technique can be used for surface smoothing and gradient estimation at the same time. [source] Using Logistic Regression to Analyze the Sensitivity of PVA Models: a Comparison of Methods Based on African Wild Dog ModelsCONSERVATION BIOLOGY, Issue 5 2001Paul C. Cross Standardized coefficients from the logistic regression analyses indicated that pup survival explained the most variability in the probability of extinction, regardless of whether or not the model incorporated density dependence. Adult survival and the standard deviation of pup survival were the next most important parameters in density-dependent simulations, whereas the severity and probability of catastrophe were more important during density-independent simulations. The inclusion of density dependence decreased the probability of extinction, but neither the abruptness nor the inclusion of density dependence were important model parameters. Results of both relative sensitivity analyses that altered each parameter by 10% of its range and life-stage-simulation analyses of deterministic matrix models supported the logistic regression results, indicating that pup survival and its variation were more important than other parameters. But both conventional sensitivity analysis of the stochastic model which changed each parameter by 10% of its mean value and elasticity analyses indicated that adult survival was more important than pup survival. We evaluated the advantages and disadvantages of using logistic regression to analyze the sensitivity of stochastic population viability models and conclude that it is a powerful method because it can address interactions among input parameters and can incorporate the range of parameter variability, although the standardized regression coefficients are not comparable between studies. Model structure, method of analysis, and parameter uncertainty affect the conclusions of sensitivity analyses. Therefore, rigorous model exploration and analysis should be conducted to understand model behavior and management implications. Resumen: Utilizamos la regresión logística como un método de análisis de sensibilidad par a un modelo de análisis de viabilidad poblacional de perros silvestres Africanos ( Lycaon pictus) y comparamos estos resultados con análisis de sensibilidad convencionales de modelos estocásticos y determinísticos. Coeficientes estandarizados de los análisis de regresión logística indicaron que la supervivencia de cachorros explicaba la mayor variabilidad en la probabilidad de extinción, independientemente de que el modelo incorporara la denso-dependencia. La supervivencia de adultos y la desviación estándar de la supervivencia de cachorros fueron los parámetros que siguieron en importancia en simulaciones de denso-dependencia, mientras que la severidad y la probabilidad de catástrofes fueron más importantes durante simulaciones denso-independientes. La inclusión de la denso dependencia disminuyó la probabilidad de extinción, pero ni la severidad ni la inclusión de denso-dependencia fueron parámetros importantes. Resultados de los análisis de sensibilidad relativa que alteraron cada parámetro en 10% de su rango y análisis de la simulación de etapas de vida de modelos matriciales determinísticos apoyaron los resultados de la regresión logística, indicando que la supervivencia de cachorros y su variación fueron más importantes que otros parámetros. Sin embargo, el análisis de sensibilidad convencional del modelo estocástico que cambiaron cada parámetro en 10% de su valor medio y el análisis de elasticidad indicaron que la supervivencia de adultos fue más importante que la supervivencia de cachorros. Evaluamos las ventajas y desventajas de utilizar la regresión logística para analizar la sensibilidad de modelos estocásticos de viabilidad poblacional y concluimos que es un método poderoso porque puede atender interacciones entre parámetros ingresados e incorporar el rango de variabilidad de parámetros, aunque los coeficientes de regresión estandarizada no son comparables entre estudios. La estructura del modelo, el método de análisis y la incertidumbre en los parámetros afectan las conclusiones del análisis de sensibilidad. Por lo tanto, se debe realizar una rigurosa exploración y análisis del modelo para entender su comportamiento y sus implicaciones en el manejo. [source] Spontaneous Regression in Merkel Cell Carcinoma: Report of Two Cases with a Description of Dermoscopic Features and Review of the LiteratureDERMATOLOGIC SURGERY, Issue 5 2010CRISTINA CIUDAD MD The authors have indicated no significant interest with commercial supporters. [source] Statistical Analysis of Surgical Dog-Ear RegressionDERMATOLOGIC SURGERY, Issue 8 2008KYUNG SUK LEE MD BACKGROUND Several methods have been developed to prevent or correct dog-ears. Most of these methods, however, result in prolonged scars and operative times. OBJECTIVE We observed dog-ears without correction to examine the regression of dog-ears with time. METHODS The study was performed on 43 cases of dog-ears in 26 patients. Linear regression analysis was performed to examine the correlation between various factors and the height of the dog-ears (%). We produced a regression equation to allow prediction of the height of the dog-ears (%). In addition, we estimated the initial height of the dog-ears that should be removed during surgery. RESULTS The height of dog-ears regressed with time, and this response was better in younger and female patients. It was predicted that the time taken for a dog-ear to reduce to 50% of its