Diagnostic profiles of acute abdominal pain with multinomial logistic regression
Directory of Open Access Journals (Sweden)
Ohmann, Christian
2007-07-01
Full Text Available Purpose: Application of multinomial logistic regression for diagnostic support of acute abdominal pain, a diagnostic problem with many differential diagnoses. Methods: The analysis is based on a prospective data base with 2280 patients with acute abdominal pain, characterized by 87 variables from history and clinical examination and 12 differential diagnoses. Associations between single variables from history and clinical examination and the final diagnoses were investigated with multinomial logistic regression. Results: Exemplarily, the results are presented for the variable rigidity. A statistical significant association was observed for generalized rigidity and the diagnoses appendicitis, bowel obstruction, pancreatitis, perforated ulcer, multiple and other diagnoses and for localized rigidity and appendicitis, diverticulitis, biliary disease and perforated ulcer. Diagnostic profiles were generated by summarizing the statistical significant associations. As an example the diagnostic profile of acute appendicitis is presented. Conclusions: Compared to alternative approaches (e.g. independent Bayes, loglinear model there are advantages for multinomial logistic regression to support complex differential diagnostic problems, provided potential traps are avoided (e.g. α-error, interpretation of odds ratio.
[Language regression to the mother tongue in polyglot patients with acute psychosis].
Heinemann, F; Assion, H J
1996-07-01
Three bilingual patients with schizophrenia are presented, who spoke almost exclusively in their native language during acute episodes of psychosis. Normal use of the foreign language, German, was again possible after remission of the acute symptoms. This phenomenon of regression is similar to speech disorders in patients with aphasia and is discussed with reference to recent biological findings. PMID:8927199
Quantin, C.; Billard, L.; Touati, M.; Andreu, N; Cottin, Y; Zeller, M.; Afonso, F.; Battaglia, G.; Seck, D.; Le Teuff, G; Diday, E.
2011-01-01
International audience Cardiologists are interested in determining whether the type of hospital pathway followed by a patient is predictive of survival. The study objective was to determine whether accounting for hospital pathways in the selection of prognostic factors of one-year survival after acute myocardial infarction AMI provided a more informative analysis than that obtained by the use of a standard regression tree analysis CART method . Information on AMI was collected for 1095 hos...
Directory of Open Access Journals (Sweden)
C. Quantin
2011-01-01
Full Text Available Cardiologists are interested in determining whether the type of hospital pathway followed by a patient is predictive of survival. The study objective was to determine whether accounting for hospital pathways in the selection of prognostic factors of one-year survival after acute myocardial infarction (AMI provided a more informative analysis than that obtained by the use of a standard regression tree analysis (CART method. Information on AMI was collected for 1095 hospitalized patients over an 18-month period. The construction of pathways followed by patients produced symbolic-valued observations requiring a symbolic regression tree analysis. This analysis was compared with the standard CART analysis using patients as statistical units described by standard data selected TIMI score as the primary predictor variable. For the 1011 (84, resp. patients with a lower (higher TIMI score, the pathway variable did not appear as a diagnostic variable until the third (second stage of the tree construction. For an ecological analysis, again TIMI score was the first predictor variable. However, in a symbolic regression tree analysis using hospital pathways as statistical units, the type of pathway followed was the key predictor variable, showing in particular that pathways involving early admission to cardiology units produced high one-year survival rates.
Institute of Scientific and Technical Information of China (English)
QIN GuoYou; ZHU ZhongYi
2009-01-01
In this paper, we study the local asymptotic behavior of the regression spline estimator in the framework of marginal semiparametric model. Similarly to Zhu, Fung and He (2008), we give explicit expression for the asymptotic bias of regression spline estimator for nonparametric function f. Our results also show that the asymptotic bias of the regression spline estimator does not depend on the working covariance matrix, which distinguishes the regression splines from the smoothing splines and the seemingly unrelated kernel. To understand the local bias result of the regression spline estimator, we show that the regression spline estimator can be obtained iteratively by applying the standard weighted least squares regression spline estimator to pseudo-observations. At each iteration, the bias of the estimator is unchanged and only the variance is updated.
Institute of Scientific and Technical Information of China (English)
2009-01-01
In this paper, we study the local asymptotic behavior of the regression spline estimator in the framework of marginal semiparametric model. Similarly to Zhu, Fung and He (2008), we give explicit expression for the asymptotic bias of regression spline estimator for nonparametric function f. Our results also show that the asymptotic bias of the regression spline estimator does not depend on the working covariance matrix, which distinguishes the regression splines from the smoothing splines and the seemingly unrelated kernel. To understand the local bias result of the regression spline estimator, we show that the regression spline estimator can be obtained iteratively by applying the standard weighted least squares regression spline estimator to pseudo-observations. At each iteration, the bias of the estimator is unchanged and only the variance is updated.
DEFF Research Database (Denmark)
Mogensen, T; Scott, N B; Lund, Claus;
1988-01-01
The purpose of this study was to investigate whether regression of sensory analgesia during constant epidural bupivacaine infusion was different in postoperative patients with acute pain than in patients with chronic nonsurgical pain. Sensory levels of analgesia (to pinprick) and pain (on a five-...
International Nuclear Information System (INIS)
Purpose: Diagnosis of right ventricular dysfunction in patients with acute pulmonary embolism (PE) is known to be associated with increased risk of mortality. The aim of the study was to calculate a logistic regression model for reliable identification of right ventricular dysfunction (RVD) in patients diagnosed with computed tomography pulmonary angiography. Material and methods: Ninety-seven consecutive patients with acute pulmonary embolism were divided into groups with and without RVD basing upon echocardiographic measurement of pulmonary artery systolic pressure (PASP). PE severity was graded with the pulmonary obstruction score. CT measurements of heart chambers and mediastinal vessels were performed; position of interventricular septum and presence of contrast reflux into the inferior vena cava were also recorded. The logistic regression model was prepared by means of stepwise logistic regression. Results: Among the used parameters, the final model consisted of pulmonary obstruction score, short axis diameter of right ventricle and diameter of inferior vena cava. The calculated model is characterized by 79% sensitivity and 81% specificity, and its performance was significantly better than single CT-based measurements. Conclusion: Logistic regression model identifies RVD significantly better, than single CT-based measurements
Regression rate behaviors of HTPB-based propellant combinations for hybrid rocket motor
Sun, Xingliang; Tian, Hui; Li, Yuelong; Yu, Nanjia; Cai, Guobiao
2016-02-01
The purpose of this paper is to characterize the regression rate behavior of hybrid rocket motor propellant combinations, using hydrogen peroxide (HP), gaseous oxygen (GOX), nitrous oxide (N2O) as the oxidizer and hydroxyl-terminated poly-butadiene (HTPB) as the based fuel. In order to complete this research by experiment and simulation, a hybrid rocket motor test system and a numerical simulation model are established. Series of hybrid rocket motor firing tests are conducted burning different propellant combinations, and several of those are used as references for numerical simulations. The numerical simulation model is developed by combining the Navies-Stokes equations with the turbulence model, one-step global reaction model, and solid-gas coupling model. The distribution of regression rate along the axis is determined by applying simulation mode to predict the combustion process and heat transfer inside the hybrid rocket motor. The time-space averaged regression rate has a good agreement between the numerical value and experimental data. The results indicate that the N2O/HTPB and GOX/HTPB propellant combinations have a higher regression rate, since the enhancement effect of latter is significant due to its higher flame temperature. Furthermore, the containing of aluminum (Al) and/or ammonium perchlorate(AP) in the grain does enhance the regression rate, mainly due to the more energy released inside the chamber and heat feedback to the grain surface by the aluminum combustion.
Welten, Carlijn C M; Koeter, Maarten W J; Wohlfarth, Tamar D; Storosum, Jitschak G; van den Brink, Wim; Gispen-de Wied, Christine C; Leufkens, Hubert G M; Denys, Damiaan A J P
2016-02-01
Patients having an acute manic episode of bipolar disorder often lack insight into their condition. Because little is known about the possible effect of insight on treatment efficacy, we examined whether insight at the start of treatment affects the efficacy of antipsychotic treatment in patients with acute mania. We used individual patient data from 7 randomized, double-blind, placebo-controlled registration studies of 4 antipsychotics in patients with acute mania (N = 1904). Insight was measured with item 11 of the Young Mania Rating Scale (YMRS) at baseline and study endpoint 3 weeks later. Treatment outcome was defined by (a) mean change score, (b) response defined as 50% or more improvement on YMRS, and (c) remission defined as YMRS score less than 8 at study endpoint. We used multilevel mixed effect linear (or logistic) regression analyses of individual patient data to assess the interaction between baseline insight and treatment outcomes. At treatment initiation, 1207 (63.5%) patients had impaired or no insight into their condition. Level of insight significantly modified the efficacy of treatment by mean change score (P = 0.039), response rate (P = 0.033), and remission rate (P = 0.043), with greater improvement in patients with more impaired insight. We therefore recommend that patients experiencing acute mania should be treated immediately and not be delayed until patients regain insight.
Welten, Carlijn C M; Koeter, Maarten W J; Wohlfarth, Tamar D; Storosum, Jitschak G; van den Brink, Wim; Gispen-de Wied, Christine C; Leufkens, Hubert G M; Denys, Damiaan A J P
2016-02-01
Patients having an acute manic episode of bipolar disorder often lack insight into their condition. Because little is known about the possible effect of insight on treatment efficacy, we examined whether insight at the start of treatment affects the efficacy of antipsychotic treatment in patients with acute mania. We used individual patient data from 7 randomized, double-blind, placebo-controlled registration studies of 4 antipsychotics in patients with acute mania (N = 1904). Insight was measured with item 11 of the Young Mania Rating Scale (YMRS) at baseline and study endpoint 3 weeks later. Treatment outcome was defined by (a) mean change score, (b) response defined as 50% or more improvement on YMRS, and (c) remission defined as YMRS score less than 8 at study endpoint. We used multilevel mixed effect linear (or logistic) regression analyses of individual patient data to assess the interaction between baseline insight and treatment outcomes. At treatment initiation, 1207 (63.5%) patients had impaired or no insight into their condition. Level of insight significantly modified the efficacy of treatment by mean change score (P = 0.039), response rate (P = 0.033), and remission rate (P = 0.043), with greater improvement in patients with more impaired insight. We therefore recommend that patients experiencing acute mania should be treated immediately and not be delayed until patients regain insight. PMID:26647231
DEFF Research Database (Denmark)
Mogensen, T; Scott, N B; Lund, Claus;
1988-01-01
The purpose of this study was to investigate whether regression of sensory analgesia during constant epidural bupivacaine infusion was different in postoperative patients with acute pain than in patients with chronic nonsurgical pain. Sensory levels of analgesia (to pinprick) and pain (on a five......-point scale) were assessed hourly for 16 hours during continuous epidural infusion of 0.5% plain bupivacaine (8 ml/hr) in 12 patients with chronic nonsurgical pain and in 30 patients after major abdominal surgery performed under combined bupivacaine and halothane--N2O general anesthesia. No opiates were given.......01). Mean duration of sensory blockade was significantly longer (P less than 0.005) in the patients with chronic pain than in surgical patients (13.1 +/- 1.2 and 8.5 +/- 0.7 hours, respectively). Thus, surgical injury hastens regression of sensory analgesia during continuous epidural bupivacaine infusion...
Cohen, Ira L; Liu, Xudong; Hudson, Melissa; Gillis, Jennifer; Cavalari, Rachel N S; Romanczyk, Raymond G; Karmel, Bernard Z; Gardner, Judith M
2016-09-01
In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80 %, generalized to an independent validation set, and generalized across age groups and sites, and agreed well with ADOS classifications. Parent PDDBIs yielded better results than teacher PDDBIs but, when CART predictions agreed across informants, sensitivity increased. Results also revealed three subtypes of ASD: minimally verbal, verbal, and atypical; and two, relatively common subtypes of non-ASD children: social pragmatic problems and good social skills. These subgroups corresponded to differences in behavior profiles and associated bio-medical findings. PMID:27318809
Maternal heavy alcohol use and toddler behavior problems: a fixed effects regression analysis.
Knudsen, Ann Kristin; Ystrom, Eivind; Skogen, Jens Christoffer; Torgersen, Leila
2015-10-01
Using data from the longitudinal Norwegian Mother and Child Cohort Study, the aims of the current study were to examine associations between postnatal maternal heavy alcohol use and toddler behavior problems, taking both observed and unobserved confounding factors into account by employing fixed effects regression models. Postnatal maternal heavy alcohol use (defined as drinking alcohol 4 or more times a week, or drinking 7 units or more per alcohol use episode) and toddler internalizing and externalizing behavior problems were assessed when the toddlers were aged 18 and 36 months. Maternal psychopathology, civil status and negative life events last year were included as time-variant covariates. Maternal heavy alcohol use was associated with toddler internalizing and externalizing behavior problems (p < 0.001) in the population when examined with generalized estimating equation models. The associations disappeared when observed and unobserved sources of confounding were taken into account in the fixed effects models [(p = 0.909 for externalizing behaviors (b = 0.002, SE = 0.021), p = 0.928 for internalizing behaviors (b = 0.002, SE = 0.023)], with an even further reduction of the estimates with the inclusion of time-variant confounders. No causal effect was found between postnatal maternal heavy alcohol use and toddler behavior problems. Increased levels of behavior problems among toddlers of heavy drinking mothers should therefore be attributed to other adverse characteristics associated with these mothers, toddlers and families. This should be taken into account when interventions aimed at at-risk families identified by maternal heavy alcohol use are planned and conducted.
Yu, Rongqin; Geddes, John R; Fazel, Seena
2012-10-01
The risk of antisocial outcomes in individuals with personality disorder (PD) remains uncertain. The authors synthesize the current evidence on the risks of antisocial behavior, violence, and repeat offending in PD, and they explore sources of heterogeneity in risk estimates through a systematic review and meta-regression analysis of observational studies comparing antisocial outcomes in personality disordered individuals with controls groups. Fourteen studies examined risk of antisocial and violent behavior in 10,007 individuals with PD, compared with over 12 million general population controls. There was a substantially increased risk of violent outcomes in studies with all PDs (random-effects pooled odds ratio [OR] = 3.0, 95% CI = 2.6 to 3.5). Meta-regression revealed that antisocial PD and gender were associated with higher risks (p = .01 and .07, respectively). The odds of all antisocial outcomes were also elevated. Twenty-five studies reported the risk of repeat offending in PD compared with other offenders. The risk of a repeat offense was also increased (fixed-effects pooled OR = 2.4, 95% CI = 2.2 to 2.7) in offenders with PD. The authors conclude that although PD is associated with antisocial outcomes and repeat offending, the risk appears to differ by PD category, gender, and whether individuals are offenders or not.
The limiting behavior of the estimated parameters in a misspecified random field regression model
DEFF Research Database (Denmark)
Dahl, Christian Møller; Qin, Yu
This paper examines the limiting properties of the estimated parameters in the random field regression model recently proposed by Hamilton (Econometrica, 2001). Though the model is parametric, it enjoys the flexibility of the nonparametric approach since it can approximate a large collection...... of nonlinear functions and it has the added advantage that there is no "curse of dimensionality."Contrary to existing literature on the asymptotic properties of the estimated parameters in random field models our results do not require that the explanatory variables are sampled on a grid. However......, as a consequence the random field model specification introduces non-stationarity and non-ergodicity in the misspecified model and it becomes non-trivial, relative to the existing literature, to establish the limiting behavior of the estimated parameters. The asymptotic results are obtained by applying some...
Fluoxetine and diazepam acutely modulate stress induced-behavior.
Giacomini, Ana Cristina V V; Abreu, Murilo S; Giacomini, Luidia V; Siebel, Anna M; Zimerman, Fernanda F; Rambo, Cassiano L; Mocelin, Ricieri; Bonan, Carla D; Piato, Angelo L; Barcellos, Leonardo J G
2016-01-01
Drug residue contamination in aquatic ecosystems has been studied extensively, but the behavioral effects exerted by the presence of these drugs are not well known. Here, we investigated the effects of acute stress on anxiety, memory, social interaction, and aggressiveness in zebrafish exposed to fluoxetine and diazepam at concentrations that disrupt the hypothalamic-pituitary-interrenal (HPI) axis. Stress increased the locomotor activity and time spent in the bottom area of the tank (novel tank). Fluoxetine and diazepam prevented these behaviors. We also observed that stress and fluoxetine and diazepam exposures decreased social interaction. Stress also increased aggressive behavior, which was not reversed by fluoxetine or diazepam. These data suggest that the presence of these drugs in aquatic ecosystems causes significant behavioral alterations in fish. PMID:26403161
Energy Technology Data Exchange (ETDEWEB)
Wolff, Hendrik Andreas; Herrmann, Markus Karl Alfred; Hennies, Steffen; Rave-Fraenk, Margret; Hess, Clemens Friedrich; Christiansen, Hans [Dept. of Radiotherapy and Radiooncology, Univ. Medicine Goettingen (Germany); Gaedcke, Jochen; Liersch, Torsten [Dept. of Surgery, Univ. Medicine Goettingen (Germany); Jung, Klaus [Dept. of Medical Statistics, Univ. Medicine Goettingen (Germany); Hermann, Robert Michael [Dept. of Radiotherapy and Radiooncology, Univ. Medicine Goettingen (Germany); Dept. of Radiotherapy and Radiooncology, Aerztehaus am Diako, Bremen (Germany); Rothe, Hilka [Dept. of Pathology, Univ. Medicine Goettingen (Germany); Schirmer, Markus [Dept. of Clinical Pharmacology, Univ. Medicine Goettingen (Germany)
2010-01-15
Purpose: To test for a possible correlation between high-grade acute organ toxicity during preoperative radiochemotherapy and complete tumor regression after total mesorectal excision in multimodal treatment of locally advanced rectal cancer. Patients and Methods: From 2001 to 2008, 120 patients were treated. Preoperative treatment consisted of normofractionated radiotherapy at a total dose of 50.4 Gy, and either two cycles of 5-fluorouracil (5-FU) or two cycles of 5-FU and oxaliplatin. Toxicity during treatment was monitored weekly, and any toxicity CTC (Common Toxicity Criteria) {>=} grade 2 of enteritis, proctitis or cystitis was assessed as high-grade organ toxicity for later analysis. Complete histopathologic tumor regression (TRG4) was defined as the absence of any viable tumor cells. Results: A significant coherency between high-grade acute organ toxicity and complete histopathologic tumor regression was found, which was independent of other factors like the preoperative chemotherapy schedule. The probability of patients with acute organ toxicity {>=} grade 2 to achieve TRG4 after neoadjuvant treatment was more than three times higher than for patients without toxicity (odds ratio: 3.29, 95% confidence interval: [1.01, 10.96]). Conclusion: Acute organ toxicity during preoperative radiochemotherapy in rectal cancer could be an early predictor of treatment response in terms of complete tumor regression. Its possible impact on local control and survival is under further prospective evaluation by the authors' working group. (orig.)
Understanding prehospital delay behavior in acute myocardial infarction in women.
Waller, Cynthia G
2006-12-01
Studies demonstrate that acute myocardial infarction (AMI) mortality can be reduced if reperfusion therapy is initiated within 1 hour of AMI symptom onset. However, a considerable number of men and women arrive at the emergency department outside of the time frame for thrombolytic and angioplasty effectiveness. This is especially true for women who have been shown to delay longer than men due to their prehospital decision-making process utilized. With a mean total delay time greater than 4 hours, the time interval from symptom onset to transport activation to the hospital consumes the majority of the prehospital phase of emergency cardiac care. The health belief model, self-regulation model, theory of reasoned action, and theory of planned behavior have all been used to describe the prehospital decision-making process of both men and women with an AMI and the variables that impact that process. These models have identified the importance of symptom attribution to cardiac-related causes as a target variable for research and interventions related to care-seeking behavior. PMID:18340239
Acute behavioral toxicity of carbaryl and propoxur in adult rats.
Ruppert, P H; Cook, L L; Dean, K F; Reiter, L W
1983-04-01
Motor activity and neuromotor function were examined in adult CD rats exposed to either carbaryl or propoxur, and behavioral effects were compared with the time course of cholinesterase inhibition. Rats received an IP injection of either 0, 2, 4, 6 or 8 mg/kg propoxur or 0, 4, 8, 16 or 28 mg/kg carbaryl in corn oil 20 min before testing. All doses of propoxur reduced 2 hr activity in a figure-eight maze, and crossovers and rears in an open field. For carbaryl, dosages of 8, 16 and 28 mg/kg decreased maze activity whereas 16 and 28 mg/kg reduced open field activity. In order to determine the time course of effects, rats received a single IP injection of either corn oil, 2 mg/kg propoxur or 16 mg/kg carbaryl, and were tested for 5 min in a figure-eight maze either 15, 30, 60, 120 or 240 min post-injection. Immediately after testing, animals were sacrificed and total cholinesterase was measured. Maximum effects of propoxur and carbaryl on blood and brain cholinesterase and motor activity were seen within 15 min. Maze activity had returned to control levels within 30 and 60 min whereas cholinesterase levels remained depressed for 120 and 240 min for propoxur and carbaryl, respectively. These results indicate that both carbamates decrease motor activity, but behavioral recovery occurs prior to that of cholinesterase following acute exposure.
George, Steven Z.; Zeppieri, Giorgio; Cere, Anthony L.; Cere, Melissa R.; Borut, Michael S.; Hodges, Michael J.; Reed, Dalton M.; Valencia, Carolina; Robinson, Michael E.
2008-01-01
Psychological factors consistent with fear-avoidance models are associated with the development of chronic low back pain (LBP). As a result, graded activity (GA) and graded exposure (GX) have been suggested as behavioral treatment options. This clinical trial compared the effectiveness of treatment based classification (TBC) physical therapy alone, to TBC augmented with GA or GX for patients with acute and sub-acute LBP. Our primary hypothesis was that GX would be most effective for those wit...
The objective of this study was to investigate and model the behavior of Salmonella on different types of chicken meat during frozen and refrigerated storage. Portions (0.69 to 0.83 g) of chicken meat (breast, skin, or thigh) were inoculated with a single strain (ATCC 700408) of Salmonella Typhimur...
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals
Vu, Kevin; Li, Li; Rupp, Matthias; Chen, Brandon F; Khelif, Tarek; Müller, Klaus-Robert; Burke, Kieron
2015-01-01
Accurate approximations to density functionals have recently been obtained via machine learning (ML). By applying ML to a simple function of one variable without any random sampling, we extract the qualitative dependence of errors on hyperparameters. We find universal features of the behavior in extreme limits, including both very small and very large length scales, and the noise-free limit. We show how such features arise in ML models of density functionals.
Mahani, Mohamad Khayatzadeh; Chaloosi, Marzieh; Maragheh, Mohamad Ghanadi; Khanchi, Ali Reza; Afzali, Daryoush
2007-09-01
The oral acute in vivo toxicity of 32 amine and amide drugs was related to their structural-dependent properties. Genetic algorithm-partial least-squares and stepwise variable selection was applied to select of meaningful descriptors. Multiple linear regression (MLR), artificial neural network (ANN) and partial least square (PLS) models were created with selected descriptors. The predictive ability of all three models was evaluated and compared on a set of five drugs, which were not used in modeling steps. Average errors of 0.168, 0.169 and 0.259 were obtained for MLR, ANN and PLS, respectively.
Welten, Carlijn C M; Koeter, Maarten W J; Wohlfarth, Tamar D; Storosum, Jitschak G; van den Brink, Wim; Gispen-de Wied, Christine C; Leufkens, Hubert G M; Denys, D.
2016-01-01
Patients having an acute manic episode of bipolar disorder often lack insight into their condition. Because little is known about the possible effect of insight on treatment efficacy, we examined whether insight at the start of treatment affects the efficacy of antipsychotic treatment in patients wi
Directory of Open Access Journals (Sweden)
Naohisa Nakajima
2014-06-01
Conclusions: Additional LDL-C reduction with combination therapy tended to reduce more plaque regression compared to a statin alone in patients with ACS. In diabetic patients, further reduction of LDL-C was associated with a significantly greater reduction in PV.
Acute and Chronic Effects of Cocaine on the Spontaneous Behavior of Pigeons
Pinkston, Jonathan W.; Branch, Marc N.
2010-01-01
The present experiment examined the effects of acute and daily cocaine on spontaneous behavior patterns of pigeons. After determining the acute effects of a range of doses, 9 pigeons were divided into three groups that received one of three doses of cocaine daily, either 1.0, 3.0, or 10.0 mg/kg cocaine. Measures were taken of spontaneous…
Directory of Open Access Journals (Sweden)
Selma KARABAŞ
2012-06-01
Full Text Available The purpose of this study is to determine consumer behavior towards organic products in Samsun city center and to determine the factors affacting their preferences of organic products. The study was interviewed with 478 consumers living the city center of Samsun. According of the findings, ease of accesibility of organic products, spouse’s educational level, paying extra for the organic produce, aware of food health benefits, considering the harmful effects of conventional produce, having complete knowledge of organic farming and one unit increase household number income to result increase consumption of organic produce. Consumers were not aware of the certification and control process. As a result, easy of accesibility of organic produces in the supermarkets need to be improved.
ACUTE BEHAVIORAL CHANGES IN THE GUPPY (Poecilia reticulata) EXPOSED TO TEMEPHOS
SELVİ, Mahmut; SARIKAYA, Rabia; Erkoç, Figen
2010-01-01
ABSTRACT Temephos is an organophosphorus insecticide used to control mosquito, midge and black fly larvae. This study was aimed to determine the acute toxicity of temephos on behavior of the guppy (Poecilia reticulata). Guppy fish (Poecilia reticulata) were selected for the bioassay experiments. Behavioral changes at each temephos concentration were recorded. The experiments were repeated 3 times. The 96 h acute toxicity range of temephos to adult male guppies was within 10 ...
Ibinson, James W; Vogt, Keith M; Taylor, Kevin B; Dua, Shiv B; Becker, Christopher J; Loggia, Marco; Wasan, Ajay D
2015-12-01
The insula is uniquely located between the temporal and parietal cortices, making it anatomically well-positioned to act as an integrating center between the sensory and affective domains for the processing of painful stimulation. This can be studied through resting-state functional connectivity (fcMRI) imaging; however, the lack of a clear methodology for the analysis of fcMRI complicates the interpretation of these data during acute pain. Detected connectivity changes may reflect actual alterations in low-frequency synchronous neuronal activity related to pain, may be due to changes in global cerebral blood flow or the superimposed task-induced neuronal activity. The primary goal of this study was to investigate the effects of global signal regression (GSR) and task paradigm regression (TPR) on the changes in functional connectivity of the left (contralateral) insula in healthy subjects at rest and during acute painful electric nerve stimulation of the right hand. The use of GSR reduced the size and statistical significance of connectivity clusters and created negative correlation coefficients for some connectivity clusters. TPR with cyclic stimulation gave task versus rest connectivity differences similar to those with a constant task, suggesting that analysis which includes TPR is more accurately reflective of low-frequency neuronal activity. Both GSR and TPR have been inconsistently applied to fcMRI analysis. Based on these results, investigators need to consider the impact GSR and TPR have on connectivity during task performance when attempting to synthesize the literature.
Executive Function, Coping, and Behavior in Survivors of Childhood Acute Lymphocytic Leukemia*
Campbell, Laura K.; Scaduto, Mary; Van Slyke, Deborah; Niarhos, Frances; Whitlock, James A.; Compas, Bruce E.
2008-01-01
Objective To examine the role of executive function in coping and behavioral outcomes in childhood acute lymphocytic leukemia (ALL) survivors. Methods We examined associations among several domains of executive function (working memory, behavioral inhibition, cognitive flexibility, and self-monitoring), coping, and emotional/behavioral problems in 30 children and adolescents ages 10- to 20-years old who completed treatment for ALL and 30 healthy controls matched on age and sex. Results We fou...
Hughes, James P.; Haley, Danielle F.; Frew, Paula M.; Golin, Carol E.; Adimora, Adaora A; Kuo, Irene; Justman, Jessica; Soto-Torres, Lydia; Wang, Jing; Hodder, Sally
2015-01-01
Purpose Reductions in risk behaviors are common following enrollment in HIV prevention studies. We develop methods to quantify the proportion of change in risk behaviors that can be attributed to regression to the mean versus study participation and other factors. Methods A novel model that incorporates both regression to the mean and study participation effects is developed for binary measures. The model is used to estimate the proportion of change in the prevalence of “unprotected sex in the past 6 months” that can be attributed to study participation versus regression to the mean in a longitudinal cohort of women at risk for HIV infection who were recruited from ten US communities with high rates of HIV and poverty. HIV risk behaviors were evaluated using audio computer-assisted self-interviews at baseline and every 6 months for up to 12 months. Results The prevalence of “unprotected sex in the past 6 months” declined from 96% at baseline to 77% at 12 months. However, this change could be almost completely explained by regression to the mean. Conclusions Analyses that examine changes over time in cohorts selected for high or low risk behaviors should account for regression to the mean effects. PMID:25883065
Directory of Open Access Journals (Sweden)
Jaime Lynn Speiser
Full Text Available Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF patients often presents significant challenges. King's College (KCC has been validated on hospital admission, but little has been published on later phases of illness. We aimed to improve determinations of prognosis both at the time of and following admission for APAP-ALF using Classification and Regression Tree (CART models.CART models were applied to US ALFSG registry data to predict 21-day death or liver transplant early (on admission and post-admission (days 3-7 for 803 APAP-ALF patients enrolled 01/1998-09/2013. Accuracy in prediction of outcome (AC, sensitivity (SN, specificity (SP, and area under receiver-operating curve (AUROC were compared between 3 models: KCC (INR, creatinine, coma grade, pH, CART analysis using only KCC variables (KCC-CART and a CART model using new variables (NEW-CART.Traditional KCC yielded 69% AC, 90% SP, 27% SN, and 0.58 AUROC on admission, with similar performance post-admission. KCC-CART at admission offered predictive 66% AC, 65% SP, 67% SN, and 0.74 AUROC. Post-admission, KCC-CART had predictive 82% AC, 86% SP, 46% SN and 0.81 AUROC. NEW-CART models using MELD (Model for end stage liver disease, lactate and mechanical ventilation on admission yielded predictive 72% AC, 71% SP, 77% SN and AUROC 0.79. For later stages, NEW-CART (MELD, lactate, coma grade offered predictive AC 86%, SP 91%, SN 46%, AUROC 0.73.CARTs offer simple prognostic models for APAP-ALF patients, which have higher AUROC and SN than KCC, with similar AC and negligibly worse SP. Admission and post-admission predictions were developed.• Prognostication in acetaminophen-induced acute liver failure (APAP-ALF is challenging beyond admission • Little has been published regarding the use of King's College Criteria (KCC beyond admission and KCC has shown limited sensitivity in subsequent studies • Classification and Regression Tree (CART methodology allows the
Harris, Breanna N; Perea-Rodriguez, Juan Pablo; Saltzman, Wendy
2011-11-01
Glucocorticoids are thought to mediate the disruption of parental behavior in response to acute and chronic stress. Previous research supports their role in chronic stress; however, no study has experimentally tested the effects of acute glucocorticoid elevation on paternal behavior. We tested the prediction that acute corticosterone (CORT) increases would decrease paternal behavior in California mouse fathers and would lead to longer-term effects on reproductive success, as even short-term increases in CORT have been shown to produce lasting effects on the hypothalamic-pituitary-adrenal axis. First-time fathers were injected with 30 mg/kg CORT, 60 mg/kg CORT or vehicle, or left unmanipulated. Interactions between the male and its pup(s) were recorded 1.5-2h after injection and scored for paternal and non-paternal behavior. Treatment groups were combined into control (unmanipulated + vehicle, n = 15) and CORT (30 mg/kg + 60 mg/kg, n = 16) for analysis based on resulting plasma CORT concentrations. CORT treatment did not alter paternal or non-paternal behaviors or any long-term measures (male body mass or temperature, pup growth rate, pup survival, interbirth interval, number or mass of pups born in the second litter). Fathers showed a significant rise in body mass at day 30 postpartum, followed by a decrease in body mass after the birth of the second litter; however, this pattern did not differ between the CORT and control groups. In summary, acute elevation of plasma CORT did not alter direct paternal behavior, body mass, or reproductive outcomes, suggesting that acute CORT elevation alone does not overtly disrupt paternal care in this biparental mammal. PMID:21939660
The Additive Benefit of Hypnosis and Cognitive-Behavioral Therapy in Treating Acute Stress Disorder
Bryant, Richard A.; Moulds, Michelle L.; Guthrie, Rachel M.; Nixon, Reginald D. V.
2005-01-01
This research represents the first controlled treatment study of hypnosis and cognitive- behavioral therapy (CBT) of acute stress disorder (ASD). Civilian trauma survivors (N = 87) who met criteria for ASD were randomly allocated to 6 sessions of CBT, CBT combined with hypnosis (CBT-hypnosis), or supportive counseling (SC). CBT comprised exposure,…
Martinez, Sarah; Davalos, Deana
2016-01-01
Objective: Executive dysfunction in college students who have had an acute traumatic brain injury (TBI) was investigated. The cognitive, behavioral, and metacognitive effects on college students who endorsed experiencing a brain injury were specifically explored. Participants: Participants were 121 college students who endorsed a mild TBI, and 121…
Hao, Lingxin
2007-01-01
Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao
Cannabinoids & Stress: impact of HU-210 on behavioral tests of anxiety in acutely stressed mice.
Kinden, Renee; Zhang, Xia
2015-05-01
Anxiety disorders are one of the most prevalent classes of mental disorders affecting the general population, but current treatment strategies are restricted by their limited efficacy and side effect profiles. Although the cannabinoid system is speculated to be a key player in the modulation of stress responses and emotionality, the vast majority of current research initiatives had not incorporated stress exposure into their experimental designs. This study was the first to investigate the impact of exogenous cannabinoid administration in an acutely stressed mouse model, where CD1 mice were pre-treated with HU-210, a potent CB1R agonist, prior to acute stress exposure and subsequent behavioral testing. Exogenous cannabinoid administration induced distinct behavioral phenotypes in stressed and unstressed mice. While low doses of HU-210 were anxiolytic in unstressed subjects, this effect was abolished when mice were exposed to an acute stressor. The administration of higher HU-210 doses in combination with acute stress exposure led to severe locomotor deficits that were not previously observed at the same dose in unstressed subjects. These findings suggest that exogenous cannabinoids and acute stress act synergistically in an anxiogenic manner. This study underlies the importance of including stress exposure into future anxiety-cannabinoid research due to the differential impact of cannabinoid administration on stressed and unstressed subjects.
OSO paradigm--A rapid behavioral screening method for acute psychosocial stress reactivity in mice.
Brzózka, M M; Unterbarnscheidt, T; Schwab, M H; Rossner, M J
2016-02-01
Chronic psychosocial stress is an important environmental risk factor for the development of psychiatric diseases. However, studying the impact of chronic psychosocial stress in mice is time consuming and thus not optimally suited to 'screen' increasing numbers of genetically manipulated mouse models for psychiatric endophenotypes. Moreover, many studies focus on restraint stress, a strong physical stressor with limited relevance for psychiatric disorders. Here, we describe a simple and a rapid method based on the resident-intruder paradigm to examine acute effects of mild psychosocial stress in mice. The OSO paradigm (open field--social defeat--open field) compares behavioral consequences on locomotor activity, anxiety and curiosity before and after exposure to acute social defeat stress. We first evaluated OSO in male C57Bl/6 wildtype mice where a single episode of social defeat reduced locomotor activity, increased anxiety and diminished exploratory behavior. Subsequently, we applied the OSO paradigm to mouse models of two schizophrenia (SZ) risk genes. Transgenic mice with neuronal overexpression of Neuregulin-1 (Nrg1) type III showed increased risk-taking behavior after acute stress exposure suggesting that NRG1 dysfunction is associated with altered affective behavior. In contrast, Tcf4 transgenic mice displayed a normal stress response which is in line with the postulated predominant contribution of TCF4 to cognitive deficits of SZ. In conclusion, the OSO paradigm allows for rapid screening of selected psychosocial stress-induced behavioral endophenotypes in mouse models of psychiatric diseases.
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HE Wei-ping; HU Jin-hua; ZHAO Jun; TONG Jing-jing; DING Jin-biao; LIN Fang; WANG Hui-fen
2012-01-01
Background Acute-on-chronic hepatitis B liver failure (ACLF-HBV) is a clinically severe disease associated with major life-threatening complications including hepatic encephalopathy and hepatorenal syndrome.The aim of this study was to evaluate the short-term prognostic predictability of the model for end-stage liver disease (MELD),MELD-based indices,and their dynamic changes in patients with ACLF-HBV,and to establish a new model for predicting the prognosis of ACLF-HBV.Methods A total of 172 patients with ACLF-HBV who stayed in the hospital for more than 2 weeks were retrospectively recruited.The predictive accuracy of MELD,MELD-based indices,and their dynamic change (△) were compared using the area under the receiver operating characteristic curve method.The associations between mortality and patient characteristics were studied by univariate and multivariate analyses.Results The 3-month mortality was 43.6％.The largest concordance (c) statistic predicting 3-month mortality was the MELD score at the end of 2 weeks of admission (0.8),followed by the MELD:sodium ratio (MESO) (0.796) and integrated MELD (iMELD) (0.758) scores,△MELD (0.752),△MESO (0.729),and MELD plus sodium (MELD-Na) (0.728) scores.In multivariate Logistic regression analysis,the independent factors predicting prognosis were hepatic encephalopathy (OR=-3.466),serum creatinine,international normalized ratio (INR),and total bilirubin at the end of 2 weeks of admission (OR=10.302,6.063,5.208,respectively),and cholinesterase on admission (OR=0.255).This regression model had a greater prognostic value (c=0.85,95％ Cl 0.791-0.909) compared to the MELD score at the end of 2 weeks of admission (Z=4.9851,P=-0.0256).Conclusions MELD score at the end of 2 weeks of admission is a useful predictor for 3-month mortality in ACLF-HBV patients.Hepatic encephalopathy,serum creatinine,international normalized ratio,and total bilirubin at the end of 2 weeks of admission and cholinesterase on admission are
Institute of Scientific and Technical Information of China (English)
Guijun YANG; Lu LIN; Runchu ZHANG
2007-01-01
Quasi-regression, motivated by the problems arising in the computer experiments, focuses mainly on speeding up evaluation. However, its theoretical properties are unexplored systemically. This paper shows that quasi-regression is unbiased, strong convergent and asymptotic normal for parameter estimations but it is biased for the fitting of curve. Furthermore, a new method called unbiased quasi-regression is proposed. In addition to retaining the above asymptotic behaviors of parameter estimations, unbiased quasi-regression is unbiased for the fitting of curve.
ACUTE PRENATAL EXPOSURE TO ETHANOL AND SOCIAL BEHAVIOR: EFFECT OF AGE, SEX, AND TIMING OF EXPOSURE
Mooney, Sandra M.; Varlinskaya, Elena I.
2010-01-01
During development of the central nervous system, neurons pass through critical periods of vulnerability to environmental factors. Exposure to ethanol during gastrulation or during neuronal generation results in a permanent reduction in the number of neurons in trigeminal-associated cranial nerve nuclei. Normal functioning of the trigeminal system is required for social behavior, the present study examined the effects of acute prenatal exposure to ethanol on social interactions across ontogen...
Kahane, Leo H
2007-01-01
Using a friendly, nontechnical approach, the Second Edition of Regression Basics introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics. New to the Second Edition Offers greater coverage of simple panel-data estimation:
Grégoire, G.
2014-12-01
The logistic regression originally is intended to explain the relationship between the probability of an event and a set of covariables. The model's coefficients can be interpreted via the odds and odds ratio, which are presented in introduction of the chapter. The observations are possibly got individually, then we speak of binary logistic regression. When they are grouped, the logistic regression is said binomial. In our presentation we mainly focus on the binary case. For statistical inference the main tool is the maximum likelihood methodology: we present the Wald, Rao and likelihoods ratio results and their use to compare nested models. The problems we intend to deal with are essentially the same as in multiple linear regression: testing global effect, individual effect, selection of variables to build a model, measure of the fitness of the model, prediction of new values… . The methods are demonstrated on data sets using R. Finally we briefly consider the binomial case and the situation where we are interested in several events, that is the polytomous (multinomial) logistic regression and the particular case of ordinal logistic regression.
Haverroth, Gabriela M B; Welang, Chariane; Mocelin, Riciéri N; Postay, Daniela; Bertoncello, Kanandra T; Franscescon, Francini; Rosemberg, Denis B; Dal Magro, Jacir; Dalla Corte, Cristiane L
2015-12-01
Copper is a heavy metal found at relatively high concentrations in surface waters around the world. Copper is a micronutrient at low concentrations and is essential to several organisms. At higher concentrations copper can become toxic, which reveal the importance of studying the toxic effects of this metal on the aquatic life. Thus, the objective of this study was to evaluate the toxic effects of copper on the behavior and biochemical parameters of zebrafish (Danio rerio). Zebrafish were exposed for 24h at a concentration of 0.006 mg/L Cu. After the exposure period, behavioral profile of animals was recorded through 6 min using two different apparatuses tests: the Novel Tank and the Light-Dark test. After behavioral testing, animals were euthanized with a solution of 250 mg/L of tricaine (MS-222). Brain, muscle, liver and gills were extracted for analysis of parameters related to oxidative stress and accumulation of copper in these tissues. Acetylcholinesterase (AChE) activity was determined in brain and muscle. Results showed acute exposure to copper induces significant changes in behavioral profile of zebrafish by changing locomotion and natural tendency to avoid brightly lit area. On the other hand, there were no significant effects on parameters related to oxidative stress. AChE activity decreased significantly in zebrafish muscle, but there were no significant changes in cerebral AChE activity. Copper levels in tissues did not increase significantly compared to the controls. Taken together, these results indicate that a low concentration of copper can acutely affect behavioral profile of adult zebrafish which could be partially related to an inhibition on muscle AChE activity. These results reinforce the need of additional tests to establishment of safe copper concentrations to aquatic organisms and the importance of behavioral parameters in ecotoxicological studies.
Matitaishvili, T; Domianidze, T; Emukhvari, N; Khananashvili, M
2016-03-01
The aim of our research was to study behavioral indices of rats standing on various hierarchical level in the conditions of acute informational stress as well as their resistance to stress taking into account their social status. The Animal's behavior has been studied in conflict and agonist conditions against the background of high food and thirst motivation. After determination of hierarchical relations the stressing procedure of two active avoidance reactions was performed simultaneously during one trial (14 days). During the experiment, behavioral indices of rats induced by stressing procedure were registered. We used "open field" test in order to assess animals' emotional state. The studies performed by us demonstrated behavioral characteristics of animals standing on various hierarchical level. The obtained results showed that after stressing all the animals of the group under stressogenic influence of equal strength, behavior of rats did nor reliably differ in conflict situations. Dominants standing on high hierarchical level remained active in both conflict situations. The impact of stress on their behavior was less detected. Dominant animal maintained its hierarchical status. Submissive rats were more greatly influenced by stress. The obtained results confirmed that dominant animals were characterized with more comprehensively developed self-regulating mechanisms of brain. PMID:27119838
Acute Synthesis of CPEB Is Required for Plasticity of Visual Avoidance Behavior in Xenopus
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Wanhua Shen
2014-02-01
Full Text Available Neural plasticity requires protein synthesis, but the identity of newly synthesized proteins generated in response to plasticity-inducing stimuli remains unclear. We used in vivo bio-orthogonal noncanonical amino acid tagging (BONCAT with the methionine analog azidohomoalanine (AHA combined with the multidimensional protein identification technique (MudPIT to identify proteins that are synthesized in the tadpole brain over 24 hr. We induced conditioning-dependent plasticity of visual avoidance behavior, which required N-methyl-D-aspartate (NMDA and Ca2+-permeable α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA receptors, αCaMKII, and rapid protein synthesis. Combining BONCAT with western blots revealed that proteins including αCaMKII, MEK1, CPEB, and GAD65 are synthesized during conditioning. Acute synthesis of CPEB during conditioning is required for behavioral plasticity as well as conditioning-induced synaptic and structural plasticity in the tectal circuit. We outline a signaling pathway that regulates protein-synthesis-dependent behavioral plasticity in intact animals, identify newly synthesized proteins induced by visual experience, and demonstrate a requirement for acute synthesis of CPEB in plasticity.
Acute behavioral effects of nicotine in male and female HINT1 knockout mice.
Jackson, K J; Wang, J B; Barbier, E; Chen, X; Damaj, M I
2012-11-01
Human genetic association and brain expression studies, and mouse behavioral and molecular studies implicate a role for the histidine triad nucleotide-binding protein 1 (HINT1) in schizophrenia, bipolar disorder, depression and anxiety. The high comorbidity between smoking and psychiatric disorders, schizophrenia in particular, is well established. Associations with schizophrenia and HINT1 are also sex specific, with effects more predominant in males; however, it is unknown if sex differences associated with the gene extend to other phenotypes. Thus, in this study, using a battery of behavioral tests, we elucidated the role of HINT1 in acute nicotine-mediated behaviors using male and female HINT1 wild-type (+/+) and knockout (-/-) mice. The results show that male HINT1 -/- mice were less sensitive to acute nicotine-induced antinociception in the tail-flick, but not hot-plate test. At low nicotine doses, male and female HINT1 -/- mice were less sensitive to nicotine-induced hypomotility, although the effect was more pronounced in females. Baseline differences in locomotor activity observed in male HINT1 +/+ and -/- mice were absent in females. Nicotine did not produce an anxiolytic effect in male HINT1 -/- mice, but rather an anxiogenic response. Diazepam also failed to induce an anxiolytic response in these mice, suggesting a general anxiety phenotype not specific to nicotine. Differences in anxiety-like behavior were not observed in female mice. These results further support a role for HINT1 in nicotine-mediated behaviors and suggest that alterations in the gene may have differential effects on phenotype in males and females. PMID:22827509
Behavioral economic analysis of stress effects on acute motivation for alcohol.
Owens, Max M; Ray, Lara A; MacKillop, James
2015-01-01
Due to issues of definition and measurement, the heavy emphasis on subjective craving in the measurement of acute motivation for alcohol and other drugs remains controversial. Behavioral economic approaches have increasingly been applied to better understand acute drug motivation, particularly using demand curve modeling via purchase tasks to characterize the perceived reinforcing value of the drug. This approach has focused on using putatively more objective indices of motivation, such as units of consumption, monetary expenditure, and price sensitivity. To extend this line of research, the current study used an alcohol purchase task to determine if, compared to a neutral induction, a personalized stress induction would increase alcohol demand in a sample of heavy drinkers. The stress induction significantly increased multiple measures of the reinforcing value of alcohol to the individual, including consumption at zero price (intensity), the maximum total amount of money spent on alcohol (Omax), the first price where consumption was reduced to zero (breakpoint), and the general responsiveness of consumption to increases in price (elasticity). These measures correlated only modestly with craving and mood. Self-reported income was largely unrelated to demand but moderated the influence of stress on Omax. Moderation based on CRH-BP genotype (rs10055255) was present for Omax, with T allele homozygotes exhibiting more pronounced increases in response to stress. These results provide further support for a behavioral economic approach to measuring acute drug motivation. The findings also highlight the potential relevance of income and genetic factors in understanding state effects on the perceived reinforcing value of alcohol. PMID:25413719
Ellis, Jason; Cushing, Toby; Germain, Anne
2015-01-01
Study Objectives Despite considerable evidence supporting cognitive behavioral therapy for insomnia (CBT-I) for chronic insomnia, it remains untested within the context of acute insomnia. This study examined the efficacy of a single session of CBT-I, with an accompanying self-help pamphlet, for individuals with acute insomnia. Design A pragmatic parallel group randomized controlled trial. Participants Forty adults (mean age 32.9 + 13.72 y) with Diagnostic and Statistical Manu...
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Niedobitek Gerald
2010-03-01
Full Text Available Abstract Epstein-Barr virus (EBV-associated B-cell post-transplantation lymphoproliferative disorder (PTLD is a severe complication following stem cell transplantation. This is believed to occur as a result of iatrogenic immunosuppression leading to a relaxation of T-cell control of EBV infection and thus allowing viral reactivation and proliferation of EBV-infected B-lymphocytes. In support of this notion, reduction of immunosuppressive therapy may lead to regression of PTLD. We present a case of an 18-year-old male developing a monomorphic B-cell PTLD 2 months after receiving an allogenic stem cell transplant for acute lymphoblastic leukemia. Reduction of immunosuppressive therapy led to regression of lymphadenopathy. Nevertheless, the patient died 3 months afterwards due to extensive graft-vs.-host-disease and sepsis. As a diagnostic lymph node biopsy was performed only after reduction of immunosuppressive therapy, we are able to study the histopathological changes characterizing PTLD regression. We observed extensive apoptosis of blast cells, accompanied by an abundant infiltrate comprising predominantly CD8-positive, Granzyme B-positive T-cells. This observation supports the idea that regression of PTLD is mediated by cytotoxic T-cells and is in keeping with the observation that T-cell depletion, represents a major risk factor for the development of PTLD.
Institute of Scientific and Technical Information of China (English)
XU Jian-yu; MIAO Xiang-wen; LIU Ying; CUI Shao-rong
2005-01-01
The behavioral responses of a tilapia (Oreochromis niloticus) school to low (0.13 mg/L), moderate (0.79 mg/L) and high (2.65 mg/L) levels of unionized ammonia (UIA) concentration were monitored using a computer vision system. The swimming activity and geometrical parameters such as location of the gravity center and distribution of the fish school were calculated continuously. These behavioral parameters of tilapia school responded sensitively to moderate and high UIA concentration. Under high UIA concentration the fish activity showed a significant increase (P＜0.05), exhibiting an avoidance reaction to high ammonia condition, and then decreased gradually. Under moderate and high UIA concentration the school's vertical location had significantly large fluctuation (P＜0.05) with the school moving up to the water surface then down to the bottom of the aquarium alternately and tending to crowd together. After several hours' exposure to high UIA level, the school finally stayed at the aquarium bottom. These observations indicate that alterations in fish behavior under acute stress can provide important information useful in predicting the stress.
Friedman, Alexander; Frankel, Michael; Flaumenhaft, Yakov; Merenlender, Avia; Pinhasov, Albert; Feder, Yuval; Taler, Michal; Gil-Ad, Irit; Abeles, Moshe; Yadid, Gal
2009-03-01
Depressive disorders affect approximately 5% of the population in any given year. Antidepressants may require several weeks to produce their clinical effects. Despite progress being made in this area there is still room and a need to explore additional therapeutic modes to increase treatment effectiveness and responsiveness. Herein, we examined a new method for intervention in depressive states based on deep brain stimulation of the ventral tegmental area (VTA) as a source of incentive motivation and hedonia, in comparison to chemical antidepressants. The pattern of stimulation was fashioned to mimic the firing pattern of VTA neurons in the normal rat. Behavioral manifestations of depression were then monitored weekly using a battery of behavioral tests. The results suggest that treatment with programmed acute electrical stimulation of the VTA substantially alleviates depressive behavior, as compared to chemical antidepressants or electroconvulsive therapy, both in onset time and longitudinal effect. These results were also highly correlated with increases in brain-derived neurotrophic factor mRNA levels in the prefrontal cortex. PMID:18843267
Acute metal toxicology of olfaction in coho salmon: behavior, receptors, and odor-metal complexation
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Rehnberg, B.C.; Schreck, C.B.