original height was 20.697 days; the median time at which dog-ears completely regressed was 132 days. The odds of regression of dog-ears with an initial height of ,8 mm was 4.667 times greater than that of larger dog-ears. CONCLUSIONS If the height of a dog-ear is ,8 mm, we recommend observation rather than immediate surgical removal. [source] Regression of Atypical Nevus: An Anecdotal Dermoscopic ObservationDERMATOLOGIC SURGERY, Issue 10 2006MARIA A PIZZICHETTA MD BACKGROUND Clark nevi (atypical melanocytic nevi) can be considered as risk markers and potential precursors of melanoma. The authors report on the morphologic changes of an atypical nevus by dermoscopic follow-up examination over a 7-year period. CASE REPORT A 43-year-old man had a brown macule on his back, sized 5 mm, with an irregular shape, clinically and dermoscopically diagnosed as an equivocal melanocytic lesion. Dermoscopically during the initial examination, a predominant reticular pattern with peripheral eccentric hyperpigmentation in the lower portion of the lesion could be seen. After 7 months, the area of peripheral eccentric hyperpigmentation had regressed, and after 4.5 years the atypical pigment network had almost disappeared. After 7 years of follow-up, a diffuse area of hypopigmentation and a residual light brown pigmentation were detectable. The histopathologic diagnosis was consistent with an atypical junctional nevus with regression with features of a Clark nevus. CONCLUSION Based on our observation, even a dermoscopically atypical nevus may undergo regression as documented by long-term dermoscopic follow-up. [source] Reduction rate of lymph node metastasis as a significant prognostic factor in esophageal cancer patients treated with neoadjuvant chemoradiation therapyDISEASES OF THE ESOPHAGUS, Issue 2 2007S. Aiko SUMMARY., Tumor regression is used widely as a measure of tumor response following radiation therapy or chemoradiation therapy (CRT). In cases of esophageal cancer, a different pattern of tumor shrinkage is often observed between primary tumors and metastatic lymph nodes (MLNs). Regression of MLNs surrounded by normal tissue may be a more direct measure of the response to CRT than regression of a primary tumor as exfoliative mechanical clearance does not participate in shrinkage of MLNs. In this study we evaluated the significance of the reduction rate (RR) of MLNs as a prognostic factor in esophageal cancer patients treated with neoadjuvant CRT. Forty-two patients with marked MLNs were selected from 93 patients with esophageal carcinoma who had received neoadjuvant CRT. The RRs of the primary tumor and the MLNs were calculated from computed tomography scans. In 20 patients, surgical resection was carried out following CRT. Univariate analysis was used to determine which of the following variables were related to survival: size of the primary tumor and MLNs; RRs of both lesions; degree of lymph node (LN) metastasis; clinical stage; and surgical resection. Multivariate analysis was then performed to assess the prognostic relevance of each variable. The primary tumor was larger than the MLNs in 69% of patients before CRT and in 40% of patients after CRT. In 79% of the patients, the RR of the primary tumor was greater than the RR of the MLNs. The results of the univariate analyses showed that a high RR of the MLNs and surgical resection after CRT were associated with significantly improved survival. The multivariate analysis demonstrated that the RR of MLNs had the strongest influence on survival. The RR of LN metastasis should be evaluated as an important prognostic predictor in patients with marked LN metastasis of esophageal cancer treated with CRT. [source] Nonparametric Censored and Truncated RegressionECONOMETRICA, Issue 2 2002Arthur Lewbel First page of article [source] Simultaneous Quantitative Determination of Cadmium, Lead, and Copper on Carbon-Ink Screen-Printed Electrodes by Differential Pulse Anodic Stripping Voltammetry and Partial Least Squares RegressionELECTROANALYSIS, Issue 23 2008Michael Cauchi Abstract Water is a vital commodity for every living entity on the planet. However, water resources are threatened by various sources of contamination from pesticides, hydrocarbons and heavy metals. This has resulted in the development of concepts and technologies to create a basis for provision of safe and high quality drinking water. This paper focuses on the simultaneous quantitative determination of three common contaminants, the heavy metals cadmium, lead and copper. Multivariate calibration was applied to voltammograms acquired on in-house printed carbon-ink screen-printed electrodes by the highly sensitive electrochemical method of differential pulse anodic stripping voltammetry (DPASV). The statistically inspired modification of partial least squares (SIMPLS) algorithm was employed to effect the multivariate calibration. The application of data pretreatment techniques involving range-scaling, mean-centering, weighting of variables and the effects of peak realignment are also investigated. It was found that peak realignment in conjunction with weighting and SIMPLS led to the better overall root mean square error of prediction (RMSEP) value. This work represents significant progress in the development of multivariate calibration tools in conjunction with analytical techniques for water quality determination. It is the first time that multivariate calibration has been performed on DPASV voltammograms acquired on carbon-ink screen-printed electrodes. [source] Rules, Regression