1986-04-01
The objective of this research was to determine the acute toxicities of mercury (Hg), copper (Cu), and zinc (Zn) to coho salmon olfaction. The authors used a behavioral assay of olfaction based on an avoidance reaction to L-serine in a two-choice Y-trough. A second objective was to gain some understanding of the mechanism of metal-induced olfactory inhibition by observing how metals affect the binding of L-serine to its olfactory cell membrane receptor. They have also taken the novel approach of addressing olfactory toxicology from the perspective of the odor molecule by considering metal speciation and metal-serpine complexation chemistry on the basis of chemical equilibrium computations.
Freedland, Kenneth E.; Carney, Robert M.; Hayano, Junichiro; Steinmeyer, Brian C.; Reese, Rebecca L.; Roest, Annelieke M.
2012-01-01
Objective: To determine whether obstructive sleep apnea (OSA) interferes with cognitive behavior therapy (CBT) for depression in patients with coronary heart disease. Methods: Patients who were depressed within 28 days after an acute myocardial infarction (MI) were enrolled in the Enhancing Recovery
Gosschalk, Philip O.
2004-01-01
This paper describes the behavioral treatment of acute onset school refusal in a 5-year old girl with Separation Anxiety Disorder (SAD). A functional classification was used to select a treatment approach that involved the parent and teacher using shaping, positive reinforcement and extinction. Results showed that by the end of the fifth week of…
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Laura A . León
2010-02-01
Full Text Available In order to study the effect of behavioral or pharmacologically enhanced anxiety on the acquisition of contextual fear conditioning, thirty two Wistar rats (275±25 gm were divided in two groups (behavioral restriction and control. Half of each group received saline solution (ig.; 0.9% or fluoxetine(ig.; 4mg/Kg before the fear conditioning procedure. The two way ANOVA showed significant differences for treatment (F[1,28] = 25.261; P < 0.001. Student Newman-Keuls showed that subjects treated with fluoxetine had lower freezing times. There were no significant differences nor for restriction neither for the interaction between the factors (F[1,28] = 0.115; P = 0.737 y F[1,28] = 0.016; P = 0.899. Thus, the restriction procedure used did not modify the acquisition of the conditioned fear response suggesting that the putative 5-HT enhancement induced is not comparable to that induced by fluoxetine. Acute fluoxetine disrupted the acquisition of the conditioned fear response, suggesting that the mechanism by means of which anxiety disrupts learning could be serotonergic in nature.
Virués-Ortega, Javier
2010-06-01
A number of clinical trials and single-subject studies have been published measuring the effectiveness of long-term, comprehensive applied behavior analytic (ABA) intervention for young children with autism. However, the overall appreciation of this literature through standardized measures has been hampered by the varying methods, designs, treatment features and quality standards of published studies. In an attempt to fill this gap in the literature, state-of-the-art meta-analytical methods were implemented, including quality assessment, sensitivity analysis, meta-regression, dose-response meta-analysis and meta-analysis of studies of different metrics. Results suggested that long-term, comprehensive ABA intervention leads to (positive) medium to large effects in terms of intellectual functioning, language development, acquisition of daily living skills and social functioning in children with autism. Although favorable effects were apparent across all outcomes, language-related outcomes (IQ, receptive and expressive language, communication) were superior to non-verbal IQ, social functioning and daily living skills, with effect sizes approaching 1.5 for receptive and expressive language and communication skills. Dose-dependant effect sizes were apparent by levels of total treatment hours for language and adaptation composite scores. Methodological issues relating ABA clinical trials for autism are discussed. PMID:20223569
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SONG Li; YAN Hong-bing; YANG Jin-gang; SUN Yi-hong; HU Da-yi
2010-01-01
Background Delay in seeking medical care in patients with acute myocardial infarction (AMI) is receiving increasing attention. This study aimed to examine the association between expected symptoms and experienced symptoms of AMI and its effects on care-seeking behaviors of patients with AMI.Methods Between November 1, 2005 and December 31, 2006, a cross-sectional and multicenter survey was conducted in 19 hospitals in Beijing and included 799 patients with ST-elevation myocardial infarction (STEMI) admitted within 24 hours after onset of symptoms. Data were collected by structured interviews and medical record review.Results The median (25%, 75%) prehospital delay was 140 (75, 300) minutes. Only 264 (33.0%) arrived at the hospital by ambulance. The most common symptoms expected by patients with STEMI were central or left chest pain (71.4%),radiating arm or shoulder pain (68.7%), shortness of breath or dyspnea (65.5%), and loss of consciousness (52.1%). The most common symptoms experienced were central or left chest pain (82.1%), sweats (71.8%), shortness of breath or dyspnea (43.7%), nausea or vomiting (32.3%), and radiating pain (29.4%). A mismatch between symptoms experienced and those expected occurred in 41.8% of patients. Patients who interpreted their symptoms as noncardiac in origin were more likely to arrive at the hospital by self-transport (86.5% vs. 52.9%, P <0.001) and had longer prehospital delays (medians, 180 vs. 120 minutes, P <0.001) compared to those who interpreted their symptoms as cardiac in origin.Conclusions Symptom interpretation influenced the care-seeking behaviors of patients with STEMI in Beijing. A mismatch between expectation and actual symptoms was associated with longer prehospital delay and decreased use of emergency medical service (EMS).
Bulcock, J. W.
The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
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WANG Dayong; XING Xiaojuan
2008-01-01
Locomotion behaviors are susceptible to disruption by a broad spectrum of chemicals and environmental stresses. However, no systematic testing of locomotion behavior defects induced by metal exposure has been conducted in the model organism of nematode Caenorhabditis elegans. In this study, the acute toxicity from heavy metal exposure on the locomotion behaviors was analyzed in nematodes. Endpoints of head thrash, body bend, forward turn, backward turn, and Omega/U turn were chosen to evaluate the locomotion behavioral defects. Our data suggest that the endpoints of head thrash, body bend, and forward turn will be useful for the evaluation of heavy metal toxicity in nematodes. The endpoint of head thrash could detect the toxicity from Cd, Co, Cr, Cu, Hg, and Pb exposures at a low concentration (2.5 μmol/L). The endpoint of body bend could be explored to evaluate the toxicity from all assayed heavy metal exposures at different concentrations, whereas the endpoint of forward turn will be more useful for the evaluation of heavy metal toxicity at high concentrations. Thus, endpoints of these locomotion behaviors establish a fast and economic way to assess the presence of acute toxicity from heavy metal exposure in nematode C. elegans.
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Shawn K Acheson
Full Text Available Ethanol is well known to adversely affect frontal executive functioning, which continues to develop throughout adolescence and into young adulthood. This is also a developmental window in which ethanol is misused by a significant number of adolescents. We examined the effects of acute and chronic ethanol exposure during adolescence on behavioral inhibition and efficiency using a modified water maze task. During acquisition, rats were trained to find a stable visible platform onto which they could escape. During the test phase, the stable platform was converted to a visible floating platform (providing no escape and a new hidden platform was added in the opposite quadrant. The hidden platform was the only means of escape during the test phase. In experiment 1, adolescent animals received ethanol (1.0 g/kg 30 min before each session during the test phase. In experiment 2, adolescent animals received chronic intermittent ethanol (5.0 g/kg for 16 days (PND30 To PND46 prior to any training in the maze. At PND72, training was initiated in the same modified water maze task. Results from experiment 1 indicated that acute ethanol promoted behavioral disinhibition and inefficiency. Experiment 2 showed that chronic intermittent ethanol during adolescence appeared to have no lasting effect on behavioral disinhibition or new spatial learning during adulthood. However, chronic ethanol did promote behavioral inefficiency. In summary, results indicate that ethanol-induced promotion of perseverative behavior may contribute to the many adverse behavioral sequelae of alcohol intoxication in adolescents and young adults. Moreover, the long-term effect of adolescent chronic ethanol exposure on behavioral efficiency is similar to that observed after chronic exposure in humans.
Calfee, Robin D.; Puglis, Holly J.; Little, Edward E.; Brumbaugh, William G.; Mebane, Christopher A.
2016-01-01
Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction. However, these responses may be subtle, and measurement can be challenging. Using juvenile white sturgeon (Acipenser transmontanus) with copper exposures, this paper illustrates techniques used for quantifying behavioral responses using computer assisted video and digital image analysis. In previous studies severe impairments in swimming behavior were observed among early life stage white sturgeon during acute and chronic exposures to copper. Sturgeon behavior was rapidly impaired and to the extent that survival in the field would be jeopardized, as fish would be swept downstream, or readily captured by predators. The objectives of this investigation were to illustrate protocols to quantify swimming activity during a series of acute copper exposures to determine time to effect during early lifestage development, and to understand the significance of these responses relative to survival of these vulnerable early lifestage fish. With mortality being on a time continuum, determining when copper first affects swimming ability helps us to understand the implications for population level effects. The techniques used are readily adaptable to experimental designs with other organisms and stressors.
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Rasmussen, Rune Skovgaard; Overgaard, Karsten; Kristiansen, Uffe;
2011-01-01
OBJECTIVES: The objective of this study was to examine the effects of d-amphetamine (amph) upon recovery after embolic stroke in rats. METHODS: Ninety-three rats were embolized in the right middle cerebral artery and assigned to: (1) controls; (2) combination (acute amph and later amph-facilitate......OBJECTIVES: The objective of this study was to examine the effects of d-amphetamine (amph) upon recovery after embolic stroke in rats. METHODS: Ninety-three rats were embolized in the right middle cerebral artery and assigned to: (1) controls; (2) combination (acute amph and later amph......: In conclusion, results showed that the acute amph group performed the best, while the late amph and the combination groups performed the worst. Amphetamine treatment in acute stroke may be warranted due to reduced detrimental effects of hypotension and improved brain plasticity....
Denesiuk, E V
2015-01-01
The study involved 23 men after acute myocardial infarction (AMI) with comorbid arterial hypertension (AH). Mean age of patients was 56.7 years. Recurrent myocardial infarction was determined in 38.4%, cardiac failure I-III functional classes--100% of the cases. All patients underwent clinical examination, electrocardiography and echocardiography, blood lipid profile. Standard comprehensive treatment for two years included an perindopril 5-10 mg/day, beta-blocker bisoprolol--5-10 mg/day, antisclerotic drug atorvastatin--20 mg/day and aspirin--75 mg/day. The patients after treatment was determined by a gradual increase towards the target of AT at 3, 6 and 12 to 24 months. Concentric left ventricular hypertrophy (LVH) before treatment was determined in 47.8%, eccentric--in 52.2% of patients. In the study of degrees of LVH I (initial) the extent to treatment was determined by 4.3%, II (moderate)--26.1%, III (large)--at 69.6%, indicating the development of cardiac remodeling. After the treatment was determined by marked reduction III (large) degree and transfer it in the II (moderate) and I (small) degree of left ventricular hypertrophy due to more or less pronounced changes remodeling left ventricular. The obtained data allow a more detailed and adequately assess the structural and functional outcome variables and determine the regression of myocardial hypertrophy in the background to achieve target blood pressure, which is important in practical cardiology.
Denesiuk, E V
2015-01-01
The study involved 23 men after acute myocardial infarction (AMI) with comorbid arterial hypertension (AH). Mean age of patients was 56.7 years. Recurrent myocardial infarction was determined in 38.4%, cardiac failure I-III functional classes--100% of the cases. All patients underwent clinical examination, electrocardiography and echocardiography, blood lipid profile. Standard comprehensive treatment for two years included an perindopril 5-10 mg/day, beta-blocker bisoprolol--5-10 mg/day, antisclerotic drug atorvastatin--20 mg/day and aspirin--75 mg/day. The patients after treatment was determined by a gradual increase towards the target of AT at 3, 6 and 12 to 24 months. Concentric left ventricular hypertrophy (LVH) before treatment was determined in 47.8%, eccentric--in 52.2% of patients. In the study of degrees of LVH I (initial) the extent to treatment was determined by 4.3%, II (moderate)--26.1%, III (large)--at 69.6%, indicating the development of cardiac remodeling. After the treatment was determined by marked reduction III (large) degree and transfer it in the II (moderate) and I (small) degree of left ventricular hypertrophy due to more or less pronounced changes remodeling left ventricular. The obtained data allow a more detailed and adequately assess the structural and functional outcome variables and determine the regression of myocardial hypertrophy in the background to achieve target blood pressure, which is important in practical cardiology. PMID:27491146
Directory of Open Access Journals (Sweden)
Abdul Rauf
2015-06-01
Full Text Available Malathion is one of the most commonly used pesticides in agriculture. This study was aimed to investigate the acute toxicity of malathion as an aquatic pollutant on the behavior and hematological indices in Indian carp (Cirrhinus mrigala. A static experiment was conducted and 1, 24, 48, 72 and 96 hrs LC50 values of malathion for the test fish were estimated as 14.55 mg/L, 12.48 mg/L, 11.56 mg/L, 10.85 mg/L and 9.32 mg/L, respectively. During 96 hrs exposure to 9.32 mg/L of malathion, behavioral abnormalities such as hyperactivity, cough, convulsions, erratic swimming, loss of balance, rapid opercular movements, gill mucous secretion, surfacing and gulping of air were observed in the test fish. The hematological changes in exposed fish after 96 hrs exposure to malathion included a significant decrease in erythrocyte count, hemoglobin content, hematocrit, leukocyte count and a significant increase in neutrophils count as compared to the control fish. In conclusion, acute exposure to 9.32 mg/L of malathion provoked behavioral and hematological abnormalities in Indian carp which offers a valuable tool to monitor malathion induced toxicity in fish.
DEFF Research Database (Denmark)
Sheng, Ying; Zhang, Yufeng; Sun, Yuexia;
2014-01-01
of moisture removal capacity, dehumidification effectiveness, dehumidification coefficient of performance and sensible energy ratio. The results show that higher effect on the dehumidification is due to the regeneration temperature and outdoor air humidity ratio rather than the outdoor air temperature...... and the ratio between regeneration and process air flow rates. A simple method based on multiple linear regression theory for predicting the performance of the wheel has been proposed. The predicted values and the experimental data are compared and good agreements are obtained. Regression models are established...
Nourse, Rosemary; Reade, Cynthia; Stoltzfus, Jill; Mittal, Vikrant
2014-01-01
Objective: Aggressive patients are not uncommon in acute inpatient behavioral health units of general hospitals. Prior research identifies various predictors associated with aggressive inpatient behavior. This prospective observational study examines the demographic and clinical characteristics of aggressive inpatients and the routine medications these patients were receiving at discharge.
Averaged extreme regression quantile
Jureckova, Jana
2015-01-01
Various events in the nature, economics and in other areas force us to combine the study of extremes with regression and other methods. A useful tool for reducing the role of nuisance regression, while we are interested in the shape or tails of the basic distribution, is provided by the averaged regression quantile and namely by the average extreme regression quantile. Both are weighted means of regression quantile components, with weights depending on the regressors. Our primary interest is ...
Effects of an acute and a sub-chronic 900 MHz GSM exposure on brain activity and behaviors of rats
Energy Technology Data Exchange (ETDEWEB)
Elsa Brillaud; Aleksandra Piotrowski; Anthony Lecomte; Franck Robidel; Rene de Seze [Toxicology Unit, INERIS, Verneuil en Halatte (France)
2006-07-01
Radio frequencies are suspected to produce health effects. Concerning the mobile phone technology, according to position during use (close to the head), possible effects of radio frequencies on the central nervous system have to be evaluated. Previous works showed contradictory results, possibly due to experimental design diversity. In the framework of R.A.M.P. 2001 project, we evaluated possible effect of a 900 MHz GSM exposure on the central nervous system of rat at a structural, a functional and a behavioral level after acute or sub-chronic exposures. Rats were exposed using a loop antenna system to different S.A.R. levels and durations, according to results of the French C.O.M.O.B.I.O. 2001 project. A functional effect was found (modification of the cerebral activity and increase of the glia surface) after an acute exposure, even at a low level of brain averaged S.A.R. (1.5 W/kg). No cumulative effect was observed after a sub-chronic exposure (same amplitude of the effect). No structural or behavioral consequence was noted. We do not conclude on the neurotoxicity of the 900 MHz GSM exposure on the rat brain. Our results do not indicate any health risk. (authors)
Diaz, Marvin R; Mooney, Sandra M; Varlinskaya, Elena I
2016-09-01
Our previous research has shown that in Long Evans rats acute prenatal exposure to a high dose of ethanol on gestational day (G) 12 produces social deficits in male offspring and elicits substantial decreases in social preference relative to controls, in late adolescents and adults regardless of sex. In order to generalize the observed detrimental effects of ethanol exposure on G12, pregnant female Sprague Dawley rats were exposed to ethanol or saline and their offspring were assessed in a modified social interaction (SI) test as early adolescents, late adolescents, or young adults. Anxiety-like behavior was also assessed in adults using the elevated plus maze (EPM) or the light/dark box (LDB) test. Age- and sex-dependent social alterations were evident in ethanol-exposed animals. Ethanol-exposed males showed deficits in social investigation at all ages and age-dependent alterations in social preference. Play fighting was not affected in males. In contrast, ethanol-exposed early adolescent females showed no changes in social interactions, whereas older females demonstrated social deficits and social indifference. In adulthood, anxiety-like behavior was decreased in males and females prenatally exposed to ethanol in the EPM, but not the LDB. These findings suggest that social alterations associated with acute exposure to ethanol on G12 are not strain-specific, although they are more pronounced in Long Evans males and Sprague Dawley females. Furthermore, given that anxiety-like behaviors were attenuated in a test-specific manner, this study indicates that early ethanol exposure can have differential effects on different forms of anxiety. PMID:27154534
DEFF Research Database (Denmark)
Fitzenberger, Bernd; Wilke, Ralf Andreas
2015-01-01
if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......, duration data, and endogeneity, and we describe how quantile regression can be used for decomposition analysis. Finally, we identify several key issues, which should be addressed by future research, and we provide an overview of quantile regression implementations in major statistics software. Our...... treatment of the topic is based on the perspective of applied researchers using quantile regression in their empirical work....
Acute and developmental behavioral effects of flame retardants and related chemicals in zebrafish
Jarema, Kimberly A; Hunter, Deborah L.; Shaffer, Rachel M.; Behl, Mamta; Padilla, Stephanie
2015-01-01
As polybrominated diphenyl ethers are phased out, numerous compounds are emerging as potential replacement flame retardants for use in consumer and electronic products. Little is known, however, about the neurobehavioral toxicity of these replacements. This study evaluated the neurobehavioral effects of acute or developmental exposure to t-butylphenyl diphenyl phosphate (BPDP), 2-ethylhexyl diphenyl phosphate (EHDP), isodecyl diphenyl phosphate (IDDP), isopropylated phenyl phosphate (IPP), tr...
Acute maternal alcohol consumption disrupts behavioral state organization in the near-term fetus
Mulder, EJH; Morssink, LP; Van der Schee, T; Visser, GHA
1998-01-01
Disturbed sleep regulation is often observed in neonates of women who drank heavily during pregnancy. It is unknown if (and how) an occasional drink affects fetal sleeping behavior. In 28 near-term pregnant women we examined the effects on fetal behavioral state organization of two glasses of wine (
Pedraza, C; Sánchez-López, J; Castilla-Ortega, E; Rosell-Valle, C; Zambrana-Infantes, E; García-Fernández, M; Rodriguez de Fonseca, F; Chun, J; Santín, L J; Estivill-Torrús, G
2014-09-01
LPA1 receptor is one of the six characterized G protein-coupled receptors (LPA1-6) through which lysophosphatidic acid acts as an intercellular signaling molecule. It has been proposed that this receptor has a role in controlling anxiety-like behaviors and in the detrimental consequences of stress. Here, we sought to establish the involvement of the LPA1 receptor in emotional regulation. To this end, we examined fear extinction in LPA1-null mice, wild-type and LPA1 antagonist-treated animals. In LPA1-null mice we also characterized the morphology and GABAergic properties of the amygdala and the medial prefrontal cortex. Furthermore, the expression of c-Fos protein in the amygdala and the medial prefrontal cortex, and the corticosterone response following acute stress were examined in both genotypes. Our data indicated that the absence of the LPA1 receptor significantly inhibited fear extinction. Treatment of wild-type mice with the LPA1 antagonist Ki16425 mimicked the behavioral phenotype of LPA1-null mice, revealing that the LPA1 receptor was involved in extinction. Immunohistochemistry studies revealed a reduction in the number of neurons, GABA+ cells, calcium-binding proteins and the volume of the amygdala in LPA1-null mice. Following acute stress, LPA1-null mice showed increased corticosterone and c-Fos expression in the amygdala. In conclusion, LPA1 receptor is involved in emotional behaviors and in the anatomical integrity of the corticolimbic circuit, the deregulation of which may be a susceptibility factor for anxiety disorders and a potential therapeutic target for the treatment of these diseases.
Regression Verification Using Impact Summaries
Backes, John; Person, Suzette J.; Rungta, Neha; Thachuk, Oksana
2013-01-01
Regression verification techniques are used to prove equivalence of syntactically similar programs. Checking equivalence of large programs, however, can be computationally expensive. Existing regression verification techniques rely on abstraction and decomposition techniques to reduce the computational effort of checking equivalence of the entire program. These techniques are sound but not complete. In this work, we propose a novel approach to improve scalability of regression verification by classifying the program behaviors generated during symbolic execution as either impacted or unimpacted. Our technique uses a combination of static analysis and symbolic execution to generate summaries of impacted program behaviors. The impact summaries are then checked for equivalence using an o-the-shelf decision procedure. We prove that our approach is both sound and complete for sequential programs, with respect to the depth bound of symbolic execution. Our evaluation on a set of sequential C artifacts shows that reducing the size of the summaries can help reduce the cost of software equivalence checking. Various reduction, abstraction, and compositional techniques have been developed to help scale software verification techniques to industrial-sized systems. Although such techniques have greatly increased the size and complexity of systems that can be checked, analysis of large software systems remains costly. Regression analysis techniques, e.g., regression testing [16], regression model checking [22], and regression verification [19], restrict the scope of the analysis by leveraging the differences between program versions. These techniques are based on the idea that if code is checked early in development, then subsequent versions can be checked against a prior (checked) version, leveraging the results of the previous analysis to reduce analysis cost of the current version. Regression verification addresses the problem of proving equivalence of closely related program
Regression analysis by example
Chatterjee, Samprit
2012-01-01
Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded
Secondary Prevention in Acute Myocardial Infarction
IRMAK, Yrd.Doç.Dr. Zöhre; FESCİ, Doç.Dr. Hatice
2005-01-01
Recent studies on patients who had an acute myocardial infarction have shown that risk factors are decreased, atherosclerosis regressed, and re-infarction and mortality rates are reduced as a result of drug therapy in combination with the changes in the lifestyle. This treatment called as secondary prevention, requires a behavioral change in the lifestyle that includes stopping smoking, making healthy food choices, and increasing physical activity. Risk factors related with lifestyle, wh...
Directory of Open Access Journals (Sweden)
Daniel G Reis
Full Text Available BACKGROUND: The Lateral Septal Area (LSA is involved with autonomic and behavior responses associated to stress. In rats, acute restraint (RS is an unavoidable stress situation that causes autonomic (body temperature, mean arterial pressure (MAP and heart rate (HR increases and behavioral (increased anxiety-like behavior changes in rats. The LSA is one of several brain regions that have been involved in stress responses. The aim of the present study was to investigate if the neurotransmission blockade in the LSA would interfere in the autonomic and behavioral changes induced by RS. METHODOLOGY/PRINCIPAL FINDINGS: Male Wistar rats with bilateral cannulae aimed at the LSA, an intra-abdominal datalogger (for recording internal body temperature, and an implanted catheter into the femoral artery (for recording and cardiovascular parameters were used. They received bilateral microinjections of the non-selective synapse blocker cobalt chloride (CoCl(2, 1 mM/ 100 nL or vehicle 10 min before RS session. The tail temperature was measured by an infrared thermal imager during the session. Twenty-four h after the RS session the rats were tested in the elevated plus maze (EPM. CONCLUSIONS/SIGNIFICANCE: Inhibition of LSA neurotransmission reduced the MAP and HR increases observed during RS. However, no changes were observed in the decrease in skin temperature and increase in internal body temperature observed during this period. Also, LSA inhibition did not change the anxiogenic effect induced by RS observed 24 h later in the EPM. The present results suggest that LSA neurotransmission is involved in the cardiovascular but not the temperature and behavioral changes induced by restraint stress.
Acute Stress Promotes Aggressive-Like Behavior in Rats Made Allergic to Tree Pollen
Tonelli, Leonardo H.; Hoshino, Akina; Katz, Morgan; Teodor T. Postolache
2008-01-01
It has been reported that allergies are associated with depression and possibly suicide in women. Aggression is an important behavioral component that predisposes depressed individuals to suicidal acts. In the present study we examined the relationship between allergies and aggression to determine a potential contribution of allergies in factors of risk for suicidal behavior. Because stress plays a critical role in the manifestation of clinical symptoms of allergies and also in suicidal behav...