and the ,Background': Dreyfus, Heidegger and McDowellEUROPEAN JOURNAL OF PHILOSOPHY, Issue 3 2008Denis McManus First page of article [source] PHYLOGENETICALLY NESTED COMPARISONS FOR TESTING CORRELATES OF SPECIES RICHNESS: A SIMULATION STUDY OF CONTINUOUS VARIABLESEVOLUTION, Issue 1 2003NICK J. B. ISAAC Abstract., Explaining the uneven distribution of species among lineages is one of the oldest questions in evolution. Proposed correlations between biological traits and species diversity are routinely tested by making comparisons between phylogenetic sister clades. Several recent studies have used nested sister-clade comparisons to test hypotheses linking continuously varying traits, such as body size, with diversity. Evaluating the findings of these studies is complicated because they differ in the index of species richness difference used, the way in which trait differences were treated, and the statistical tests employed. In this paper, we use simulations to compare the performance of four species richness indices, two choices about the branch lengths used to estimate trait values for internal nodes and two statistical tests under a range of models of clade growth and character evolution. All four indices returned appropriate Type I error rates when the assumptions of the method were met and when branch lengths were set proportional to time. Only two of the indices were robust to the different evolutionary models and to different choices of branch lengths and statistical tests. These robust indices had comparable power under one nonnull scenario. Regression through the origin was consistently more powerful than the t -test, and the choice of branch lengths exerts a strong effect on both the validity and power. In the light of our simulations, we re-evaluate the findings of those who have previously used nested comparisons in the context of species richness. We provide a set of simple guidelines to maximize the performance of phylogenetically nested comparisons in tests of putative correlates of species richness. [source] An Examination of Clothing Issues and Physical Limitations in the Product Development ProcessFAMILY & CONSUMER SCIENCES RESEARCH JOURNAL, Issue 1 2010Katherine Carroll The purpose of this study was to explore physical limitations and clothing problems among working women with physical disabilities to determine whether types of physical limitations are linked to specific clothing problems. The sample included 117 working women with a variety of disabilities. Principle Components Factor Analysis and Multiple Regression were used to analyze the data. Three distinct factors emerged to represent clothing problems (called Design, Materials Performance, and Dressing) and four distinct factors emerged to represent physical limitations (called Limbs/Outer Extremities, Central Core/Torso, Central Nervous System, and Intellect, Vision and Hearing). Regression analysis showed that the physical limitations impact each of the three clothing factors. The study extends research by focusing on an underserved market segment and providing the apparel industry with a potential method of addressing the needs of that market. The study also contributes to interdisciplinary research by further developing an Inclusive Design model for apparel product development. [source] Uncertainty about estimating total returns of Atlantic salmon, Salmo salar to the Gander River, Newfoundland, Canada, evaluated using a fish counting fenceFISHERIES MANAGEMENT & ECOLOGY, Issue 1 2003M. F. O'Connell Abstract ,For a number of rivers in Newfoundland, Atlantic salmon, Salmo salar L., is managed in relation to river-specific conservation spawning requirements. One such river is the Gander River, where between 1989 and 1999, the escapement of Atlantic salmon, a major factor in assessing the status of stock, was determined using a fish counting fence. In 2000, the counting fence was discontinued and alternative means of calculating total returns were explored. Regression and simulation methods, using relationships between total returns and salmon counts at an upstream tributary during 1989,99, formed the basis for estimates of returns for 2000, and the uncertainty around estimates. The accuracy of methods is evaluated by retrospective comparisons with actual total returns between 1989 and 1999. Estimates of total returns deviated from the actual by as much as 50,60%, depending on the method. Management implications of the approach are discussed. [source] Geographically Weighted Discriminant AnalysisGEOGRAPHICAL ANALYSIS, Issue 4 2007Chris Brunsdon In this article, we propose a novel analysis technique for geographical data, Geographically Weighted Discriminant Analysis. This approach adapts the method of Geographically Weighted Regression (GWR), allowing the modeling and prediction of categorical response variables. As with GWR, the relationship between predictor and response variables may alter over space, and calibration is achieved using a moving kernel window approach. The methodology is outlined and is illustrated with an example analysis of voting patterns in the 2005 UK general election. The example shows that similar social conditions can lead to different voting outcomes in different parts of England and Wales. Also discussed are techniques for visualizing the results of the analysis and methods for choosing the extent of the moving kernel window. [source] Regional-scale spatial patterns of fire in relation to rainfall gradients in sub-tropical mountains, NW ArgentinaGLOBAL ECOLOGY, Issue 2 2001Héctor Ricardo Grau Abstract 1Spatial patterns of burns are described using Landsat TM images from the sub-tropical mountains of north-west Argentina, over a span of 6 degrees of latitude, and a precipitation range from 250 to 1300 mm/yr. Burns were discriminated easily from unburnt vegetation, mainly by using infrared spectral bands from images taken at the end of the fire season of 1986. 2Nineteen sampling units were defined on the basis of geographical proximity and relatively homogeneous rainfall as inferred from topography, and they were characterized in terms of percentage of burnt area and burn size distribution during one fire season. Regression and Correspondence Analysis were used to assess the relationship between rainfall and spatial descriptors of fire regime. 3Burnt size area was log-normally distributed with most fires in the small-size classes. Of a total of 643 burns, the five largest (more than 2000 hectares each) represented about 30% of the total burnt area. 4Percentage of burnt area, density of burns per unit area, and skewness of the burn-size frequency distribution showed a unimodal pattern along the rainfall gradient, peaking between 700 and 900 mm/yr. Mean and maximum burn size showed a negative but weak correlation with rainfall. The first axis of a Correspondence Analysis ordination of sampling units, on the basis of different descriptors of spatial patterns of fire, was significantly correlated with the rainfall of the sampling unit. 5The results suggest that climate is an important factor controlling fuel conditions and therefore fire regime at the spatial scale of this study, which includes different mountain ranges spanning , 700 km. [source] Comparing Safety Climate between Two Populations of Hospitals in the United StatesHEALTH SERVICES RESEARCH, Issue 5p1 2009Sara J. Singer Objective. To compare safety climate between diverse U.S. hospitals and Veterans Health Administration (VA) hospitals, and to explore the factors influencing climate in each setting. Data Sources. Primary data from surveys of hospital personnel; secondary data from the American Hospital Association's 2004 Annual Survey of Hospitals. Study Design. Cross-sectional study of 69 U.S. and 30 VA hospitals. Data Collection. For each sample, hierarchical linear models used safety-climate scores as the dependent variable and respondent and facility characteristics as independent variables. Regression-based Oaxaca,Blinder decomposition examined differences in effects of model characteristics on safety climate between the U.S. and VA samples. Principal Findings. The range in safety climate among U.S. and VA hospitals overlapped substantially. Characteristics of individuals influenced safety climate consistently across settings. Working in southern and urban facilities corresponded with worse safety climate among VA employees and better safety climate in the U.S. sample. Decomposition results predicted 1.4 percentage points better safety climate in U.S. than in VA hospitals: ,0.77 attributable to sample-characteristic differences and 2.2 due to differential effects of sample characteristics. Conclusions. Results suggest that safety climate is linked more to efforts of individual hospitals than to participation in a nationally integrated system or measured characteristics of workers and facilities. [source] Imputation of SF-12 Health Scores for Respondents with Partially Missing DataHEALTH SERVICES RESEARCH, Issue 3 2005Honghu Liu Objective. To create an efficient imputation algorithm for imputing the SF-12 physical component summary (PCS) and mental component summary (MCS) scores when patients have one to eleven SF-12 items missing. Study Setting. Primary data collection was performed between 1996 and 1998. Study Design. Multi-pattern regression was conducted to impute the scores using only available SF-12 items (simple model), and then supplemented by demographics, smoking status and comorbidity (enhanced model) to increase the accuracy. A cut point of missing SF-12 items was determined for using the simple or the enhanced model. The algorithm was validated through simulation. Data Collection. Thirty-thousand-three-hundred and eight patients from 63 physician groups were surveyed for a quality of care study in 1996, which collected the SF-12 and other information. The patients were classified as "chronic" patients if they reported that they had diabetes, heart disease, asthma/chronic obstructive pulmonary disease, or low back pain. A follow-up survey was conducted in 1998. Principal Findings. Thirty-one percent of the patients missed at least one SF-12 item. Means of variance of prediction and standard errors of the mean imputed scores increased with the number of missing SF-12 items. Correlations between the observed and the imputed scores derived from the enhanced models were consistently higher than those derived from the simple model and the increments were significant for patients with ,6 missing SF-12 items (p<.03). Conclusion. Missing SF-12 items are prevalent and lead to reduced analytical power. Regression-based multi-pattern imputation using the available SF-12 items is efficient and can produce good estimates of the scores. The enhancement from the additional patient information can significantly improve the accuracy of the imputed scores for patients with ,6 items missing, leading to estimated scores that are as accurate as that of patients with <6 missing items. [source] | ||||||||||||||||||||||||||||||||||||||||||||||||||||