Naghshpour, Shahdad
2012-01-01
Regression analysis is the most commonly used statistical method in the world. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation and will help demystify regression analysis using examples from economics and with real data to show the applications of the method. T
Jha, Mithilesh Kumar; Rahman, Md Habibur; Park, Dong Ho; Kook, Hyun; Lee, In-Kyu; Lee, Won-Ha; Suk, Kyoungho
2016-09-01
Pyruvate dehydrogenase (PDH) kinases (PDKs) 1-4, expressed in peripheral and central tissues, regulate the activity of the PDH complex (PDC). The PDC is an important mitochondrial gatekeeping enzyme that controls cellular metabolism. The role of PDKs in diverse neurological disorders, including neurometabolic aberrations and neurodegeneration, has been described. Implications for a role of PDKs in inflammation and neurometabolic coupling led us to investigate the effect of genetic ablation of PDK2/4 on nociception in a mouse model of acute inflammatory pain. Deficiency in Pdk2 and/or Pdk4 in mice led to attenuation of formalin-induced nociceptive behaviors (flinching, licking, biting, or lifting of the injected paw). Likewise, the pharmacological inhibition of PDKs substantially diminished the nociceptive responses in the second phase of the formalin test. Furthermore, formalin-provoked paw edema formation and mechanical and thermal hypersensitivities were significantly reduced in Pdk2/4-deficient mice. Formalin-driven neutrophil recruitment at the site of inflammation, spinal glial activation, and neuronal sensitization were substantially lessened in the second or late phase of the formalin test in Pdk2/4-deficient animals. Overall, our results suggest that PDK2/4 can be a potential target for the development of pharmacotherapy for the treatment of acute inflammatory pain. © 2016 Wiley Periodicals, Inc. PMID:26931482
Coping with an acute psychosocial challenge: behavioral and physiological responses in young women.
Directory of Open Access Journals (Sweden)
Carolina Villada
Full Text Available Despite the relevance of behavior in understanding individual differences in the strategies used to cope with stressors, behavioral responses and their relationships with psychobiological changes have received little attention. In this study on young women, we aimed at analyzing the associations among different components of the stress response and behavioral coping using a laboratory psychosocial stressor. The Ethological Coding System for Interviews, as well as neuroendocrine, autonomic and mood parameters, were used to measure the stress response in 34 young women (17 free-cycling women in their early follicular phase and 17 oral contraceptive users subjected to the Trier Social Stress Test (TSST and a control condition in a crossover design. No significant differences in cardiac autonomic, negative mood and anxiety responses to the stressor were observed between the two groups of women. However, women in the follicular phase showed a higher cortisol response and a larger decrease in positive mood during the social stress episode, as well as greater anxiety overall. Interestingly, the amount of displacement behavior exhibited during the speaking task of the TSST was positively related to anxiety levels preceding the test, but negatively related to baseline and stress response values of heart rate. Moreover, the amount of submissive behavior was negatively related to basal cortisol levels. Finally, eye contact and low-aggressiveness behaviors were associated with a worsening in mood. Overall, these findings emphasize the close relationship between coping behavior and psychobiological reactions, as well as the role of individual variations in the strategy of coping with a psychosocial stressor.
Institute of Scientific and Technical Information of China (English)
程昌志; 赵东海; 李全岳; 曲海燕; 陈伯成; 林舟丹
2011-01-01
Objective To explore the risk factors of complication of acute renal failure (ARF) in war injuries of limbs. Methods The clinical data of 352 patients with limb injuries admitted to 303 Hospital of PLA from 1968 to 2002 were retrospectively analyzed. The patients were divided into ARF group (n=9) and non-ARF group ( n=343) according to the occurrence of ARF, and the case-control study was carried out. Ten factors which might lead to death were analyzed by logistic regression to screen the risk factors for ARF,including causes of trauma, shock after injury, time of admission to hospital after injury, injured sites, combined trauma, number of surgical procedures, presence of foreign matters, features of fractures, amputation, and tourniquet time. Results Fifteen of the 352 patients died (4.3％) , among them 7 patients (46.7％) died of ARF, 3 (20.0％) of pulmonary embolism, 3 (20.0 ％) of gas gangrene,and 2 (13.3％) of multiple organ failure. Univariate analysis revealed that the shock, time before admitted to hospital, amputation and tourniquet time were the risk factors for ARF in the wounded with limb injuries, while the logistic regression analysis showed only amputation was the risk factor for ARF ( P＜0.05). Conclusion ARF is the primary cause-of-death in the wounded with limb injury.Prompt and accurate treatment and optimal time for amputation may be beneficial to decreasing the incidence and mortality of ARF in the wounded with severe limb injury and ischemic necrosis.%目的 探讨四肢战创伤并发急性肾衰竭(ARF)的危险因素.方法 回顾性分析1968-2002年收治的352例四肢战创伤患者,根据是否发生ARF将患者分为ARF组(9例)和非ARF组(343例)并进行病例对照研究,选择可能影响患者死亡的10个因素(致伤物、伤后是否休克、伤后入院时间、受伤部位、有无合并伤、手术次数、有否异物存留、骨折性质、是否截肢、止血带时间)进行logistic回归分析,筛
DEFF Research Database (Denmark)
Sickmann, Helle Mark; Skoven, Christian; Arentzen, Tina S.;
, PS blunted this effect. Relative and absolute numbers of rapid eye movement sleep bouts were higher in PS offspring. Moreover, exposure to an acute stressor induced a REM rebound effect in control animals but this compensatory mechanism was blunted in PS animals. Finally, depression-like behavioral...... stress (PS). These include increased helplessness, altered anxiety indicators and sleep modifications. Our purpose was to further investigate behavioral depression indices following PS as well as CNS structural changes including sex specificity of these variables. Pregnant Sprague-Dawley rats were...... in locomotor activity, depressive- and anxiety-like behavior as well as sleep architecture. Some animals were analyzed for CNS microstructural changes based on diffusion MRI. Subsets of PS and control rats were exposed to an acute stressor prior to the behavioral tests. Rearing/climbing activity in a familiar...
Freitas, Kelen C; Carroll, F Ivy; Negus, S Stevens
2015-11-01
Agonists at nicotinic acetylcholine receptors (nAChRs) constitute one drug class being evaluated as candidate analgesics. Previous preclinical studies have implicated α4β2 and α7 nAChRs as potential mediators of the antinociceptive effects of (–)-nicotine hydrogen tartrate (nicotine) and other nAChR agonists; however, these studies have relied exclusively on measures of pain-stimulated behavior, which can be defined as behaviors that increase in frequency, rate, or intensity after presentation of a noxious stimulus. Pain is also associated with depression of many behaviors, and drug effects can differ in assays of pain-stimulated versus pain-depressed behavior. Accordingly, this study compared the effects of nicotine, the selective α4/6β2 agonist 5-(123I)iodo-3-[2(S)-2-azetidinylmethoxy]pyridine (5-I-A-85380), and the selective α7 agonist N-(3R)-1-azabicyclo(2.2.2)oct-3-yl-4-chlorobenzamide in assays of pain-stimulated and pain-depressed behavior in male Sprague-Dawley rats. Intraperitoneal injection of dilute lactic acid served as an acute noxious stimulus to either stimulate a stretching response or depress the operant responding, which is maintained by electrical brain stimulation in an intracranial self-stimulation (ICSS) procedure. Nicotine produced a dose-dependent, time-dependent, and mecamylamine-reversible blockade of both acid-stimulated stretching and acid-induced depression of ICSS. 5-I-A-85380 also blocked both acid-stimulated stretching and acid-induced depression of ICSS, whereas N-(3R)-1-azabicyclo(2.2.2)oct-3-yl-4-chlorobenzamide produced no effect in either procedure. Both nicotine and 5-I-A-85380 were ≥10-fold more potent in blocking the acid-induced depression of ICSS than in blocking the acid-induced stimulation of stretching. These results suggest that stimulation of α4β2 and/or α6β2 nAChRs may be especially effective to alleviate the signs of pain-related behavioral depression in rats; however, nonselective behavioral effects
Zhang, Guang-Fen; Wang, Jing; Han, Jin-Feng; Guo, Jie; Xie, Ze-Min; Pan, Wei; Yang, Jian-Jun; Sun, Kang-Jian
2016-09-19
Both chronic pain and depression are debilitating diseases, which often coexist in clinic. However, current analgesics and antidepressants exhibit limited efficacy for this comorbidity. The present study aimed to investigate the effect of ketamine on the comorbidity of inflammatory pain and consequent depression-like behaviors in a rat model established by intraplantar administration of complete Freunds adjuvant (CFA). The mechanical withdrawal threshold, thermal withdrawal latency, open field test, forced swimming test, and sucrose preference test were evaluated after the CFA injection and ketamine treatment. The hippocampus was harvested to determine the levels of interleukin (IL)-6, IL-1β, indoleamine 2,3-dioxygenase (IDO), kynurenine (KYN), 5-hydroxytryptamine (5-HT), and tryptophan (TRP). The inflammatory pain-induced depression-like behaviors presented on 7days and lasted to at least 14days after the CFA injection. Single dose of ketamine at 20mg/kg relieved both the mechanical allodynia and the associated depression-like behaviors as demonstrated by the attenuated mechanical withdrawal threshold, reduced immobility time in the forced swim test, and increased sucrose preference after ketamine treatment. The total distance had no significant change after the CFA injection or ketamine treatment in the open field test. Simultaneously, ketamine reduced the levels of IL-6, IL-1β, IDO, and KYN/TRP ratio and increased the 5-HT/TRP ratio in the hippocampus. In conclusion, acute single dose of ketamine can rapidly attenuate mechanical allodynia and consequent depression-like behaviors and down-regulate hippocampal proinflammatory responses and IDO/KYN signal pathway in rats. PMID:27497920
Behavioral changes and cholinesterase activity of rats acutely treated with propoxur.
Thiesen, F V; Barros, H M; Tannhauser, M; Tannhauser, S L
1999-01-01
Early assessment of neurological and behavioral effects is extremely valuable for early identification of intoxications because preventive measures can be taken against more severe or chronic toxic consequences. The time course of the effects of an oral dose of the anticholinesterase agent propoxur (8.3 mg/kg) was determined on behaviors displayed in the open-field and during an active avoidance task by rats and on blood and brain cholinesterase activity. Maximum inhibition of blood cholinesterase was observed within 30 min after administration of propoxur. The half-life of enzyme-activity recovery was estimated to be 208.6 min. Peak brain cholinesterase inhibition was also detected between 5 and 30 min of the pesticide administration, but the half-life for enzyme activity recovery was much shorter, in the range of 85 min. Within this same time interval of the enzyme effects, diminished motor and exploratory activities and decreased performance of animals in the active avoidance task were observed. Likewise, behavioral normalization after propoxur followed a time frame similar to that of brain cholinesterase. These data indicate that behavioral changes that occur during intoxication with low oral doses of propoxur may be dissociated from signs characteristic of cholinergic over-stimulation but accompany brain cholinesterase activity inhibition.
Numerical calculation on behavior of fuel regression in hybrid rocket motor%混合火箭发动机燃料退移特性的数值计算
Institute of Scientific and Technical Information of China (English)
单繁立; 侯凌云; 朴英
2011-01-01
混合火箭发动机在航天推进领域优势明显,但由于氧化剂和燃料相态不同,燃料退移的机理和特性比较复杂.采用自行编写的混合火箭发动机程序(HRM)模拟了这种发动机的非稳态工作过程.通过该程序实时数值求解了从氧化剂注入端到尾喷管的全部物理化学过程,并基于燃料表面上气固间的质量和能量耦合,运用燃料表面动态退移和两步计算方法,模拟了燃料退移.在与发动机推力和燃料退移量等实验数据对比的基础上,给出了燃料退移速率方程和燃料退移速率随燃烧室直径的变化规律,确定并分析了影响混合火箭发动机尺度效应的因素.%Hybrid rocket motor has many advantages for space propulsion applications. The mechanism and behavior of the fuel regression in the motor are complicated due to different phase states of the oxidizer and the fuel. The hybrid rocket motor code ( HRM) for the unsteady simulation of motor operation has been programmed. This code can calculate physical and chemical processes from the oxidizer injector to the nozzle during motor operation. The mass and energy coupling between gas and solid phases as well as a dynamic fuel surface regression technique with a two-step calculation method is applied to simulate the fuel regression. The calculated motor thrust and fuel regression are compared to the experimental data for the code validation. The fuel regression rate equation and the relation between fuel regression rate and chamber diameter have been derived. The reasons for scale effect in hybrid rocket motor have been determined and analyzed.
Aldrich, John
2005-01-01
In 1922 R. A. Fisher introduced the modern regression model, synthesizing the regression theory of Pearson and Yule and the least squares theory of Gauss. The innovation was based on Fisher’s realization that the distribution associated with the regression coefficient was unaffected by the distribution of X. Subsequently Fisher interpreted the fixed X assumption in terms of his notion of ancillarity. This paper considers these developments against the background of the development of statisti...
David F. Hendry; Krolzig, Hans Martin
2004-01-01
The controversy over the selection of "growth regressions" was precipitated by some remarkably numerous "estimation" strategies, including two million regressions by Sala-i-Martin [American Economic Review (1997b) Vol. 87, pp. 178-183]. Only one regression is really needed, namely the general unrestricted model, appropriately reduced to a parsimonious encompassing, congruent representation. We corroborate the findings of Hoover and Perez [Oxford Bulletin of Economics and Statistics (2004) Vol...
Introduction to regression graphics
Cook, R Dennis
2009-01-01
Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava
Weisberg, Sanford
2005-01-01
Master linear regression techniques with a new edition of a classic text Reviews of the Second Edition: ""I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression."" -Technometrics, February 1987 ""Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis."" -American Scientist, May-June 1987
Cardel, M I; Johnson, S L; Beck, J; Dhurandhar, E; Keita, A D; Tomczik, A C; Pavela, G; Huo, T; Janicke, D M; Muller, K; Piff, P K; Peters, J C; Hill, J O; Allison, D B
2016-08-01
Both subjective and objectively measured social status has been associated with multiple health outcomes, including weight status, but the mechanism for this relationship remains unclear. Experimental studies may help identify the causal mechanisms underlying low social standing as a pathway for obesity. Our objective was to investigate the effects of experimentally manipulated social status on ad libitum acute dietary intakes and stress-related outcomes as potential mechanisms relating social status and weight. This was a pilot feasibility, randomized, crossover study in Hispanic young adults (n=9; age 19-25; 67% female; BMI ≥18.5 and ≤30kg/m(2)). At visit 1, participants consumed a standardized breakfast and were randomized to a high social status position (HIGH) or low social status position (LOW) in a rigged game of Monopoly™. The rules for the game differed substantially in terms of degree of 'privilege' depending on randomization to HIGH or LOW. Following Monopoly™, participants were given an ad libitum buffet meal and energy intakes (kcal) were estimated by pre- and post-weighing foods consumed. Stress-related markers were measured at baseline, after the game of Monopoly™, and after lunch. Visit 2 used the same standardized protocol; however, participants were exposed to the opposite social status condition. When compared to HIGH, participants in LOW consumed 130 more calories (p=0.07) and a significantly higher proportion of their daily calorie needs in the ad libitum buffet meal (39% in LOW versus 31% in HIGH; p=0.04). In LOW, participants reported decreased feelings of pride and powerfulness following Monopoly™ (p=0.05) and after their lunch meal (p=0.08). Relative to HIGH, participants in LOW demonstrated higher heart rates following Monopoly™ (p=0.06), but this relationship was not significant once lunch was consumed (p=0.31). Our pilot data suggest a possible causal relationship between experimentally manipulated low social status and
Cardel, M I; Johnson, S L; Beck, J; Dhurandhar, E; Keita, A D; Tomczik, A C; Pavela, G; Huo, T; Janicke, D M; Muller, K; Piff, P K; Peters, J C; Hill, J O; Allison, D B
2016-08-01
Both subjective and objectively measured social status has been associated with multiple health outcomes, including weight status, but the mechanism for this relationship remains unclear. Experimental studies may help identify the causal mechanisms underlying low social standing as a pathway for obesity. Our objective was to investigate the effects of experimentally manipulated social status on ad libitum acute dietary intakes and stress-related outcomes as potential mechanisms relating social status and weight. This was a pilot feasibility, randomized, crossover study in Hispanic young adults (n=9; age 19-25; 67% female; BMI ≥18.5 and ≤30kg/m(2)). At visit 1, participants consumed a standardized breakfast and were randomized to a high social status position (HIGH) or low social status position (LOW) in a rigged game of Monopoly™. The rules for the game differed substantially in terms of degree of 'privilege' depending on randomization to HIGH or LOW. Following Monopoly™, participants were given an ad libitum buffet meal and energy intakes (kcal) were estimated by pre- and post-weighing foods consumed. Stress-related markers were measured at baseline, after the game of Monopoly™, and after lunch. Visit 2 used the same standardized protocol; however, participants were exposed to the opposite social status condition. When compared to HIGH, participants in LOW consumed 130 more calories (p=0.07) and a significantly higher proportion of their daily calorie needs in the ad libitum buffet meal (39% in LOW versus 31% in HIGH; p=0.04). In LOW, participants reported decreased feelings of pride and powerfulness following Monopoly™ (p=0.05) and after their lunch meal (p=0.08). Relative to HIGH, participants in LOW demonstrated higher heart rates following Monopoly™ (p=0.06), but this relationship was not significant once lunch was consumed (p=0.31). Our pilot data suggest a possible causal relationship between experimentally manipulated low social status and
Institute of Scientific and Technical Information of China (English)
刘弘; 罗宝章; 吴春峰; 陆冬磊; 邢之慧
2012-01-01
Objective To study acute diarrhea status and risk factors of dietary behavior in Shanghai. Methods A stratified multi-stage cluster random household sampling was used in this cross-sectional survey. Results The incidence rate of acute diarrhea among Shanghai residents was 0. 68 episodes per person-year. It was 0. 75 episodes per person-year for males and 0.62 episodes per person-year for females. It was estimated to be 0.96, 0.54, 0.71, 0.71 and 0.64 episodes per person-year for age groups of 0 - 7 , 8 - 17 , 18 - 33 , 34 - 59 and ≥60, respectively. 24. 34% of respondents suspected their illness was due to contaminated food. 40. 03% of respondents had visited doctor. Single variable and logistic regression analysis showed that odds ratio of acute diarrhea were 1.37 ( 95 % confidence interval, 1. 13 - 1. 67 ) , 0.66 (95% confidence interval, 0.49 -0.88) and 0.76 (95% confidence interval, 0.62 -0.94) for the respondents who had the behavior of eating delicatessen, keeping food at low temperature and salty taste. Conclusion Acute diarrhea is a common illness among residents in Shanghai. The incidence of acute diarrhea was slightly higher in males. After the age of eight, the incidence declined, but increased again in adult and then declined above 60. The behavior of eating delicatessen was a risk factor for acute diarrhea. The habit of keeping the food at low temperature and salty taste might be the protective factors for acute diarrhea.%目的 了解上海市急性腹泻现况及饮食行为危险因素.方法 采用多阶段随机抽样,进行横断面入户问卷调查.结果 上海市居民急性腹泻年发生率0.68次/人年.男性0.75次/人年、女性0.62次/人年,0～7岁、8 ～17岁、18 ～33岁、34 ～59岁、≥60岁分别为0.96、0.54、0.71、0.71、0.64次/人年.有24.34％人自诉有可疑食物史、40.03％的人就诊.单因素及Logistic回归多因素分析显示:食用散装熟食者的急性腹泻OR值为1.37、95％CI (1.13～1.67),
Abdullah, Mishal; Mahowald, Maren L; Frizelle, Sandra P; Dorman, Christopher W; Funkenbusch, Sonia C; Krug, Hollis E
2016-01-01
Arthritis is the most common cause of disability in the US, and the primary manifestation of arthritis is joint pain that leads to progressive physical limitation, disability, morbidity, and increased health care utilization. Capsaicin (CAP) is a vanilloid agonist that causes substance P depletion by interacting with vanilloid receptor transient receptor potential V1 on small unmyelinated C fibers. It has been used topically for analgesia in osteoarthritis with variable success. Resiniferatoxin (RTX) is an ultra potent CAP analog. The aim of this study was to measure the analgesic effects of intra-articular (IA) administration of CAP and RTX in experimental acute inflammatory arthritis in mice. Evoked pain score (EPS) and a dynamic weight bearing (DWB) device were used to measure nociceptive behaviors in a murine model of acute inflammatory monoarthritis. A total of 56 C57B16 male mice underwent EPS and DWB testing – 24 nonarthritic controls and 32 mice with carrageenan-induced arthritis. The effects of pretreatment with 0.1% CAP, 0.0003% RTX, or 0.001% RTX were measured. Nociception was reproducibly demonstrated by increased EPS and reduced DWB measures in the affected limb of arthritic mice. Pretreatment with 0.001% RTX resulted in statistically significant improvement in EPS and DWB measures when compared with those observed in carrageenan-induced arthritis animals. Pretreatment with IA 0.0003% RTX and IA 0.01% CAP resulted in improvement in some but not all of these measures. The remaining 24 mice underwent evaluation following treatment with 0.1% CAP, 0.0003% RTX, or 0.001% RTX, and the results obtained were similar to that of naïve, nonarthritic mice. PMID:27574462
Hung, Chiao-Ling; Huang, Chung-Ju; Tsai, Yu-Jung; Chang, Yu-Kai; Hung, Tsung-Min
2016-01-01
The main purpose of this two-part study was to examine the effects of acute, moderate intensity exercise on task switching in children with attention-deficit/hyperactivity disorder (ADHD). In Study 1, we compared the task switching performance of children with and without ADHD. Twenty children with ADHD and 20 matched controls performed the task switching paradigm, in which the behavioral indices and P3 component of event-related potentials elicited by task-switching were assessed simultaneously. The amplitude and latency of P3 reflected the amount of attention resource allocated to task-relevant stimulus in the environment and the efficiency of stimulus detection and evaluation, respectively. The task switching included two conditions; the pure condition required participants to perform the task on the same rule (e.g., AAAA or BBBB) whereas the mixed condition required participants to perform the task on two alternating rules (e.g., AABBAA…). The results indicated that children with ADHD had significantly longer RTs, less accuracy, and larger global switch cost for accuracy than controls. Additionally, ADHD participants showed smaller amplitudes and longer P3 latencies in global switch effects. In Study 2, we further examined the effects of an acute aerobic exercise session on task switching in children with ADHD. Thirty-four children with ADHD performed a task switching paradigm after 30 min of moderate-intensity aerobic exercise on a treadmill and after control sessions (watching videos while seated). The results revealed that following exercise, children with ADHD exhibited smaller global switch costs in RT compared with after control sessions. The P3 amplitude only increased following exercise in the mixed condition relative to the pure condition, whereas no effects were found in the control session. These findings suggest that single bouts of moderate intensity aerobic exercise may have positive effects on the working memory of children with ADHD. PMID
Flexible survival regression modelling
DEFF Research Database (Denmark)
Cortese, Giuliana; Scheike, Thomas H; Martinussen, Torben
2009-01-01
Regression analysis of survival data, and more generally event history data, is typically based on Cox's regression model. We here review some recent methodology, focusing on the limitations of Cox's regression model. The key limitation is that the model is not well suited to represent time......-varying effects. We start by considering classical and also more recent goodness-of-fit procedures for the Cox model that will reveal when the Cox model does not capture important aspects of the data, such as time-varying effects. We present recent regression models that are able to deal with and describe...... such time-varying effects. The introduced models are all applied to data on breast cancer from the Norwegian cancer registry, and these analyses clearly reveal the shortcomings of Cox's regression model and the need for other supplementary analyses with models such as those we present here....
Mishra, Rachana; Manchanda, Shaffi; Gupta, Muskan; Kaur, Taranjeet; Saini, Vedangana; Sharma, Anuradha; Kaur, Gurcharan
2016-01-01
Sleep deprivation (SD) leads to the spectrum of mood disorders like anxiety, cognitive dysfunctions and motor coordination impairment in many individuals. However, there is no effective pharmacological remedy to negate the effects of SD. The current study examined whether 50% ethanolic extract of Tinospora cordifolia (TCE) can attenuate these negative effects of SD. Three groups of adult Wistar female rats - (1) vehicle treated-sleep undisturbed (VUD), (2) vehicle treated-sleep deprived (VSD) and (3) TCE treated-sleep deprived (TSD) animals were tested behaviorally for cognitive functions, anxiety and motor coordination. TSD animals showed improved behavioral response in EPM and NOR tests for anxiety and cognitive functions, respectively as compared to VSD animals. TCE pretreatment modulated the stress induced-expression of plasticity markers PSA-NCAM, NCAM and GAP-43 along with proteins involved in the maintenance of LTP i.e., CamKII-α and calcineurin (CaN) in hippocampus and PC regions of the brain. Interestingly, contrary to VSD animals, TSD animals showed downregulated expression of inflammatory markers such as CD11b/c, MHC-1 and cytokines along with inhibition of apoptotic markers. This data suggests that TCE alone or in combination with other memory enhancing agents may help in managing sleep deprivation associated stress and improving cognitive functions. PMID:27146164
Institute of Scientific and Technical Information of China (English)
夏斌; 王春丽; 张笋
2013-01-01
Objective To test and verify the regression equation got before for children's dental behavior management problems(BMP).Methods The study group included 279 children aged 2-＜ 8 years who received dental treatment by 16 pediatric dentists in the Department of Pediatric Dentistry,Peking University School of and Hospital of Stomatology.Interviews were conducted with accompanying guardians and children's dental behavior was rated by a modified Venham's clinical anxiety scale and a cooperative behavior rating scale.The variables were put into the regression equation and the results were compared with their dental behavior scale.Results The accuracy rate of regression equation reached 84.2％ (235/279),sensitivity was 0.613(95％CI:0.514-0.712) and specificity was 0.957 (95％CI:0.928-0.986).Conclusions The regression equation is characterized by its accuracy rate at a good level.Younger age,negative guardian expectations of the child's behavior during treatment,anxiety or shyness around strangers,and presence of toothache were four risk factors for children's dental BMP.%目的 检验既往研究获得的口腔诊疗中儿童行为表现预测回归方程的准确性,为该方程在临床的应用提供指导.方法 对北京大学口腔医学院·口腔医院儿童口腔科门诊279名2～＜8岁首次就诊儿童的家长进行问卷调查,并对儿童就诊时的行为表现进行评价记录,将通过问卷调查获得的影响因素代入以往研究所获得的回归方程[logit(P)=-0.884a+1.212b+ 1.063c+0.918d +0.955,P:概率值;a:年龄;b:监护人预测;c:是否存在行为方面的问题;d:是否有牙痛史]进行验证,对得出的预测值与儿童实际行为表现间的异同进行比较.结果 回归方程预测准确率为84.2％(235/279);回归方程的敏感度为0.613(95％ CI:0.514 ～0.712),特异度为0.957(95％ CI:0.928 ～0.986),阳性预测值为0.877(95％CI:0.797 ～0.957),阴性预测值为0.832(95％ CI:0.782 ～0.882).结论 该回归
Hosmer, David W; Sturdivant, Rodney X
2013-01-01
A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-
Weisberg, Sanford
2013-01-01
Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus
Pase, C S; Roversi, Kr; Trevizol, F; Roversi, K; Kuhn, F T; Schuster, A J; Vey, L T; Dias, V T; Barcelos, R C S; Piccolo, J; Emanuelli, T; Bürger, M E
2013-09-01
Because consumption of processed foods has increased in the last decades and so far its potential influence on emotionality and susceptibility to stress is unknown, we studied the influence of different fatty acids (FA) on behavioral and biochemical parameters after acute restrain stress (AS) exposure. Two sequential generations of female rats were supplemented with soybean oil (control group; C-SO), fish oil (FO) and hydrogenated vegetable fat (HVF) from pregnancy and during lactation. At 41days of age, half the animals of each supplemented group were exposed to AS and observed in open field and elevated plus maze task, followed by euthanasia for biochemical assessments. The HVF-supplemented group showed higher anxiety-like symptoms per se, while the C-SO and FO groups did not show these behaviors. Among groups exposed to AS, HVF showed locomotor restlessness in the open field, while both C-SO and HVF groups showed anxiety-like symptoms in the elevated plus maze, but this was not observed in the FO group. Biochemical evaluations showed higher lipoperoxidation levels and lower cell viability in cortex in the HVF group. In addition, HVF-treated rats showed reduced catalase activity in striatum and hippocampus, as well as increased generation of reactive species in striatum, while FO was associated with increased cell viability in the hippocampus. Among groups exposed to AS, HVF increased reactive species generation in the brain, decreased cell viability in the cortex and striatum, and decreased catalase activity in the striatum and hippocampus. Taken together, our findings show that the type of FA provided during development and growth over two generations is able to modify the brain oxidative status, which was particularly adversely affected by trans fat. In addition, the harmful influence of chronic consumption of trans fats as observed in this study can enhance emotionality and anxiety parameters resulting from stressful situations of everyday life, which can
George: Gaussian Process regression
Foreman-Mackey, Daniel
2015-11-01
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
Praptiningsih, Catharina Y; Lafond, Kathryn E; Wahyuningrum, Yunita; Storms, Aaron D; Mangiri, Amalya; Iuliano, Angela D; Samaan, Gina; Titaley, Christiana R; Yelda, Fitra; Kreslake, Jennifer; Storey, Douglas; Uyeki, Timothy M
2016-06-01
Understanding healthcare-seeking patterns for respiratory illness can help improve estimations of disease burden and inform public health interventions to control acute respiratory disease in Indonesia. The objectives of this study were to describe healthcare-seeking behaviors for respiratory illnesses in one rural and one urban community in Western Java, and to explore the factors that affect care seeking. From February 8, 2012 to March 1, 2012, a survey was conducted in 2520 households in the East Jakarta and Bogor districts to identify reported recent respiratory illnesses, as well as all hospitalizations from the previous 12-month period. We found that 4% (10% of those less than 5years) of people had respiratory disease resulting in a visit to a healthcare provider in the past 2weeks; these episodes were most commonly treated at government (33%) or private (44%) clinics. Forty-five people (0.4% of those surveyed) had respiratory hospitalizations in the past year, and just over half of these (24/45, 53%) occurred at a public hospital. Public health programs targeting respiratory disease in this region should account for care at private hospitals and clinics, as well as illnesses that are treated at home, in order to capture the true burden of illness in these communities.
Xiong, Shifeng
2011-01-01
In this paper we discuss the variable selection method from \\ell0-norm constrained regression, which is equivalent to the problem of finding the best subset of a fixed size. Our study focuses on two aspects, consistency and computation. We prove that the sparse estimator from such a method can retain all of the important variables asymptotically for even exponentially growing dimensionality under regularity conditions. This indicates that the best subset regression method can efficiently shri...
Sparse Multivariate Factor Regression
Kharratzadeh, Milad; Coates, Mark
2015-01-01
We consider the problem of multivariate regression in a setting where the relevant predictors could be shared among different responses. We propose an algorithm which decomposes the coefficient matrix into the product of a long matrix and a wide matrix, with an elastic net penalty on the former and an $\\ell_1$ penalty on the latter. The first matrix linearly transforms the predictors to a set of latent factors, and the second one regresses the responses on these factors. Our algorithm simulta...
Multicollinearity in cross-sectional regressions
Lauridsen, Jørgen; Mur, Jesùs
2006-10-01
The paper examines robustness of results from cross-sectional regression paying attention to the impact of multicollinearity. It is well known that the reliability of estimators (least-squares or maximum-likelihood) gets worse as the linear relationships between the regressors become more acute. We resolve the discussion in a spatial context, looking closely into the behaviour shown, under several unfavourable conditions, by the most outstanding misspecification tests when collinear variables are added to the regression. A Monte Carlo simulation is performed. The conclusions point to the fact that these statistics react in different ways to the problems posed.
Directory of Open Access Journals (Sweden)
Seyed Ali Akbar Hedayati
2015-09-01
Full Text Available Background: Diazinon is an organophosphorous pesticide which widely found in municipal, agricultural, and urban storm water discharges. The present study was conducted to achieve lethal concentration (LC50 and behavioral changes of Rutilus rutilus caspius and Hypophthal-micthys molitrix after exposure to lethal concentration of diazinon. Methods: The experiment was carried out in static conditions, based on instructions of OECD in 4 days under controlled water physicochemical conditions with pH of 7.2±0.2, oxygen of 7±0.3 mg/l, total hardness of 180 mg CaCo3 and temperature of 24±1 C°. All fishes were accli-matized in 400 L aquaria for 10 days. Treated aquaria had concentrations of 0.5, 1, 2, 4, 8, 10, 20, 40, 60, and 80 ppm of diazinon for H. molitrix, and 1, 2, 4, 8, 10, and 20 for R. rutilus caspi-cus, while there was no toxic concentration for the control group. LC1, LC10, LC30, LC50, LC70, LC90, and LC99 were calculated for 24, 48, 72, and 96 hours. Results: LC50 96h diazinon values were 3.93 and 1.71 ppm for H. molitrix and R. rutilus caspi-cus, respectively. Clinical observation revealed that the poisoned fishes suffered from nerve paralysis syndrome. The fishes exhibited irregular, erratic, and darting swimming movements, severe aching, and collapse to the bottom of the aquarium. Conclusion: These findings suggest that diazinon has medium toxicity at low concentrations for thede two species and causes morbidities.
Xue, Li-Xia; Zhang, Ting; Zhao, Yu-Wu; Geng, Zhi; CHEN Jing-jiong; Chen, Hao
2016-01-01
Cerebrolysin and DL-3-n-butylphthalide (NBP) have each shown neuroprotective efficacy in preclinical models of acute ischemic stroke (AIS) and passed clinical trials as therapeutic drugs for AIS. The present study was a clinical trial to assess and compare the efficacy and safety of NBP and Cerebrolysin in the reduction of neurological and behavioral disability following AIS. A randomized, double-blind trial was conducted with enrolment of 60 patients within 12 h of AIS. In addition to routin...
Zümrüt Başbakkal; Sibel Sönmez; Nesrin Şen Celasin; Figen Esenay
2010-01-01
The study is executed with mothers of children aged 3-6 (n=170) whose children were hospitalized for the first time between the dates of 15.07.2003 and 15.06.2006, who were reachable by phone and accepted to participate in the study aiming determination of behavioral reactions of a child of 3-6 ages group to be hospitalized due to an acute illness.In this study, for data gathering "Personal Information Form" including 15 questions and "Inquiry Form of Behavior Changes of 3-6 Ages Group Child...
McConnell, Eleanor S; Karel, Michele J
2016-01-01
As the prevalence of Alzheimer disease and related dementias increases, dementia-related behavioral symptoms present growing threats to care quality and safety of older adults across care settings. Behavioral and psychological symptoms of dementia (BPSD) such as agitation, aggression, and resistance to care occur in nearly all individuals over the course of their illness. In inpatient care settings, if not appropriately treated, BPSD can result in care complications, increased length of stay, dissatisfaction with care, and caregiver stress and injury. Although evidence-based, nonpharmacological approaches to treating BPSD exist, their implementation into acute care has been thwarted by limited nursing staff expertise in behavioral health, and a lack of consistent approaches to integrate behavioral health expertise into medically focused inpatient care settings. This article describes the core components of one evidence-based approach to integrating behavioral health expertise into dementia care. This approach, called STAR-VA, was implemented in Veterans' Health Administration community living centers (nursing homes). It has demonstrated effectiveness in reducing the severity and frequency of BPSD, while improving staff knowledge and skills in caring for people with dementia. The potential for adapting this approach in acute care settings is discussed, along with key lessons learned regarding opportunities for nursing leadership to ensure consistent implementation and sustainability. PMID:27259128
[Understanding logistic regression].
El Sanharawi, M; Naudet, F
2013-10-01
Logistic regression is one of the most common multivariate analysis models utilized in epidemiology. It allows the measurement of the association between the occurrence of an event (qualitative dependent variable) and factors susceptible to influence it (explicative variables). The choice of explicative variables that should be included in the logistic regression model is based on prior knowledge of the disease physiopathology and the statistical association between the variable and the event, as measured by the odds ratio. The main steps for the procedure, the conditions of application, and the essential tools for its interpretation are discussed concisely. We also discuss the importance of the choice of variables that must be included and retained in the regression model in order to avoid the omission of important confounding factors. Finally, by way of illustration, we provide an example from the literature, which should help the reader test his or her knowledge.
Aggression and the Risk for Suicidal Behaviors among Children
Greening, Leilani; Stoppelbein, Laura; Luebbe, Aaron; Fite, Paula J.
2010-01-01
Two subtypes of aggression--reactive and proactive--were examined to see how they relate to suicidal behaviors among young children admitted for acute psychiatric inpatient care. The children and their parents completed self-report questionnaires/interviews. Regression analyses revealed that depressed girls who scored higher on reactive aggression…
The role of innate immunity in spontaneous regression of cancer
Directory of Open Access Journals (Sweden)
J A Thomas
2011-01-01
Full Text Available Nature has provided us with infections - acute and chronic - and these infections have both harmful and beneficial effects on the human system. Worldwide, a number of chronic infections are associated with a risk of cancer, but it is also known that cancer regresses when associated with acute infections such as bacterial, viral, fungal, protozoal, etc. Acute infections are known to cure chronic diseases since the time of Hippocrates. The benefits of these fever producing acute infections has been applied in cancer vaccinology such as the Coley′s toxins. Immune cells like the natural killer cells, macrophages and dendritic cells have taken greater precedence in cancer immunity than ever before. This review provides an insight into the benefits of fever and its role in prevention of cancer, the significance of common infections in cancer regression, the dual nature of our immune system and the role of the often overlooked primary innate immunity in tumor immunology and spontaneous regression of cancer.
DEFF Research Database (Denmark)
Bache, Stefan Holst
A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....
Zhuk, Olga; Jasicka-Misiak, Izabela; Poliwoda, Anna; Kazakova, Anastasia; Godovan, Vladlena V.; Halama, Marek; Wieczorek, Piotr P.
2015-01-01
The pharmacological activities and acute toxicity of the psilocin (PC) and dried residues of the crude extracts of psychotropic mushrooms were investigated in mice. The hallucinogenic substances were effectively isolated, by using methanol, from the species of Psilocybe semilanceata and Pholiotina cyanopus, that were collected in the north-east region of Poland. The chemical analysis of these extracts, which was performed by liquid chromatography with mass spectrometry detection (LC-MS), indicated the presence of psilocin and other hallucinogenic substances, including indolealkylamines and their phosphorylated analogues. When the pure psilocin or fungal extracts were used, slight differences in determined LD50 values were observed. However, the application of PC evoked the highest level of toxicity (293.07 mg/kg) compared to the activity of extracts from Ph. cyanopus and P. semilanceata, where the level of LD50 was 316.87 mg/kg and 324.37 mg/kg, respectively. Furthermore, the behavioral test, which considered the head-twitching response (HTR), was used to assess the effects of the studied psychotropic factors on the serotonergic system. Both, the fungal extracts and psilocin evoked characteristic serotoninergic effects depending on the dose administered to mice, acting as an agonist/partial agonist on the serotonergic system. A dose of 200 mg/kg 5-hydroxytryptophan (5-HTP) induced spontaneous head-twitching in mice (100% effect), as a result of the formation of 5-hydroxytryptamine (5-HT) in the brain. Compared to the activity of 5-HTP, the intraperitoneal administration of 1mg/kg of psilocin or hallucinogenic extracts of studied mushrooms (Ph. cyanopus and P. semilanceata) reduced the number of head-twitch responses of about 46% and 30%, respectively. In contrast, the administration of PC exhibited a reduction of about 60% in HTR numbers. PMID:25826052
Directory of Open Access Journals (Sweden)
Olga Zhuk
2015-03-01
Full Text Available The pharmacological activities and acute toxicity of the psilocin (PC and dried residues of the crude extracts of psychotropic mushrooms were investigated in mice. The hallucinogenic substances were effectively isolated, by using methanol, from the species of Psilocybe semilanceata and Pholiotina cyanopus, that were collected in the north-east region of Poland. The chemical analysis of these extracts, which was performed by liquid chromatography with mass spectrometry detection (LC-MS, indicated the presence of psilocin and other hallucinogenic substances, including indolealkylamines and their phosphorylated analogues. When the pure psilocin or fungal extracts were used, slight differences in determined LD50 values were observed. However, the application of PC evoked the highest level of toxicity (293.07 mg/kg compared to the activity of extracts from Ph. cyanopus and P. semilanceata, where the level of LD50 was 316.87 mg/kg and 324.37 mg/kg, respectively. Furthermore, the behavioral test, which considered the head-twitching response (HTR, was used to assess the effects of the studied psychotropic factors on the serotonergic system. Both, the fungal extracts and psilocin evoked characteristic serotoninergic effects depending on the dose administered to mice, acting as an agonist/partial agonist on the serotonergic system. A dose of 200 mg/kg 5-hydroxytryptophan (5-HTP induced spontaneous head-twitching in mice (100% effect, as a result of the formation of 5-hydroxytryptamine (5-HT in the brain. Compared to the activity of 5-HTP, the intraperitoneal administration of 1mg/kg of psilocin or hallucinogenic extracts of studied mushrooms (Ph. cyanopus and P. semilanceata reduced the number of head-twitch responses of about 46% and 30%, respectively. In contrast, the administration of PC exhibited a reduction of about 60% in HTR numbers.
Zhuk, Olga; Jasicka-Misiak, Izabela; Poliwoda, Anna; Kazakova, Anastasia; Godovan, Vladlena V; Halama, Marek; Wieczorek, Piotr P
2015-03-27
The pharmacological activities and acute toxicity of the psilocin (PC) and dried residues of the crude extracts of psychotropic mushrooms were investigated in mice. The hallucinogenic substances were effectively isolated, by using methanol, from the species of Psilocybe semilanceata and Pholiotina cyanopus, that were collected in the north-east region of Poland. The chemical analysis of these extracts, which was performed by liquid chromatography with mass spectrometry detection (LC-MS), indicated the presence of psilocin and other hallucinogenic substances, including indolealkylamines and their phosphorylated analogues. When the pure psilocin or fungal extracts were used, slight differences in determined LD50 values were observed. However, the application of PC evoked the highest level of toxicity (293.07 mg/kg) compared to the activity of extracts from Ph. cyanopus and P. semilanceata, where the level of LD50 was 316.87 mg/kg and 324.37 mg/kg, respectively. Furthermore, the behavioral test, which considered the head-twitching response (HTR), was used to assess the effects of the studied psychotropic factors on the serotonergic system. Both, the fungal extracts and psilocin evoked characteristic serotoninergic effects depending on the dose administered to mice, acting as an agonist/partial agonist on the serotonergic system. A dose of 200 mg/kg 5-hydroxytryptophan (5-HTP) induced spontaneous head-twitching in mice (100% effect), as a result of the formation of 5-hydroxytryptamine (5-HT) in the brain. Compared to the activity of 5-HTP, the intraperitoneal administration of 1mg/kg of psilocin or hallucinogenic extracts of studied mushrooms (Ph. cyanopus and P. semilanceata) reduced the number of head-twitch responses of about 46% and 30%, respectively. In contrast, the administration of PC exhibited a reduction of about 60% in HTR numbers.
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Directory of Open Access Journals (Sweden)
Eliana Peresi
2008-11-01
Full Text Available OBJETIVO: Analisar o padrão de citocinas pró- e antiinflamatórias e da resposta de fase aguda (RFA como marcadores de resposta ao tratamento da tuberculose pulmonar. MÉTODOS: Determinação dos níveis de interferon-gama (IFN-γ, tumor necrosis factor-alpha (TNF-α, fator de necrose tumoral-alfa, interleucina-10 (IL-10 e transforming growth factor-beta (TGF-β, fator transformador de crescimento-beta, pelo método ELISA, em sobrenadante de cultura de células mononucleares do sangue periférico e monócitos, assim como dos níveis de proteínas totais, albumina, globulinas, alfa-1-glicoproteína ácida (AGA, proteína C reativa (PCR e velocidade de hemossedimentação (VHS em 28 doentes com tuberculose pulmonar, em três tempos: antes (T0, aos três meses (T3 e aos seis meses (T6 de tratamento, em relação aos controles saudáveis, em um único tempo. RESULTADOS: Os pacientes apresentaram valores maiores de citocinas e RFA que os controles em T0, com diminuição em T3 e diminuição (TNF-α, IL-10, TGF-β, AGA e VHS ou normalização (IFN-γ e PCR em T6. CONCLUSÕES: PCR, AGA e VHS são possíveis marcadores para auxiliar no diagnóstico de tuberculose pulmonar e na indicação de tratamento de indivíduos com baciloscopia negativa; PCR (T0 > T3 > T6 = referência pode também ser marcador de resposta ao tratamento. Antes do tratamento, o perfil Th0 (IFN-γ, IL-10, TNF-α e TGF-β, indutor de e protetor contra inflamação, prevaleceu nos pacientes; em T6, prevaleceu o perfil Th2 (IL-10, TNF-α e TGF-β, protetor contra efeito nocivo pró-inflamatório do TNF-α ainda presente. O comportamento do IFN-γ (T0 > T3 > T6 = controle sugere sua utilização como marcador de resposta ao tratamento.OBJECTIVE: To evaluate the pattern of pro-inflammatory cytokines, anti-inflammatory cytokines and the acute phase response (APR as markers of the response to treatment of pulmonary tuberculosis. METHODS: Twenty-eight patients with pulmonary tuberculosis
Caporino, Nicole E; Herres, Joanna; Kendall, Philip C; Wolk, Courtney Benjamin
2016-08-01
This study evaluated the impact of dysregulation across cognitive, affective, and behavioral domains on acute and 7- to 19-year follow-up outcomes of cognitive-behavioral therapy (CBT) for anxiety, and explored dysregulation as a predictor of psychopathology and impairment in young adulthood among individuals who received anxiety treatment as youth. Participants (N = 64; 50 % female, 83 % non-Hispanic White) from two randomized clinical trials completed a follow-up assessment 7-19 years later. Latent profile analysis identified dysregulation based on Anxious/Depressed, Attention Problems, and Aggressive Behavior scores on the Child Behavior Checklist. Although pretreatment dysregulation was not related to acute or follow-up outcomes for anxiety diagnoses that were the focus of treatment, dysregulation predicted an array of non-targeted psychopathology at follow-up. Among youth with a principal anxiety disorder, the effects of CBT (Coping Cat) appear to be robust against broad impairments in self-regulation. However, youth with a pretreatment dysregulation profile likely need follow-up to monitor for the emergence of other disorders.
Caporino, Nicole E; Herres, Joanna; Kendall, Philip C; Wolk, Courtney Benjamin
2016-08-01
This study evaluated the impact of dysregulation across cognitive, affective, and behavioral domains on acute and 7- to 19-year follow-up outcomes of cognitive-behavioral therapy (CBT) for anxiety, and explored dysregulation as a predictor of psychopathology and impairment in young adulthood among individuals who received anxiety treatment as youth. Participants (N = 64; 50 % female, 83 % non-Hispanic White) from two randomized clinical trials completed a follow-up assessment 7-19 years later. Latent profile analysis identified dysregulation based on Anxious/Depressed, Attention Problems, and Aggressive Behavior scores on the Child Behavior Checklist. Although pretreatment dysregulation was not related to acute or follow-up outcomes for anxiety diagnoses that were the focus of treatment, dysregulation predicted an array of non-targeted psychopathology at follow-up. Among youth with a principal anxiety disorder, the effects of CBT (Coping Cat) appear to be robust against broad impairments in self-regulation. However, youth with a pretreatment dysregulation profile likely need follow-up to monitor for the emergence of other disorders. PMID:26384978
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Miriam Kron
2014-09-01
Full Text Available Reduced levels of brain-derived neurotrophic factor (BDNF are thought to contribute to the pathophysiology of Rett syndrome (RTT, a severe neurodevelopmental disorder caused by loss-of-function mutations in the gene encoding methyl-CpG-binding protein 2 (MeCP2. In Mecp2 mutant mice, BDNF deficits have been associated with breathing abnormalities, a core feature of RTT, as well as with synaptic hyperexcitability within the brainstem respiratory network. Application of BDNF can reverse hyperexcitability in acute brainstem slices from Mecp2-null mice, suggesting that therapies targeting BDNF or its receptor, TrkB, could be effective at acute reversal of respiratory abnormalities in RTT. Therefore, we examined the ability of LM22A-4, a small-molecule BDNF loop-domain mimetic and TrkB partial agonist, to modulate synaptic excitability within respiratory cell groups in the brainstem nucleus tractus solitarius (nTS and to acutely reverse abnormalities in breathing at rest and during behavioral arousal in Mecp2 mutants. Patch-clamp recordings in Mecp2-null brainstem slices demonstrated that LM22A-4 decreases excitability at primary afferent synapses in the nTS by reducing the amplitude of evoked excitatory postsynaptic currents and the frequency of spontaneous and miniature excitatory postsynaptic currents. In vivo, acute treatment of Mecp2-null and -heterozygous mutants with LM22A-4 completely eliminated spontaneous apneas in resting animals, without sedation. Moreover, we demonstrate that respiratory dysregulation during behavioral arousal, a feature of human RTT, is also reversed in Mecp2 mutants by acute treatment with LM22A-4. Together, these data support the hypothesis that reduced BDNF signaling and respiratory dysfunction in RTT are linked, and establish the proof-of-concept that treatment with a small-molecule structural mimetic of a BDNF loop domain and a TrkB partial agonist can acutely reverse abnormal breathing at rest and in response to
Low rank Multivariate regression
Giraud, Christophe
2010-01-01
We consider in this paper the multivariate regression problem, when the target regression matrix $A$ is close to a low rank matrix. Our primary interest in on the practical case where the variance of the noise is unknown. Our main contribution is to propose in this setting a criterion to select among a family of low rank estimators and prove a non-asymptotic oracle inequality for the resulting estimator. We also investigate the easier case where the variance of the noise is known and outline that the penalties appearing in our criterions are minimal (in some sense). These penalties involve the expected value of the Ky-Fan quasi-norm of some random matrices. These quantities can be evaluated easily in practice and upper-bounds can be derived from recent results in random matrix theory.
ON INTERVAL ESTIMATING REGRESSION
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Marcin Michalak
2014-06-01
Full Text Available This paper presents a new look on the well-known nonparametric regression estimator – the Nadaraya-Watson kernel estimator. Though it was invented 50 years ago it still being applied in many fields. After these yearsfoundations of uncertainty theory – interval analysis – are joined with this estimator. The paper presents the background of Nadaraya-Watson kernel estimator together with the basis of interval analysis and shows the interval Nadaraya-Watson kernel estimator.
Sparse Bilinear Logistic Regression
Shi, Jianing V.; Xu, Yangyang; Baraniuk, Richard G.
2014-01-01
In this paper, we introduce the concept of sparse bilinear logistic regression for decision problems involving explanatory variables that are two-dimensional matrices. Such problems are common in computer vision, brain-computer interfaces, style/content factorization, and parallel factor analysis. The underlying optimization problem is bi-convex; we study its solution and develop an efficient algorithm based on block coordinate descent. We provide a theoretical guarantee for global convergenc...
TWO REGRESSION CREDIBILITY MODELS
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Constanţa-Nicoleta BODEA
2010-03-01
Full Text Available In this communication we will discuss two regression credibility models from Non – Life Insurance Mathematics that can be solved by means of matrix theory. In the first regression credibility model, starting from a well-known representation formula of the inverse for a special class of matrices a risk premium will be calculated for a contract with risk parameter θ. In the next regression credibility model, we will obtain a credibility solution in the form of a linear combination of the individual estimate (based on the data of a particular state and the collective estimate (based on aggregate USA data. To illustrate the solution with the properties mentioned above, we shall need the well-known representation theorem for a special class of matrices, the properties of the trace for a square matrix, the scalar product of two vectors, the norm with respect to a positive definite matrix given in advance and the complicated mathematical properties of conditional expectations and of conditional covariances.
Li, Xiang; Li, Xu; Li, Yi-Xiang; Zhang, Yuan; Chen, Di; Sun, Ming-Zhu; Zhao, Xin; Chen, Dong-Yan; Feng, Xi-Zeng
2015-01-01
We describe an interdisciplinary comparison of the effects of acute and chronic alcohol exposure in terms of their disturbance of light, dark and color preferences and the occurrence of Parkinson-like behavior in zebrafish through computer visual tracking, data mining, and behavioral and physiological analyses. We found that zebrafish in anxiolytic and anxious states, which are induced by acute and chronic repeated alcohol exposure, respectively, display distinct emotional reactions in light/dark preference tests as well as distinct learning and memory abilities in color-enhanced conditional place preference (CPP) tests. Additionally, compared with the chronic alcohol (1.0%) treatment, acute alcohol exposure had a significant, dose-dependent effect on anxiety, learning and memory (color preference) as well as locomotive activities. Acute exposure doses (0.5%, 1.0%, and 1.5%) generated an "inverted V" dose-dependent pattern in all of the behavioral parameters, with 1.0% having the greatest effect, while the chronic treatment had a moderate effect. Furthermore, by measuring locomotive activity, learning and memory performance, the number of dopaminergic neurons, tyrosine hydroxylase expression, and the change in the photoreceptors in the retina, we found that acute and chronic alcohol exposure induced varying degrees of Parkinson-like symptoms in zebrafish. Taken together, these results illuminated the behavioral and physiological mechanisms underlying the changes associated with learning and memory and the cause of potential Parkinson-like behaviors in zebrafish due to acute and chronic alcohol exposure. PMID:26558894
Zhang, Feipeng; Li, Qunhua
2016-01-01
We introduce a rank-based bent linear regression with an unknown change point. Using a linear reparameterization technique, we propose a rank-based estimate that can make simultaneous inference on all model parameters, including the location of the change point, in a computationally efficient manner. We also develop a score-like test for the existence of a change point, based on a weighted CUSUM process. This test only requires fitting the model under the null hypothesis in absence of a chang...
Adaptive Metric Kernel Regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression by...... minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...
Adaptive metric kernel regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
2000-01-01
Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the...
Otsuka, Tomomi; Nishii, Ayu; Amemiya, Seiichiro; Kubota, Natsuko; Nishijima, Takeshi; Kita, Ichiro
2016-02-01
Accumulating evidence suggests that physical exercise can reduce and prevent the incidence of stress-related psychiatric disorders, including depression and anxiety. Activation of serotonin (5-HT) neurons in the dorsal raphe nucleus (DRN) is implicated in antidepressant/anxiolytic properties. In addition, the incidence and symptoms of these disorders may involve dysregulation of the hypothalamic-pituitary-adrenal axis that is initiated by corticotropin-releasing factor (CRF) neurons in the hypothalamic paraventricular nucleus (PVN). Thus, it is possible that physical exercise produces its antidepressant/anxiolytic effects by affecting these neuronal activities. However, the effects of acute physical exercise at different intensities on these neuronal activation and behavioral changes are still unclear. Here, we examined the activities of 5-HT neurons in the DRN and CRF neurons in the PVN during 30 min of treadmill running at different speeds (high speed, 25 m/min; low speed, 15m/min; control, only sitting on the treadmill) in male Wistar rats, using c-Fos/5-HT or CRF immunohistochemistry. We also performed the elevated plus maze test and the forced swim test to assess anxiety- and depressive-like behaviors, respectively. Acute treadmill running at low speed, but not high speed, significantly increased c-Fos expression in 5-HT neurons in the DRN compared to the control, whereas high-speed running significantly enhanced c-Fos expression in CRF neurons in the PVN compared with the control and low-speed running. Furthermore, low-speed running resulted in decreased anxiety- and depressive-like behaviors compared with high-speed running. These results suggest that acute physical exercise with mild and low stress can efficiently induce optimal neuronal activation that is involved in the antidepressant/anxiolytic effects. PMID:26542811
Nesrin Şen Celasin; Sibel Sönmez; Zümrüt Başbakkal; Figen Esenay
2010-01-01
The study is executed with mothers of children aged 3-6 (n=170) whose children were hospitalized for the first time between the dates of 15.07.2003 and 15.06.2006, who were reachable by phone and accepted to participate in the study aiming determination of behavioral reactions of a child of 3-6 ages group to be hospitalized due to an acute illness.In this study, for data gathering "Personal Information Form" including 15 questions and "Inquiry Form of Behavior Changes of 3-6 Ages Group Child...
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Karim Hardani*
2012-05-01
Full Text Available A 10-month-old baby presented with developmental delay. He had flaccid paralysis on physical examination.An MRI of the spine revealed malformation of the ninth and tenth thoracic vertebral bodies with complete agenesis of the rest of the spine down that level. The thoracic spinal cord ends at the level of the fifth thoracic vertebra with agenesis of the posterior arches of the eighth, ninth and tenth thoracic vertebral bodies. The roots of the cauda equina appear tightened down and backward and ended into a subdermal fibrous fatty tissue at the level of the ninth and tenth thoracic vertebral bodies (closed meningocele. These findings are consistent with caudal regression syndrome.
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Tydén Patrik
2011-07-01
Full Text Available Abstract Background Psychosocial stress has been identified as a risk factor in association with cardiovascular disease but less attention has been paid to heterogeneity in vulnerability to stress. The serial Color Word Test (CWT measures adaptation to a stressful situation and it can be used to identify individuals that are vulnerable to stress. Prospective studies have shown that individuals with a maladaptive behavior in this test are exposed to an increased risk of future cardiovascular events. The aim of the present study was to investigate whether maladaptive behavior in the serial CWT alone or in combination with any specific personality dimension was associated with severity of myocardial infarction (MI. Methods MI-patients (n = 147 completed the test and filled in a personality questionnaire in close proximity to the acute event. The results were analyzed in association with four indicators of severity: maximum levels above median of the cardiac biomarkers troponin I and creatine kinase-MB (CKMB, Q-wave infarctions, and a left ventricular ejection fraction (LVEF ≤ 50%. Results Maladaptive behavior in the serial CWT together with low scores on extraversion were associated with maximum levels above median of cardiac troponin I (OR 2.97, CI 1.08-8.20, p = 0.04 and CKMB (OR 3.33, CI 1.12-9.93, p = 0.03. No associations were found between the combination maladaptive behavior and low scores on extraversion and Q-wave infarctions or a decreased LVEF. Conclusions Maladaptive behavior in combination with low scores on extraversion is associated with higher cardiac biomarker levels following an MI. The serial CWT and personality questionnaires could be used to identify individuals vulnerable to the hazardous effects of stress and thereby are exposed to an increased risk of a more severe infarction.
Green, Nella; Hoenigl, Martin; Morris, Sheldon; Little, Susan J
2015-10-01
The transgender community represents an understudied population in the literature. The objective of this study was to compare risk behavior, and HIV and sexually transmitted infection (STI) rates between transgender women and transgender men undergoing community-based HIV testing.With this retrospective analysis of a cohort study, we characterize HIV infection rates as well as reported risk behaviors and reported STI in 151 individual transgender women and 30 individual transgender men undergoing community based, voluntary screening for acute and early HIV infection (AEH) in San Diego, California between April 2008 and July 2014.HIV positivity rate was low for both, transgender women and transgender men undergoing AEH screening (2% and 3%, respectively), and the self-reported STI rate for the prior 12 months was 13% for both. Although transgender women appeared to engage in higher rates of risk behavior overall, with 69% engaged in condomless receptive anal intercourse (CRAI) and 11% engaged in sex work, it is important to note that 91% of transgender women reported recent sexual intercourse, 73% had more than 1 sexual partner, 63% reported intercourse with males, 37% intercourse with males and females, and 30% had CRAI.Our results indicate that in some settings rates of HIV infection, as well as rates of reported STIs and sexual risk behavior in transgender men may resemble those found in transgender women. Our findings support the need for comprehensive HIV prevention in both, transgender women and men. PMID:26469928
Sulakhiya, Kunjbihari; Patel, Vikas Kumar; Saxena, Rahul; Dashore, Jagrati; Srivastava, Amit Kumar; Rathore, Manoj
2016-01-01
Background: Stress plays a significant role in the pathogenesis of neuropsychiatric disorders such as anxiety and depression. Beta vulgaris is commonly known as “beet root” possessing antioxidant, anticancer, hepatoprotective, nephroprotective, wound healing, and anti-inflammatory properties. Objective: To study the protective effect of Beta vulgaris Linn. ethanolic extract (BVEE) of leaves against acute restraint stress (ARS)-induced anxiety- and depressive-like behavior and oxidative stress in mice. Materials and Methods: Mice (n = 6) were pretreated with BVEE (100 and 200 mg/kg, p. o.) for 7 days and subjected to ARS for 6 h to induce behavioral and biochemical changes. Anxiety- and depressive-like behavior were measured by using different behavioral paradigms such as open field test (OFT), elevated plus maze (EPM), forced swim test (FST), and tail suspension test (TST) 40 min postARS. Brain homogenate was used to analyze oxidative stress parameters, that is, malondialdehyde (MDA) and reduced glutathione (GSH) level. Results: BVEE pretreatment significantly (P < 0.05) reversed the ARS-induced reduction in EPM parameters, that is, percentage entries and time spent in open arms and in OFT parameters, that is, line crossings, and rearings in mice. ARS-induced increase in the immobility time in FST and TST was attenuated significantly (P < 0.05) by BVEE pretreatment at both the dosage. An increase in MDA and depletion of GSH level postARS was prevented significantly (P < 0.05) with BVEE pretreatment at both the dosage (100 and 200 mg/kg). Conclusion: BVEE exhibits anxiolytic and antidepressant activity in stressed mice along with good antioxidant property suggesting its therapeutic potential in the treatment of stress-related psychiatric disorders. SUMMARY Stress plays major role in the pathogenesis of anxiety and depressionARS-induced anxiety- and depressive-like behavior through oxidative damage in miceBVEE pretreatment reversed ARS-induced behavioral changes
Regression Analysis A Constructive Critique
Berk, Richard A
2003-01-01
Regression Analysis: A Constructive Critique identifies a wide variety of problems with regression analysis as it is commonly used and then provides a number of ways in which practice could be improved. Regression is most useful for data reduction, leading to relatively simple but rich and precise descriptions of patterns in a data set. The emphasis on description provides readers with an insightful rethinking from the ground up of what regression analysis can do, so that readers can better match regression analysis with useful empirical questions and improved policy-related research. "An
Combining Alphas via Bounded Regression
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Zura Kakushadze
2015-11-01
Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.
Institute of Scientific and Technical Information of China (English)
刘鹏; 白亚娜; 胡晓斌; 毛宝宏; 王辉; 孙仙; 靳利梅; 祝意
2013-01-01
Objective To investigate influential factors of smoking behavior among urban residents in Lanzhou city and to provide reference for preventing urban residents from smoking. Methods With cluster sampling method,1 072 urban residents aged 15 years and over were selected from two communities of Lanzhou and investigated with a questionnaire. Logistic regression was used to analysze influential factors of smoking. Results The smoking rate among the residents was 34. 14% (55.07% for male and 3.02% for female) and 24. 72% of the residents smoked every day. The influencing factors of smoking in the residents were gender, whether paying attention to people smoking around, familial income of last year,and the awareness of tobacco advertisements in previous 6 months. Conclusion Male population is still the key group for tobacco control in Lanzhou city. We should strengthen the laws against smoking ads to carry out tobacco control intervention.%目的 了解甘肃省兰州市城市居民吸烟现状及其吸烟行为影响因素,为社区居民吸烟行为干预提供依据.方法 按照分层随机抽样方法,选择兰州市2个社区作为研究现场,对1072名年龄≥15岁的社区居民进行问卷调查.结果 兰州市城市居民吸烟率为34.14％ (366/1072),其中男性吸烟率为55.07％ (353/641),女性吸烟率为3.02％(13/431)；24.72％ (265/1072)的居民每天都吸烟,9.42％(101/1072)的居民只在某些天吸烟,65.86％ (706/1072)的居民不吸烟；城市居民吸烟行为的影响因素有性别、是否介意别人在身边吸烟、去年1年家庭收入、近半年来是否看到过香烟广告.结论 男性群体仍旧是甘肃省控烟工作的重点人群；加大禁止吸烟广告的力度对控烟干预工作具有重要意义.
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Leopoldo Soares Piegas
2013-01-01
ão ajudar a promover um melhor planejamento e manejo do atendimento da síndrome coronariana aguda a nível público e privado.BACKGROUND: Brazil lacks published multicenter registries of acute coronary syndrome. OBJECTIVE: The Brazilian Registry of Acute Coronary Syndrome is a multicenter national study aiming at providing data on clinical aspects, management and hospital outcomes of acute coronary syndrome in our country. METHODS: A total of 23 hospitals from 14 cities, participated in this study. Eligible patients were those who came to the emergency wards with suspected acute coronary syndrome within the first 24 hours of symptom onset, associated with compatible electrocardiographic alterations and/or altered necrosis biomarkers. Follow-up lasted until hospital discharge or death, whichever occurred first. RESULTS: Between 2003 and 2008, 2,693 ACS patients were enrolled, of which 864 (32.1% were females. T he final diagnosis was unstable angina in 1,141 patients, (42.4%, with a mortality rate of 3.06%, non-ST elevation acute myocardial infarction (AMI in 529 (19.6%, with mortality of 6.8%, ST-elevation AMI 950 (35.3%, with mortality of 8.1% and non-confirmed diagnosis 73 (2.7%, with mortality of 1.36%. The overall mortality was 5.53%. The multiple logistic regression model identified the following as risk factors for death regarding demographic factors and interventions: female gender (OR=1.45, diabetes mellitus (OR=1.59, body mass index (OR=1.27 and percutaneous coronary intervention (OR=0.70. A second model for death due to major complications identified: cardiogenic shock/acute pulmonary edema (OR=4.57, reinfarction (OR=3.48, stroke (OR=21.56, major bleeding (OR=3.33, cardiopulmonary arrest (OR=40.27 and Killip functional class (OR=3.37. CONCLUSION: The Brazilian Registry of Acute Coronary Syndrome data do not differ from other data collected abroad. The understanding of their findings may help promote better planning and management of acute coronary syndrome care
Institute of Scientific and Technical Information of China (English)
席翼; 周泉; 刘朝霞
2015-01-01
Objective :To grasp the prevalence situation of primary and secondary school students’ obesity of Shenzhen and to study the dangerous factors resulted in obesity in order to provide the basis for further preventing and controlling the students’ obesity .Methods :The“BMI classification reference for screening overweight and obesity in Chinese school‐age chil‐dren and adolescents proposed by Working Group on Obesity in China (WGOC )”was used to screen the 3 833 primary school and secondary school students at the age of 8‐16 years in Shenzhen .Among which 195 obese students were picked out to form an “ obesity group” , while another 195 students were chosen to form the “control group” .The behavior factors of the two groups were investigated by the method of closed questionnaire (48 items ) and two rounds analysis were made by using single factor χ2 test and non conditional logistic regression model .Results and Conclusion :7 important factors which were recognized the main reasons re‐sulted in the primary and secondary school students’ obesity were selected :how to describe one’s body weight ,how to control body weight ,the living condition ,time of community sports activities ,mother’ s education level ,how long snacks before bedtime ,the amount of food to eat .That is the main reason causing the behavior of primary and middle school students obesi‐ty .Among them ,the living conditions ,education level of mother ,and body weight describation have not been reported in the previous studies .%研究目的：掌握深圳市中、小学学生肥胖的流行情况，探讨导致肥胖的行为危险因素，为进一步预防与控制学生肥胖提供依据。研究方法：采用中国肥胖问题工作组推出的“中国学龄儿童青少年超重、肥胖筛查BMI值分类标准”，对深圳3833名8～17岁普通学生筛查，确定肥胖学生195名，并选定对照组195名，对肥胖组和对照组的390人
An Application on Multinomial Logistic Regression Model
Abdalla M El-Habil
2012-01-01
This study aims to identify an application of Multinomial Logistic Regression model which is one of the important methods for categorical data analysis. This model deals with one nominal/ordinal response variable that has more than two categories, whether nominal or ordinal variable. This model has been applied in data analysis in many areas, for example health, social, behavioral, and educational.To identify the model by practical way, we used real data on physical violence against children...
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Zümrüt Başbakkal
2010-02-01
Full Text Available The study is executed with mothers of children aged 3-6 (n=170 whose children were hospitalized for the first time between the dates of 15.07.2003 and 15.06.2006, who were reachable by phone and accepted to participate in the study aiming determination of behavioral reactions of a child of 3-6 ages group to be hospitalized due to an acute illness.In this study, for data gathering "Personal Information Form" including 15 questions and "Inquiry Form of Behavior Changes of 3-6 Ages Group Children After Being Hospitalized" with 30 questions were used. Date gathering forms were carried out as pre-test by using face-to-face interview method with mothers of 3-6 aged children who were hospitalized for the first time and were in first 12 hours of hospitalization. "Inquiry Form of Behavior Changes of 3-6 Ages Group Children After Being Hospitalized" was re-carried out with mothers by phone 1 month after children being discharged from hospital.In analyzing of datas statistical programme of SPSS 13.0 for Windows was used. In statistical evaluation; number-percent dispersion, Wilcoxon Sing Rank test and Paired Sample-t test were used.According to the results obtained from the study, 57.6% of children are male with age average of 4,46±1,18 and 52.3% of them were hospitalized due to Gastroentestinal System Illnesses. A significant difference was determined between average points of behavior changes of 3-6 ages group children hospitalized due to an acute illness before hospitalized (10,735±4,882 and after being discharged from hospital (15,0476±4,306. In the study, it is observed that there are some behavioral changes in children after being hospitalized such as being cranky before going to bed and during eating, disquiet, bed-wetting, seperation anxiety, excessive attachment to a parent, to need help even for the things he/she could accomplish, to have fear from new environments, people or objects, bad temper attacks, fear of doctor/nurse and hospital
Directory of Open Access Journals (Sweden)
Mohammad Abu Basma Rajeh
2012-01-01
Full Text Available Background: The methanol extract of Euphorbia hirta L (Euphorbiaceae, which is used in traditional medicines, was tested for in vivo toxicity. Materials and Methods: In vivo brine shrimp lethality assay and oral acute toxicity study at single high dose of 5000 mg/kg and observation for 14 days in mice were used to study the toxic effect of E. hirta. Results: Brine shrimp lethality assay was used to calculate the median lethal concentration (LC 50 of E. hirta (for leaves, stems, flowers and roots methanolic extracts at concentrations from 100 to 0.07 mg/ml. The LC 50 values of 1.589, 1.420, 0.206 and 0.0827 mg/ml were obtained for stems, leaves, flowers and roots, respectively. Potassium dichromate (the positive control had LC 50 value of 0.00758 mg/ml. The acute oral toxicity study of the leaf extract resulted in one third mortality and mild behavioral changes among the treated mice. No significant statistical differences found between body weight, relative (% and absolute (g organ weights of treated and untreated groups (P> 0.05. Gross and microscopic examination of the vital organ tissues revealed no differences between control and treated mice. All the tissues appeared normal. Conclusions : E. hirta leaves methanol extract has exhibited mild toxic effects in mice.
Polynomial Regression on Riemannian Manifolds
Hinkle, Jacob; Fletcher, P Thomas; Joshi, Sarang
2012-01-01
In this paper we develop the theory of parametric polynomial regression in Riemannian manifolds and Lie groups. We show application of Riemannian polynomial regression to shape analysis in Kendall shape space. Results are presented, showing the power of polynomial regression on the classic rat skull growth data of Bookstein as well as the analysis of the shape changes associated with aging of the corpus callosum from the OASIS Alzheimer's study.
Regression Testing Cost Reduction Suite
Mohamed Alaa El-Din; Ismail Abd El-Hamid Taha; Hesham El-Deeb
2014-01-01
The estimated cost of software maintenance exceeds 70 percent of total software costs [1], and large portion of this maintenance expenses is devoted to regression testing. Regression testing is an expensive and frequently executed maintenance activity used to revalidate the modified software. Any reduction in the cost of regression testing would help to reduce the software maintenance cost. Test suites once developed are reused and updated frequently as the software evolves. As a result, some...
Kako, Shinichi; Akahoshi, Yu; Harada, Naonori; Nakano, Hirofumi; Kameda, Kazuaki; Ugai, Tomotaka; Wada, Hidenori; Yamasaki, Ryoko; Ishihara, Yuko; Kawamura, Koji; Sakamoto, Kana; Sato, Miki; Ashizawa, Masahiro; Terasako-Saito, Kiriko; Kimura, Shun-ichi; Kikuchi, Misato; Nakasone, Hideki; Yamazaki, Rie; Kanda, Junya; Nishida, Junji; Kanda, Yoshinobu
2016-01-01
The effects of intensive regimens and the roles of drugs used might differ between T- and B-lineage acute lymphoblastic leukemia (ALL). We performed a literature search for clinical studies published from January 1998 to March 2013. Studies were eligible for inclusion in the analyses if they included more than 80 patients with adult ALL who were treated with a uniform regimen and compared T- and B-lineage ALL. Studies that included only adolescent or elderly patients were excluded. We identified 11 clinical studies, which included a total of 381 and 1366 patients with T- and B-lineage ALL, respectively, and performed meta-analyses using the selected studies. Nine studies included patients with Philadelphia chromosome-positive (Ph+) ALL. A meta-analysis using the random-effect model demonstrated superior survival in patients with T-lineage ALL compared to those with B-lineage ALL (hazard ratio 1.78, 95 % confidence interval 1.50-2.11), though the inclusion of patients with Ph+ ALL in B-lineage ALL must have influenced this result strongly. We performed meta-regression analyses, adjusted according to whether or not patients with Ph+ ALL were included in each study. Use of dexamethasone (Dex), higher dose of methotrexate (MTX), and higher dose of L-asparaginase (L-asp) were associated with a significant trend toward a better outcome in T-lineage ALL. A meta-regression analysis including Dex and the dose of L-asp or MTX together as covariates showed that these factors were independently significant. In conclusion, the use of Dex and high-dose L-asp or MTX may improve the outcome of T-lineage ALL. This hypothesis should be tested in a prospective study including only patients with Ph-negative ALL.
Time-adaptive quantile regression
DEFF Research Database (Denmark)
Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik
2008-01-01
An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power...
Business applications of multiple regression
Richardson, Ronny
2015-01-01
This second edition of Business Applications of Multiple Regression describes the use of the statistical procedure called multiple regression in business situations, including forecasting and understanding the relationships between variables. The book assumes a basic understanding of statistics but reviews correlation analysis and simple regression to prepare the reader to understand and use multiple regression. The techniques described in the book are illustrated using both Microsoft Excel and a professional statistical program. Along the way, several real-world data sets are analyzed in deta
Quantile regression theory and applications
Davino, Cristina; Vistocco, Domenico
2013-01-01
A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and
Directory of Open Access Journals (Sweden)
Kunjbihari Sulakhiya
2016-01-01
Full Text Available Background: Stress plays a significant role in the pathogenesis of neuropsychiatric disorders such as anxiety and depression. Beta vulgaris is commonly known as "beet root" possessing antioxidant, anticancer, hepatoprotective, nephroprotective, wound healing, and anti-inflammatory properties. Objective: To study the protective effect of Beta vulgaris Linn. ethanolic extract (BVEE of leaves against acute restraint stress (ARS-induced anxiety- and depressive-like behavior and oxidative stress in mice. Materials and Methods: Mice (n = 6 were pretreated with BVEE (100 and 200 mg/kg, p. o. for 7 days and subjected to ARS for 6 h to induce behavioral and biochemical changes. Anxiety- and depressive-like behavior were measured by using different behavioral paradigms such as open field test (OFT, elevated plus maze (EPM, forced swim test (FST, and tail suspension test (TST 40 min postARS. Brain homogenate was used to analyze oxidative stress parameters, that is, malondialdehyde (MDA and reduced glutathione (GSH level. Results: BVEE pretreatment significantly (P < 0.05 reversed the ARS-induced reduction in EPM parameters, that is, percentage entries and time spent in open arms and in OFT parameters, that is, line crossings, and rearings in mice. ARS-induced increase in the immobility time in FST and TST was attenuated significantly (P < 0.05 by BVEE pretreatment at both the dosage. An increase in MDA and depletion of GSH level postARS was prevented significantly (P < 0.05 with BVEE pretreatment at both the dosage (100 and 200 mg/kg. Conclusion: BVEE exhibits anxiolytic and antidepressant activity in stressed mice along with good antioxidant property suggesting its therapeutic potential in the treatment of stress-related psychiatric disorders.
Fisette, Alexandre; Fernandes, Maria F.; Hryhorczuk, Cécile; Poitout, Vincent; Alquier, Thierry; Fulton, Stephanie
2016-01-01
Background: GPR120 (FFAR4) is a G-protein coupled receptor implicated in the development of obesity and the antiinflammatory and insulin-sensitizing effects of omega-3 (ω-3) polyunsaturated fatty acids. Increasing central ω-3 polyunsaturated fatty acid levels has been shown to have both anorectic and anxiolytic actions. Despite the strong clinical interest in GPR120, its role in the brain is largely unknown, and thus we sought to determine the impact of central GPR120 pharmacological activation on energy balance, food reward, and anxiety-like behavior. Methods: Male C57Bl/6 mice with intracerebroventricular cannulae received a single injection (0.1 or 1 µM) or continuous 2-week infusion (1 µM/d; mini-pump) of a GPR120 agonist or vehicle. Free-feeding intake, operant lever-pressing for palatable food, energy expenditure (indirect calorimetry), and body weight were measured. GPR120 mRNA expression was measured in pertinent brain areas. Anxiety-like behavior was assessed in the elevated-plus maze and open field test. Results: GPR120 agonist injections substantially reduced chow intake during 4 hours postinjection, suppressed the rewarding effects of high-fat/-sugar food, and blunted approach-avoidance behavior in the open field. Conversely, prolonged central GPR120 agonist infusions reduced anxiety-like behavior in the elevated-plus maze and open field, yet failed to affect free-feeding intake, energy expenditure, and body weight on a high-fat diet. Conclusion: Acute reductions in food intake and food reward suggest that GPR120 could mediate the effects of central ω-3 polyunsaturated fatty acids to inhibit appetite. The anxiolytic effect elicited by GPR120 agonist infusions favors the testing of compounds that can enter the brain to activate GPR120 for the mitigation of anxiety. PMID:26888796
Seluzicki, Adam; Flourakis, Matthieu; Kula-Eversole, Elzbieta; Zhang, Luoying; Kilman, Valerie; Allada, Ravi
2014-03-01
Molecular circadian clocks are interconnected via neural networks. In Drosophila, PIGMENT-DISPERSING FACTOR (PDF) acts as a master network regulator with dual functions in synchronizing molecular oscillations between disparate PDF(+) and PDF(-) circadian pacemaker neurons and controlling pacemaker neuron output. Yet the mechanisms by which PDF functions are not clear. We demonstrate that genetic inhibition of protein kinase A (PKA) in PDF(-) clock neurons can phenocopy PDF mutants while activated PKA can partially rescue PDF receptor mutants. PKA subunit transcripts are also under clock control in non-PDF DN1p neurons. To address the core clock target of PDF, we rescued per in PDF neurons of arrhythmic per⁰¹ mutants. PDF neuron rescue induced high amplitude rhythms in the clock component TIMELESS (TIM) in per-less DN1p neurons. Complete loss of PDF or PKA inhibition also results in reduced TIM levels in non-PDF neurons of per⁰¹ flies. To address how PDF impacts pacemaker neuron output, we focally applied PDF to DN1p neurons and found that it acutely depolarizes and increases firing rates of DN1p neurons. Surprisingly, these effects are reduced in the presence of an adenylate cyclase inhibitor, yet persist in the presence of PKA inhibition. We have provided evidence for a signaling mechanism (PKA) and a molecular target (TIM) by which PDF resets and synchronizes clocks and demonstrates an acute direct excitatory effect of PDF on target neurons to control neuronal output. The identification of TIM as a target of PDF signaling suggests it is a multimodal integrator of cell autonomous clock, environmental light, and neural network signaling. Moreover, these data reveal a bifurcation of PKA-dependent clock effects and PKA-independent output effects. Taken together, our results provide a molecular and cellular basis for the dual functions of PDF in clock resetting and pacemaker output. PMID:24643294
Olivier, Jocelien D A; de Jong, Trynke R; Jos Dederen, P; van Oorschot, Ruud; Heeren, Dick; Pattij, Tommy; Waldinger, Marcel D; Coolen, Lique M; Cools, Alexander R; Olivier, Berend; Veening, Jan G
2007-01-01
Apomorphine is a non-selective dopaminergic receptor agonist. Because of its pro-erectile effects, apomorphine is clinically used for treatment of erectile dysfunction. We investigated the effects of subcutaneous apomorphine administration (0.4 mg/kg rat) on sexual behavior and mating-induced Fos-ex
A.A.P. van Emmerik; J.H. Kamphuis; P.M.G. Emmelkamp
2008-01-01
Background: Writing assignments have shown promising results in treating traumatic symptomatology. Yet no studies have compared their efficacy to the current treatment of choice, cognitive behavior therapy (CBT). The present study evaluated the efficacy of structured writing therapy (SWT) and CBT as
Assessing risk factors for periodontitis using regression
Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa
2013-10-01
Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.
Reveron, Maria Elena; Maier, Esther Y.; Duvauchelle, Christine L.
2009-01-01
3,4-methylenedioxymethamphetamine (MDMA) is a popular methamphetamine derivative associated with young adults and all-night dance parties. However, the enduring effects of MDMA at voluntary intake levels have not been extensively investigated. In this study, MDMA-influenced behaviors and core temperatures were assessed over the course of 20 daily MDMA self-administration sessions in rats. In vivo microdialysis techniques were used in a subsequent MDMA challenge test session to determine extra...
Fish, E W; Holloway, H T; Rumple, A; Baker, L K; Wieczorek, L A; Moy, S S; Paniagua, B; Parnell, S E
2016-09-15
Prenatal alcohol exposure (PAE) can induce physical malformations and behavioral abnormalities that depend in part on thedevelopmental timing of alcohol exposure. The current studies employed a mouse FASD model to characterize the long-term behavioral and brain structural consequences of a binge-like alcohol exposure during neurulation; a first-trimester stage when women are typically unaware that they are pregnant. Time-mated C57BL/6J female mice were administered two alcohol doses (2.8g/kg, four hours apart) or vehicle starting at gestational day 8.0. Male and female adolescent offspring (postnatal day 28-45) were then examined for motor activity (open field and elevated plus maze), coordination (rotarod), spatial learning and memory (Morris water maze), sensory motor gating (acoustic startle and prepulse inhibition), sociability (three-chambered social test), and nociceptive responses (hot plate). Regional brain volumes and shapes were determined using magnetic resonance imaging. In males, PAE increased activity on the elevated plus maze and reduced social novelty preference, while in females PAE increased exploratory behavior in the open field and transiently impaired rotarod performance. In both males and females, PAE modestly impaired Morris water maze performance and decreased the latency to respond on the hot plate. There were no brain volume differences; however, significant shape differences were found in the cerebellum, hypothalamus, striatum, and corpus callosum. These results demonstrate that alcohol exposure during neurulation can have functional consequences into adolescence, even in the absence of significant brain regional volumetric changes. However, PAE-induced regional shape changes provide evidence for persistent brain alterations and suggest alternative clinical diagnostic markers. PMID:27185739
Abstract Expression Grammar Symbolic Regression
Korns, Michael F.
This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.
ORDINAL REGRESSION FOR INFORMATION RETRIEVAL
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
This letter presents a new discriminative model for Information Retrieval (IR), referred to as Ordinal Regression Model (ORM). ORM is different from most existing models in that it views IR as ordinal regression problem (i.e. ranking problem) instead of binary classification. It is noted that the task of IR is to rank documents according to the user information needed, so IR can be viewed as ordinal regression problem. Two parameter learning algorithms for ORM are presented. One is a perceptron-based algorithm. The other is the ranking Support Vector Machine (SVM). The effectiveness of the proposed approach has been evaluated on the task of ad hoc retrieval using three English Text REtrieval Conference (TREC) sets and two Chinese TREC sets. Results show that ORM significantly outperforms the state-of-the-art language model approaches and OKAPI system in all test sets; and it is more appropriate to view IR as ordinal regression other than binary classification.
... of bronchitis: acute and chronic. Most cases of acute bronchitis get better within several days. But your cough ... that cause colds and the flu often cause acute bronchitis. These viruses spread through the air when people ...
Wrong Signs in Regression Coefficients
McGee, Holly
1999-01-01
When using parametric cost estimation, it is important to note the possibility of the regression coefficients having the wrong sign. A wrong sign is defined as a sign on the regression coefficient opposite to the researcher's intuition and experience. Some possible causes for the wrong sign discussed in this paper are a small range of x's, leverage points, missing variables, multicollinearity, and computational error. Additionally, techniques for determining the cause of the wrong sign are given.
Forecasting with Dynamic Regression Models
Pankratz, Alan
2012-01-01
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
ISIR: Independent Sliced Inverse Regression
Li, Kevin
2013-01-01
International audience In this paper we consider a semiparametric regression model involving a $p$-dimensional explanatory variable ${\\mathbf{x}}$ and including a dimension reduction of ${\\mathbf{x}}$ via an index $B'{\\mathbf{x}}$. In this model, the main goal is to estimate $B$ and to predict the real response variable $Y$ conditionally to ${\\mathbf{x}}$. A standard approach is based on sliced inverse regression (SIR). We propose a new version of this method: the independent sliced invers...
Regression methods for medical research
Tai, Bee Choo
2013-01-01
Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the
From Rasch scores to regression
DEFF Research Database (Denmark)
Christensen, Karl Bang
2006-01-01
Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....
Biplots in Reduced-Rank Regression
Braak, ter C.J.F.; Looman, C.W.N.
1994-01-01
Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced-rank regression. Reduced-rank regression combines multiple regression and principal c
Validation of a heteroscedastic hazards regression model.
Wu, Hong-Dar Isaac; Hsieh, Fushing; Chen, Chen-Hsin
2002-03-01
A Cox-type regression model accommodating heteroscedasticity, with a power factor of the baseline cumulative hazard, is investigated for analyzing data with crossing hazards behavior. Since the approach of partial likelihood cannot eliminate the baseline hazard, an overidentified estimating equation (OEE) approach is introduced in the estimation procedure. It by-product, a model checking statistic, is presented to test for the overall adequacy of the heteroscedastic model. Further, under the heteroscedastic model setting, we propose two statistics to test the proportional hazards assumption. Implementation of this model is illustrated in a data analysis of a cancer clinical trial. PMID:11878222
Directory of Open Access Journals (Sweden)
Jan eSvoboda
2015-04-01
Full Text Available Patients with schizophrenia often manifest deficits in behavioral flexibility. Non-competitive NMDA receptor antagonists such as MK-801 induce schizophrenia-like symptoms in rodents, including cognitive functions. Despite work exploring flexibility has been done employing behavioral paradigms with simple stimuli, much less is known about what kinds of flexibility are affected in an MK-801 model of schizophrenia-like behavior in the spatial domain. We used a rotating arena-based apparatus (Carousel requiring rats to avoid an unmarked sector defined in either the reference frame of the rotating arena (arena frame task, AF or the stationary room (room frame task, RF. We investigated behavioral flexibility in four conditions involving different cognitive loads. Each condition encompassed an initial (five sessions and a test phase (five sessions in which some aspects of the task were changed to test flexibility in which rats were given saline, 0.05 mg/kg or 0.1 mg/kg MK-801 thirty minutes prior to a session. In the first condition, rats acquired avoidance in RF with clockwise rotation of the arena while in the test phase the arena rotated counterclockwise. In the second condition, rats initially acquired avoidance in RF with the sector on the north and then it was reversed to south (spatial reversal. In the third and fourth conditions, rats initially performed an AF (RF, respectively task, followed by an RF (AF, respectively task, testing the ability of cognitive set-shifting. We found no effect of MK-801 either on simple motor adjustment after reversal of arena rotation or on spatial reversal within the RF. In contrast, administration of MK-801 at a dose of 0.1 mg/kg interfered with set-shifting in both conditions. Furthermore, we observed MK-801 0.1 mg/kg elevated locomotion in all cases. These data suggest that blockade of NMDA receptors by acute system administration of MK-801 preferentially affects set-shifting in the cognitive domain rather
Directory of Open Access Journals (Sweden)
Nesrin Şen Celasin
2010-02-01
Full Text Available The study is executed with mothers of children aged 3-6 (n=170 whose children were hospitalized for the first time between the dates of 15.07.2003 and 15.06.2006, who were reachable by phone and accepted to participate in the study aiming determination of behavioral reactions of a child of 3-6 ages group to be hospitalized due to an acute illness.In this study, for data gathering "Personal Information Form" including 15 questions and "Inquiry Form of Behavior Changes of 3-6 Ages Group Children After Being Hospitalized" with 30 questions were used. Date gathering forms were carried out as pre-test by using face-to-face interview method with mothers of 3-6 aged children who were hospitalized for the first time and were in first 12 hours of hospitalization. "Inquiry Form of Behavior Changes of 3-6 Ages Group Children After Being Hospitalized" was re-carried out with mothers by phone 1 month after children being discharged from hospital.In analyzing of datas statistical programme of SPSS 13.0 for Windows was used. In statistical evaluation; number-percent dispersion, Wilcoxon Sing Rank test and Paired Sample-t test were used.According to the results obtained from the study, 57.6% of children are male with age average of 4,46±1,18 and 52.3% of them were hospitalized due to Gastroentestinal System Illnesses. A significant difference was determined between average points of behavior changes of 3-6 ages group children hospitalized due to an acute illness before hospitalized (10,735±4,882 and after being discharged from hospital (15,0476±4,306. In the study, it is observed that there are some behavioral changes in children after being hospitalized such as being cranky before going to bed and during eating, disquiet, bed-wetting, seperation anxiety, excessive attachment to a parent, to need help even for the things he/she could accomplish, to have fear from new environments, people or objects, bad temper attacks, fear of doctor/nurse and hospital, fear
Energy Technology Data Exchange (ETDEWEB)
Winkler, J.D.
1987-01-01
Mice with unilateral, 6-hydroxydopamine-induced lesions of the corpus striatum were exposed to continuous infusion of apomorphine via a subcutaneously implanted osmotic pump. The turning response of these mice when challenged with an acute injection of apomorphine was significantly reduced at one day after chronic implantation and was totally absent at two and four days after implantation. This effect of continuous exposure to apomorphine was found to be concentration- and time-dependent as well as reversible when the implant was removed. Mice tolerant to apomorphine were cross-tolerant to the rotational effects of the D{sub 1} dopaminergic agonist SKF 38393 and the D{sub 2} dopaminergic agonist Ly 171555, but not to amphetamine. Continuous exposure to apomorphine resulted in a decrease in the binding of ({sup 3}H)spiroperidol (D{sub 2} sites) by 44%, whereas the binding of ({sup 3}H)SCH 23390 (D{sub 1} sites) was not affected. Fluphenazine-N-mustard (FNM) has been shown to bind irreversibly to dopaminergic sites. Experiments using varying doses of FNM demonstrated that FNM inhibited Ly 171555-induced rotational behavior at doses ten fold lower than those required to block rotations induced by SKF 38393. In vitro, FNM inhibited the specific binding of ({sup 3}H) spiroperidol at concentrations ten fold lower than those required to inhibit the binding of ({sup 3}H)Sch23390. In vivo, FNM inhibited the binding of ({sup 3}H) spiroperidol measured ex vivo, but did not inhibit the binding of ({sup 3}H) Sch 23390, even when given in doses as high as 100 mg/kg. These studies indicate that FNM was approximately ten times more potent at inhibiting D{sub 2} than D{sub 1} mediated behavior and at displacing D{sub 2} versus D{sub 1} ligands, suggesting that FNM may be useful for studying and differentiating D{sub 2} and D{sub 1} mediated events.
Hughes, Robert N; Hancock, Nicola J
2016-01-01
To assess the possibility that acute caffeine's behavioral action might depend on rats' strain, effects of 50mg/kg of the drug were observed on activity, anxiety-related behavior and habituation learning in male and female rats from three different strains, namely PVG/c, Long-Evans and Wistar. All subjects were tested in an open field, an elevated plus maze and a light-dark box. For the three strains combined, increased occupancy of the center of the open field and entries of the open plus-maze arms with caffeine suggested caffeine-induced anxiolysis, whereas increased grooming in the open field, decreased rearing in the plus maze and increased risk assessment in the light-dark box were consistent with anxiogenesis. Caffeine also reduced open-field rearing only for PVG/c rats, and entries into and occupation of the light side of the light-dark box only for Long-Evans rats, and increased total defecation in the three types of apparatus for all three strains combined. Overall, caffeine appeared to be mainly anxiogenic. The drug also increased open-field ambulation for PVG/c rats and walking for all rats, but decreased open-field ambulation and entries into the plus maze closed arms for Wistar rats alone. In general, Wistar rats appeared to be the least and Long-Evans the most anxious of the three strains investigated. Caffeine also decreased within-session habituation of open-field ambulation for PVG/c rats alone, thereby suggesting strain-dependent interference with non-associative learning and short-term memory. Several overall sex differences were also observed that supported female rats being more active and less anxious than males. PMID:26577750
Hughes, Robert N; Hancock, Nicola J
2016-01-01
To assess the possibility that acute caffeine's behavioral action might depend on rats' strain, effects of 50mg/kg of the drug were observed on activity, anxiety-related behavior and habituation learning in male and female rats from three different strains, namely PVG/c, Long-Evans and Wistar. All subjects were tested in an open field, an elevated plus maze and a light-dark box. For the three strains combined, increased occupancy of the center of the open field and entries of the open plus-maze arms with caffeine suggested caffeine-induced anxiolysis, whereas increased grooming in the open field, decreased rearing in the plus maze and increased risk assessment in the light-dark box were consistent with anxiogenesis. Caffeine also reduced open-field rearing only for PVG/c rats, and entries into and occupation of the light side of the light-dark box only for Long-Evans rats, and increased total defecation in the three types of apparatus for all three strains combined. Overall, caffeine appeared to be mainly anxiogenic. The drug also increased open-field ambulation for PVG/c rats and walking for all rats, but decreased open-field ambulation and entries into the plus maze closed arms for Wistar rats alone. In general, Wistar rats appeared to be the least and Long-Evans the most anxious of the three strains investigated. Caffeine also decreased within-session habituation of open-field ambulation for PVG/c rats alone, thereby suggesting strain-dependent interference with non-associative learning and short-term memory. Several overall sex differences were also observed that supported female rats being more active and less anxious than males.
Institute of Scientific and Technical Information of China (English)
徐冬梅; 文岳中; 李立; 钟旭初
2011-01-01
全氟辛烷磺酰基化合物(PFOS)作为一种新型持久性有机污染物,已经成为环境科学和毒理学的研究热点,其对生态环境的影响值得深入研究.本文采用OECD标准滤纸接触法、人工土壤法及自然土壤法研究了PFOS对蚯蚓急性致死作用及回避行为的影响.结果表明:PFOS对蚯蚓的急性毒性作用与染毒时间和染毒浓度相关,试验求得滤纸法48h、人工土壤法14d和自然土壤法14d的LC50值分别为13.64μg·cm-2、955.28mg·kg-1和542.08mg·kg-1;人工土壤和自然土壤中蚯蚓在PFOS的最大试验浓度组160mg·kg-1,中均表现出显著的回避行为,表明蚯蚓可以明显感知较高浓度PFOS污染土壤并作出回避反应.与急性毒性试验的测试终点LC50,相比,蚯蚓行为测试终点对PFOS的反应更为敏感.自然土壤中PFOS对蚯蚓的急性毒性大于人工土壤,相同浓度PFOS作用下,蚯蚓于自然土壤中的回避行为较人工土壤明显.%As a new kind of persistent organic pollutants, perfluorooctane sulfonate (PFOS) has become a research spot of environmental science and toxicology.Its impacts on ecological environment should be deeply studied.In this paper, standard contact filter paper test of OECD, artificial soil test, and natural soil test were adopted to study the effects of PFOS on the acute lethality and avoidance behavior of earthworm.The results showed that the acute toxicity of PFOS on earthworm was related to the toxicant exposure time and concentration.The LC50,48 h in filter paper test,LC50, 14 d in artificial soil test, and LC50, 14 d in natural soil test were 13.64 μg · cm-2, 955.28 mg· kg-1, and 542.08 mg· kg-1, respectively.At the maximum test concentration of 160 mg·kg-1 , the earthworm in artificial soil and natural soil showed significant avoidance behavior, which proved that earthworm could perceive and avoid the soil contaminated by a higher concentration of PFOS.To assess PFOS-contaminated soils, the
Entrepreneurial intention modeling using hierarchical multiple regression
Directory of Open Access Journals (Sweden)
Marina Jeger
2014-12-01
Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.
Kovalev, G I; Kondrakhin, E A; Salimov, R M; Neznamov, G G
2014-01-01
The effect of acute, 7-fold and 14-fold noopept (1 mg/kg/day) administration on the dynamics of anxiolitic and nootropic behavioral effects in cross-maze, as well as their correlations with NMDA- and BDZ-receptor density was studied in inbred mice strains, differing in exploratory and emotional status--C57BL/6 and BALB/c. The dipeptide failed to affect the anxiety and exploration activity in C57BL/6 mice at each of 3 steps of experimental session. In this strain the B(max) values of [3H]-MK-801 and [3H]-Flunitrazepam binding changed only after single administration. In respect to BALB/c mice noopept induced both the anxiolitic and nootropic effects reaching their maximum on 7th day. In BALB/c strain the dynamics of hippocampal NMDA-receptor binding corresponds to the dynamics of exploratory efficacy whereas the dynamics of BDZ-receptors in prefrontal cortex was reciprocally to dynamics of anxiety level. PMID:25739185
Josse, Jérôme; Guillaume, Christine; Bour, Camille; Lemaire, Flora; Mongaret, Céline; Draux, Florence; Velard, Frédéric; Gangloff, Sophie C
2016-01-01
Staphylococcus aureus is one of the most frequently involved pathogens in bacterial infections such as skin abscess, pneumonia, endocarditis, osteomyelitis, and implant-associated infection. As for bone homeostasis, it is partly altered during infections by S. aureus by the induction of various responses from osteoblasts, which are the bone-forming cells responsible for extracellular matrix synthesis and its mineralization. Nevertheless, bone-forming cells are a heterogeneous population with different stages of maturation and the impact of the latter on their responses toward bacteria remains unclear. We describe the impact of S. aureus on two populations of human primary bone-forming cells (HPBCs) which have distinct maturation characteristics in both acute and persistent models of interaction. Cell maturation did not influence the internalization and survival of S. aureus inside bone-forming cells or the cell death related to the infection. By studying the expression of chemokines, cytokines, and osteoclastogenic regulators by HPBCs, we observed different profiles of chemokine expression according to the degree of cell maturation. However, there was no statistical difference in the amounts of proteins released by both populations in the presence of S. aureus compared to the non-infected counterparts. Our findings show that cell maturation does not impact the behavior of HPBCs infected with S. aureus and suggest that the role of bone-forming cells may not be pivotal for the inflammatory response in osteomyelitis. PMID:27446812
Interpretation of Standardized Regression Coefficients in Multiple Regression.
Thayer, Jerome D.
The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for variables…
Survival Data and Regression Models
Grégoire, G.
2014-12-01
We start this chapter by introducing some basic elements for the analysis of censored survival data. Then we focus on right censored data and develop two types of regression models. The first one concerns the so-called accelerated failure time models (AFT), which are parametric models where a function of a parameter depends linearly on the covariables. The second one is a semiparametric model, where the covariables enter in a multiplicative form in the expression of the hazard rate function. The main statistical tool for analysing these regression models is the maximum likelihood methodology and, in spite we recall some essential results about the ML theory, we refer to the chapter "Logistic Regression" for a more detailed presentation.
[Is regression of atherosclerosis possible?].
Thomas, D; Richard, J L; Emmerich, J; Bruckert, E; Delahaye, F
1992-10-01
Experimental studies have shown the regression of atherosclerosis in animals given a cholesterol-rich diet and then given a normal diet or hypolipidemic therapy. Despite favourable results of clinical trials of primary prevention modifying the lipid profile, the concept of atherosclerosis regression in man remains very controversial. The methodological approach is difficult: this is based on angiographic data and requires strict standardisation of angiographic views and reliable quantitative techniques of analysis which are available with image processing. Several methodologically acceptable clinical coronary studies have shown not only stabilisation but also regression of atherosclerotic lesions with reductions of about 25% in total cholesterol levels and of about 40% in LDL cholesterol levels. These reductions were obtained either by drugs as in CLAS (Cholesterol Lowering Atherosclerosis Study), FATS (Familial Atherosclerosis Treatment Study) and SCOR (Specialized Center of Research Intervention Trial), by profound modifications in dietary habits as in the Lifestyle Heart Trial, or by surgery (ileo-caecal bypass) as in POSCH (Program On the Surgical Control of the Hyperlipidemias). On the other hand, trials with non-lipid lowering drugs such as the calcium antagonists (INTACT, MHIS) have not shown significant regression of existing atherosclerotic lesions but only a decrease on the number of new lesions. The clinical benefits of these regression studies are difficult to demonstrate given the limited period of observation, relatively small population numbers and the fact that in some cases the subjects were asymptomatic. The decrease in the number of cardiovascular events therefore seems relatively modest and concerns essentially subjects who were symptomatic initially. The clinical repercussion of studies of prevention involving a single lipid factor is probably partially due to the reduction in progression and anatomical regression of the atherosclerotic plaque
Assessment of deforestation using regression
International Nuclear Information System (INIS)
This work is devoted to the evaluation of deforestation using regression methods through software Idrisi Taiga. Deforestation is evaluated by the method of logistic regression. The dependent variable has discrete values '0' and '1', indicating that the deforestation occurred or not. Independent variables have continuous values, expressing the distance from the edge of the deforested areas of forests from urban areas, the river and the road network. The results were also used in predicting the probability of deforestation in subsequent periods. The result is a map showing the output probability of deforestation for the periods 1990/2000 and 200/2006 in accordance with predetermined coefficients (values of independent variables). (authors)
Al-Ghraibah, Amani
Solar flares release stored magnetic energy in the form of radiation and can have significant detrimental effects on earth including damage to technological infrastructure. Recent work has considered methods to predict future flare activity on the basis of quantitative measures of the solar magnetic field. Accurate advanced warning of solar flare occurrence is an area of increasing concern and much research is ongoing in this area. Our previous work 111] utilized standard pattern recognition and classification techniques to determine (classify) whether a region is expected to flare within a predictive time window, using a Relevance Vector Machine (RVM) classification method. We extracted 38 features which describing the complexity of the photospheric magnetic field, the result classification metrics will provide the baseline against which we compare our new work. We find a true positive rate (TPR) of 0.8, true negative rate (TNR) of 0.7, and true skill score (TSS) of 0.49. This dissertation proposes three basic topics; the first topic is an extension to our previous work [111, where we consider a feature selection method to determine an appropriate feature subset with cross validation classification based on a histogram analysis of selected features. Classification using the top five features resulting from this analysis yield better classification accuracies across a large unbalanced dataset. In particular, the feature subsets provide better discrimination of the many regions that flare where we find a TPR of 0.85, a TNR of 0.65 sightly lower than our previous work, and a TSS of 0.5 which has an improvement comparing with our previous work. In the second topic, we study the prediction of solar flare size and time-to-flare using support vector regression (SVR). When we consider flaring regions only, we find an average error in estimating flare size of approximately half a GOES class. When we additionally consider non-flaring regions, we find an increased average
A flexible fuzzy regression algorithm for forecasting oil consumption estimation
International Nuclear Information System (INIS)
Oil consumption plays a vital role in socio-economic development of most countries. This study presents a flexible fuzzy regression algorithm for forecasting oil consumption based on standard economic indicators. The standard indicators are annual population, cost of crude oil import, gross domestic production (GDP) and annual oil production in the last period. The proposed algorithm uses analysis of variance (ANOVA) to select either fuzzy regression or conventional regression for future demand estimation. The significance of the proposed algorithm is three fold. First, it is flexible and identifies the best model based on the results of ANOVA and minimum absolute percentage error (MAPE), whereas previous studies consider the best fitted fuzzy regression model based on MAPE or other relative error results. Second, the proposed model may identify conventional regression as the best model for future oil consumption forecasting because of its dynamic structure, whereas previous studies assume that fuzzy regression always provide the best solutions and estimation. Third, it utilizes the most standard independent variables for the regression models. To show the applicability and superiority of the proposed flexible fuzzy regression algorithm the data for oil consumption in Canada, United States, Japan and Australia from 1990 to 2005 are used. The results show that the flexible algorithm provides accurate solution for oil consumption estimation problem. The algorithm may be used by policy makers to accurately foresee the behavior of oil consumption in various regions.
Ridge Regression for Interactive Models.
Tate, Richard L.
1988-01-01
An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are favorable to…
Regression of lumbar disk herniation
Directory of Open Access Journals (Sweden)
G. Yu Evzikov
2015-01-01
Full Text Available Compression of the spinal nerve root, giving rise to pain and sensory and motor disorders in the area of its innervation is the most vivid manifestation of herniated intervertebral disk. Different treatment modalities, including neurosurgery, for evolving these conditions are discussed. There has been recent evidence that spontaneous regression of disk herniation can regress. The paper describes a female patient with large lateralized disc extrusion that has caused compression of the nerve root S1, leading to obvious myotonic and radicular syndrome. Magnetic resonance imaging has shown that the clinical manifestations of discogenic radiculopathy, as well myotonic syndrome and morphological changes completely regressed 8 months later. The likely mechanism is inflammation-induced resorption of a large herniated disk fragment, which agrees with the data available in the literature. A decision to perform neurosurgery for which the patient had indications was made during her first consultation. After regression of discogenic radiculopathy, there was only moderate pain caused by musculoskeletal diseases (facet syndrome, piriformis syndrome that were successfully eliminated by minimally invasive techniques.
ERM Scheme for Quantile Regression
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Dao-Hong Xiang
2013-01-01
Full Text Available This paper considers the ERM scheme for quantile regression. We conduct error analysis for this learning algorithm by means of a variance-expectation bound when a noise condition is satisfied for the underlying probability measure. The learning rates are derived by applying concentration techniques involving the ℓ2-empirical covering numbers.
On Weighted Support Vector Regression
DEFF Research Database (Denmark)
Han, Xixuan; Clemmensen, Line Katrine Harder
2014-01-01
We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...
Growth Regression and Economic Theory
Elbers, Chris; Gunning, Jan Willem
2002-01-01
In this note we show that the standard, loglinear growth regression specificationis consistent with one and only one model in the class of stochastic Ramsey models. Thismodel is highly restrictive: it requires a Cobb-Douglas technology and a 100% depreciationrate and it implies that risk does not af
Fuzzy linear regression forecasting models
Institute of Scientific and Technical Information of China (English)
吴冲; 惠晓峰; 朱洪文
2002-01-01
The fuzzy linear regression forecasting model is deduced from the symmetric triangular fuzzy number.With the help of the degree of fitting and the measure of fuzziness, the determination of symmetric triangularfuzzy numbers is changed into a problem of solving linear programming.
Heteroscedasticity checks for regression models
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
For checking on heteroscedasticity in regression models, a unified approach is proposed to constructing test statistics in parametric and nonparametric regression models. For nonparametric regression, the test is not affected sensitively by the choice of smoothing parameters which are involved in estimation of the nonparametric regression function. The limiting null distribution of the test statistic remains the same in a wide range of the smoothing parameters. When the covariate is one-dimensional, the tests are, under some conditions, asymptotically distribution-free. In the high-dimensional cases, the validity of bootstrap approximations is investigated. It is shown that a variant of the wild bootstrap is consistent while the classical bootstrap is not in the general case, but is applicable if some extra assumption on conditional variance of the squared error is imposed. A simulation study is performed to provide evidence of how the tests work and compare with tests that have appeared in the literature. The approach may readily be extended to handle partial linear, and linear autoregressive models.
Logistic regression: a brief primer.
Stoltzfus, Jill C
2011-10-01
Regression techniques are versatile in their application to medical research because they can measure associations, predict outcomes, and control for confounding variable effects. As one such technique, logistic regression is an efficient and powerful way to analyze the effect of a group of independent variables on a binary outcome by quantifying each independent variable's unique contribution. Using components of linear regression reflected in the logit scale, logistic regression iteratively identifies the strongest linear combination of variables with the greatest probability of detecting the observed outcome. Important considerations when conducting logistic regression include selecting independent variables, ensuring that relevant assumptions are met, and choosing an appropriate model building strategy. For independent variable selection, one should be guided by such factors as accepted theory, previous empirical investigations, clinical considerations, and univariate statistical analyses, with acknowledgement of potential confounding variables that should be accounted for. Basic assumptions that must be met for logistic regression include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers. Additionally, there should be an adequate number of events per independent variable to avoid an overfit model, with commonly recommended minimum "rules of thumb" ranging from 10 to 20 events per covariate. Regarding model building strategies, the three general types are direct/standard, sequential/hierarchical, and stepwise/statistical, with each having a different emphasis and purpose. Before reaching definitive conclusions from the results of any of these methods, one should formally quantify the model's internal validity (i.e., replicability within the same data set) and external validity (i.e., generalizability beyond the current sample). The resulting logistic regression model
Patel, Sapan J; Dao, Su; Darie, Costel C; Clarkson, Bayard D
2016-01-01
Quorum sensing (QS) is a generic term used to describe cell-cell communication and collective decision making by bacterial and social insects to regulate the expression of specific genes in controlling cell density and other properties of the populations in response to nutrient supply or changes in the environment. QS mechanisms also have a role in higher organisms in maintaining homeostasis, regulation of the immune system and collective behavior of cancer cell populations. In the present study, we used a p190(BCR-ABL) driven pre-B acute lymphoblastic leukemia (ALL3) cell line derived from the pleural fluid of a terminally ill patient with ALL to test the QS hypothesis in leukemia. ALL3 cells don't grow at low density (LD) in liquid media but grow progressively faster at increasingly high cell densities (HD) in contrast to other established leukemic cell lines that grow well at very low starting cell densities. The ALL3 cells at LD are poised to grow but shortly die without additional stimulation. Supernates of ALL3 cells (HDSN) and some other primary cells grown at HD stimulate the growth of the LD ALL3 cells without which they won't survive. To get further insight into the activation processes we performed microarray analysis of the LD ALL3 cells after stimulation with ALL3 HDSN at days 1, 3, and 6. This screen identified several candidate genes, and we linked them to signaling networks and their functions. We observed that genes involved in lipid, cholesterol, fatty acid metabolism, and B cell activation are most up- or down-regulated upon stimulation of the LD ALL3 cells using HDSN. We also discuss other pathways that are differentially expressed upon stimulation of the LD ALL3 cells. Our findings suggest that the Ph+ ALL population achieves dominance by functioning as a collective aberrant ecosystem subject to defective quorum-sensing regulatory mechanisms. PMID:27429840
Acute Pancreatitis and Pregnancy
... Acute Pancreatitis > Acute Pancreatitis and Pregnancy test Acute Pancreatitis and Pregnancy Timothy Gardner, MD Acute pancreatitis is ... of acute pancreatitis in pregnancy. Reasons for Acute Pancreatitis and Pregnancy While acute pancreatitis is responsible for ...
Invasive Mole Presenting as Acute Haemoperitoneum
Directory of Open Access Journals (Sweden)
Sunesh Kumar, N. Vimala, Suneeta Mittal
2004-07-01
Full Text Available We report a case of invasive hydatidiform mole presenting as an acute primary haemoperitoneum.The patient presented with acute abdominal pain and signs of haemoperitoneum. Emergencylaparotomy revealed a molar pregnancy perforating through the uterine fundus, resulting in massivehaemoperitoneum. The serum beta chorionic gonado-tropin (ß-hCG levels regressed spontaneouslyfollowing evacuation of the molar pregnancy.
Heteroscedasticity checks for regression models
Institute of Scientific and Technical Information of China (English)
ZHU; Lixing
2001-01-01
［1］Carroll, R. J., Ruppert, D., Transformation and Weighting in Regression, New York: Chapman and Hall, 1988.［2］Cook, R. D., Weisberg, S., Diagnostics for heteroscedasticity in regression, Biometrika, 1988, 70: 1—10.［3］Davidian, M., Carroll, R. J., Variance function estimation, J. Amer. Statist. Assoc., 1987, 82: 1079—1091.［4］Bickel, P., Using residuals robustly I: Tests for heteroscedasticity, Ann. Statist., 1978, 6: 266—291.［5］Carroll, R. J., Ruppert, D., On robust tests for heteroscedasticity, Ann. Statist., 1981, 9: 205—209.［6］Eubank, R. L., Thomas, W., Detecting heteroscedasticity in nonparametric regression, J. Roy. Statist. Soc., Ser. B, 1993, 55: 145—155.［7］Diblasi, A., Bowman, A., Testing for constant variance in a linear model, Statist. and Probab. Letters, 1997, 33: 95—103.［8］Dette, H., Munk, A., Testing heteoscedasticity in nonparametric regression, J. R. Statist. Soc. B, 1998, 60: 693—708.［9］Müller, H. G., Zhao, P. L., On a semi-parametric variance function model and a test for heteroscedasticity, Ann. Statist., 1995, 23: 946—967.［10］Stute, W., Manteiga, G., Quindimil, M. P., Bootstrap approximations in model checks for regression, J. Amer. Statist. Asso., 1998, 93: 141—149.［11］Stute, W., Thies, G., Zhu, L. X., Model checks for regression: An innovation approach, Ann. Statist., 1998, 26: 1916—1939.［12］Shorack, G. R., Wellner, J. A., Empirical Processes with Applications to Statistics, New York: Wiley, 1986.［13］Efron, B., Bootstrap methods: Another look at the jackknife, Ann. Statist., 1979, 7: 1—26.［14］Wu, C. F. J., Jackknife, bootstrap and other re-sampling methods in regression analysis, Ann. Statist., 1986, 14: 1261—1295.［15］H rdle, W., Mammen, E., Comparing non-parametric versus parametric regression fits, Ann. Statist., 1993, 21: 1926—1947.［16］Liu, R. Y., Bootstrap procedures under some non-i.i.d. models, Ann. Statist., 1988, 16: 1696—1708.［17
The Standard Error of Regressions
Deirdre N. McCloskey; Stephen T. Ziliak
1996-01-01
Statistical significance as used in economics has weak theoretical justification. In particular it merges statistical and substantive significance. The 182 papers using regression analysis in the American Economic Review in the 1980s were tested against 19 criteria for the accepted use of statistical significance. Most, some three-quarters of the papers, did poorly. Likewise, textbooks in econometrics do not distinguish statistical and economic significance. Statistical significance should no...
Functional linear regression with derivatives
Mas, André; Pumo, Besnik
2006-01-01
International audience We introduce a new model of linear regression for random functional inputs taking into account the first order derivative of the data. We propose an estimation method which comes down to solving a special linear inverse problem. Our procedure tackles the problem through a double and synchronized penalization. An asymptotic expansion of the mean square prevision error is given. The model and the method are applied to a benchmark dataset of spectrometric curves and com...
Robust nonlinear regression in applications
Lim, Changwon; Sen, Pranab K.; Peddada, Shyamal D.
2013-01-01
Robust statistical methods, such as M-estimators, are needed for nonlinear regression models because of the presence of outliers/influential observations and heteroscedasticity. Outliers and influential observations are commonly observed in many applications, especially in toxicology and agricultural experiments. For example, dose response studies, which are routinely conducted in toxicology and agriculture, sometimes result in potential outliers, especially in the high dose gr...
Mission assurance increased with regression testing
Lang, R.; Spezio, M.
- C based and big endian. The presence of byte swap issues that might not have been identified in the required software changes was very real and can be difficult to find. The ability to have test designs that would exercise all major functions and operations was invaluable to assure that critical operations and tools would operate as they had since first operational use. With the longevity of the mission also came the realization that the original ISAT team would not be the people working on the ISAT regression testing. The ability to have access to all original test designs and test results identified in the regression test suite greatly improved the ability to identify not only the expected system behavior, but also the actual behavior with the old architecture. So in summary, this paper will discuss the importance, practicality, and results achieved by having a well-defined regression test available to assure the New Horizons Mission Operations Control system continues to meet its functional requirements to support the mission objectives.
... sharing features on this page, please enable JavaScript. Acute bronchitis is swelling and inflammation in the main passages ... present only for a short time. Causes When acute bronchitis occurs, it almost always comes after having a ...
An Application on Multinomial Logistic Regression Model
Directory of Open Access Journals (Sweden)
Abdalla M El-Habil
2012-03-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE This study aims to identify an application of Multinomial Logistic Regression model which is one of the important methods for categorical data analysis. This model deals with one nominal/ordinal response variable that has more than two categories, whether nominal or ordinal variable. This model has been applied in data analysis in many areas, for example health, social, behavioral, and educational.To identify the model by practical way, we used real data on physical violence against children, from a survey of Youth 2003 which was conducted by Palestinian Central Bureau of Statistics (PCBS. Segment of the population of children in the age group (10-14 years for residents in Gaza governorate, size of 66,935 had been selected, and the response variable consisted of four categories. Eighteen of explanatory variables were used for building the primary multinomial logistic regression model. Model had been tested through a set of statistical tests to ensure its appropriateness for the data. Also the model had been tested by selecting randomly of two observations of the data used to predict the position of each observation in any classified group it can be, by knowing the values of the explanatory variables used. We concluded by using the multinomial logistic regression model that we can able to define accurately the relationship between the group of explanatory variables and the response variable, identify the effect of each of the variables, and we can predict the classification of any individual case.
Bo-Guang Fan; Åke Andrén-Sandberg
2010-01-01
Background : Acute pancreatitis continues to be a serious illness, and the patients with acute pancreatitis are at risk to develop different complications from ongoing pancreatic inflammation. Aims : The present review is to highlight the classification, treatment and prognosis of acute pancreatitis. Material & Methods : We reviewed the English-language literature (Medline) addressing pancreatitis. Results : Acute pancreatitis is frequently caused by gallstone disease or excess alcohol ingest...
Bo-Guang Fan; Åke Andrén-Sandberg
2010-01-01
Background: Acute pancreatitis continues to be a serious illness, and the patients with acute pancreatitis are at risk to develop different complications from ongoing pancreatic inflammation. Aims: The present review is to highlight the classification, treatment and prognosis of acute pancreatitis. Material & Methods: We reviewed the English-language literature (Medline) addressing pancreatitis. Results: Acute pancreatitis is frequently caused by gallstone disease or excess alcohol ingestion....
Testing for Stock Market Contagion: A Quantile Regression Approach
S.Y. Park (Sung); W. Wang (Wendun); N. Huang (Naijing)
2015-01-01
markdownabstract__Abstract__ Regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile regression framework that is robust to model misspecification. Unlike conventional correlation-based tests, the proposed quantile contagion test allows
Credit Scoring Problem Based on Regression Analysis
Khassawneh, Bashar Suhil Jad Allah
2014-01-01
ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....
Directory of Open Access Journals (Sweden)
Bo-Guang Fan
2010-01-01
Full Text Available Background : Acute pancreatitis continues to be a serious illness, and the patients with acute pancreatitis are at risk to develop different complications from ongoing pancreatic inflammation. Aims : The present review is to highlight the classification, treatment and prognosis of acute pancreatitis. Material & Methods : We reviewed the English-language literature (Medline addressing pancreatitis. Results : Acute pancreatitis is frequently caused by gallstone disease or excess alcohol ingestion. There are a number of important issues regarding clinical highlights in the classification, treatment and prognosis of acute pancreatitis, and treatment options for complications of acute pancreatitis including pancreatic pseudocysts. Conclusions : Multidisciplinary approach should be used for the management of the patient with acute pancreatitis.
Directory of Open Access Journals (Sweden)
Bo-Guang Fan
2010-05-01
Full Text Available Background: Acute pancreatitis continues to be a serious illness, and the patients with acute pancreatitis are at risk to develop different complications from ongoing pancreatic inflammation. Aims: The present review is to highlight the classification, treatment and prognosis of acute pancreatitis. Material & Methods: We reviewed the English-language literature (Medline addressing pancreatitis. Results: Acute pancreatitis is frequently caused by gallstone disease or excess alcohol ingestion. There are a number of important issues regarding clinical highlights in the classification, treatment and prognosis of acute pancreatitis, and treatment options for complications of acute pancreatitis including pancreatic pseudocysts. Conclusions: Multidisciplinary approach should be used for the management of the patient with acute pancreatitis.
Prediction, Regression and Critical Realism
DEFF Research Database (Denmark)
Næss, Petter
2004-01-01
This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... of prediction necessary and possible in spatial planning of urban development. Finally, the political implications of positions within theory of science rejecting the possibility of predictions about social phenomena are addressed....... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...
Nonparametric Regression with Common Shocks
Directory of Open Access Journals (Sweden)
Eduardo A. Souza-Rodrigues
2016-09-01
Full Text Available This paper considers a nonparametric regression model for cross-sectional data in the presence of common shocks. Common shocks are allowed to be very general in nature; they do not need to be finite dimensional with a known (small number of factors. I investigate the properties of the Nadaraya-Watson kernel estimator and determine how general the common shocks can be while still obtaining meaningful kernel estimates. Restrictions on the common shocks are necessary because kernel estimators typically manipulate conditional densities, and conditional densities do not necessarily exist in the present case. By appealing to disintegration theory, I provide sufficient conditions for the existence of such conditional densities and show that the estimator converges in probability to the Kolmogorov conditional expectation given the sigma-field generated by the common shocks. I also establish the rate of convergence and the asymptotic distribution of the kernel estimator.
Adaptive Local Linear Quantile Regression
Institute of Scientific and Technical Information of China (English)
Yu-nan Su; Mao-zai Tian
2011-01-01
In this paper we propose a new method of local linear adaptive smoothing for nonparametric conditional quantile regression. Some theoretical properties of the procedure are investigated. Then we demonstrate the performance of the method on a simulated example and compare it with other methods. The simulation results demonstrate a reasonable performance of our method proposed especially in situations when the underlying image is piecewise linear or can be approximated by such images. Generally speaking, our method outperforms most other existing methods in the sense of the mean square estimation (MSE) and mean absolute estimation (MAE) criteria. The procedure is very stable with respect to increasing noise level and the algorithm can be easily applied to higher dimensional situations.
Directory of Open Access Journals (Sweden)
Krishna Tanwar
2014-02-01
Full Text Available Neurosteroids (NS are considered important modulators of brain functions. Lindane a pesticide has been shown to affect the nerv-ous system adversely. The present study was designed to explore the modulation of the effects of lindane on convulsions by Allopregnenalone (AP, and 4′-Chlorodiazepam (4′-CD, in both acute and chronic seizure models using Pentylenetetrazole (PTZ. We used acute and chronic models. In the acute model, seizures were induced by PTZ 90mg/kg, intra-peritoneal (i.p. injection, while in the chronic model, kindling was induced by injecting PTZ 30 mg/kg sub-cutaneous(s.c on alternate days three times in a week. Lindane produced augmented effect on convulsions by decreasing the onset of preclonic convulsions and increased duration of clonic convulsions. AP (2.5mg/kg, i.p and 4′-CD (0.5mg/kg, i.p were able to attenuate the effect of acute as well as chronic exposure of lindane. They significantly increased the onset and decreased the duration of convulsions in lindane-treated rats. These results conclusively demonstrate the efficacy of the neurosteroids in lindane-induced convulsions in both acute as well as chronic models. Thus, NS have a potential role as anticonvulsant in treatment of convulsions produced by pesticides like lindane.
Polynomial Regressions and Nonsense Inference
DEFF Research Database (Denmark)
Ventosa-Santaulària, Daniel; Rodríguez-Caballero, Carlos Vladimir
behavior. We extend Phillips’ (1986) results by proving an inference drawn from polynomial specifications, under stochastic nonstationarity, is misleading unless the variables cointegrate. We use a generalized polynomial specification as a vehicle to study its asymptotic and finite-sample properties. Our...
Depression following acute coronary syndrome
DEFF Research Database (Denmark)
Joergensen, Terese Sara Hoej; Maartensson, Solvej; Ibfelt, Else Helene;
2016-01-01
PURPOSE: Depression is common following acute coronary syndrome, and thus, it is important to provide knowledge to improve prevention and detection of depression in this patient group. The objectives of this study were to examine: (1) whether indicators of stressors and coping resources were risk...... factors for developing depression early and later after an acute coronary syndrome and (2) whether prior depression modified these associations. METHODS: The study was a register-based cohort study, which includes 87,118 patients with a first time diagnosis of acute coronary syndrome during the period...... 2001-2009 in Denmark. Cox regression models were used to analyse hazard ratios (HRs) for depression. RESULTS: 1.5 and 9.5 % develop early (≤30 days) and later (31 days-2 years) depression after the acute coronary syndrome. Among all patients with depression, 69.2 % had first onset depression, while 30...
RANDOM WEIGHTING METHOD FOR CENSORED REGRESSION MODEL
Institute of Scientific and Technical Information of China (English)
ZHAO Lincheng; FANG Yixin
2004-01-01
Rao and Zhao (1992) used random weighting method to derive the approximate distribution of the M-estimator in linear regression model. In this paper we extend the result to the censored regression model (or censored "Tobit" model).
Gaussian process regression analysis for functional data
Shi, Jian Qing
2011-01-01
Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime
Semiparametric regression during 2003–2007
Ruppert, David
2009-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
Distributional aspects in partial least squares regression
Romera, Rosario
1999-01-01
This paper presents some results about the asymptotic behaviour of the estimate of a regression model obtained by Partial Least Squares (PLS) Methods. Because the nonlinearity of the regression estimator on the response variable, local linear approximation through the 6-method for the PLS regression vector is carried out. A new implementation of the PLS algorithm is developed for this purpose.
Functional Regression for Quasar Spectra
Ciollaro, Mattia; Freeman, Peter; Genovese, Christopher; Lei, Jing; O'Connell, Ross; Wasserman, Larry
2014-01-01
The Lyman-alpha forest is a portion of the observed light spectrum of distant galactic nuclei which allows us to probe remote regions of the Universe that are otherwise inaccessible. The observed Lyman-alpha forest of a quasar light spectrum can be modeled as a noisy realization of a smooth curve that is affected by a `damping effect' which occurs whenever the light emitted by the quasar travels through regions of the Universe with higher matter concentration. To decode the information conveyed by the Lyman-alpha forest about the matter distribution, we must be able to separate the smooth `continuum' from the noise and the contribution of the damping effect in the quasar light spectra. To predict the continuum in the Lyman-alpha forest, we use a nonparametric functional regression model in which both the response and the predictor variable (the smooth part of the damping-free portion of the spectrum) are function-valued random variables. We demonstrate that the proposed method accurately predicts the unobserv...
Violent behavior in chronic schizophrenia and inpatient psychiatry.
O'Connor, Siobhán
2003-01-01
The author describes how work with inpatients with chronic schizophrenia has contributed to a better understanding of antisocial behavior. She has used the concept of regression, along biological and psychological lines, to hypothesize fantasies of primitive object relationships which drive the behavior. Engaging patients in thoughtful reflection, she has introduced a third perspective on the potential state of mind of the important people in their lives; the possibility of a concerned object, rather than that of a vengeful or rejecting object. Finding that even those with resistant schizophrenia respond with change in behavior, she found that she could more easily employ the same psychoanalytic concepts in engaging those who present with more acute problems of violent and suicidal behavior. PMID:12722886
Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.
1996-01-01
BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a
Regression modeling methods, theory, and computation with SAS
Panik, Michael
2009-01-01
Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,
Regression with Sparse Approximations of Data
DEFF Research Database (Denmark)
Noorzad, Pardis; Sturm, Bob L.
2012-01-01
We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected by a...... sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based on the...
Functional linear regression via canonical analysis
He, Guozhong; Wang, Jane-Ling; Yang, Wenjing; 10.3150/09-BEJ228
2011-01-01
We study regression models for the situation where both dependent and independent variables are square-integrable stochastic processes. Questions concerning the definition and existence of the corresponding functional linear regression models and some basic properties are explored for this situation. We derive a representation of the regression parameter function in terms of the canonical components of the processes involved. This representation establishes a connection between functional regression and functional canonical analysis and suggests alternative approaches for the implementation of functional linear regression analysis. A specific procedure for the estimation of the regression parameter function using canonical expansions is proposed and compared with an established functional principal component regression approach. As an example of an application, we present an analysis of mortality data for cohorts of medflies, obtained in experimental studies of aging and longevity.
Analysis of Sting Balance Calibration Data Using Optimized Regression Models
Ulbrich, N.; Bader, Jon B.
2010-01-01
Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.
Thomas, Michael S. C.; Knowland, Victoria C. P.; Karmiloff-Smith, Annette
2011-01-01
Loss of previously established behaviors in early childhood constitutes a markedly atypical developmental trajectory. It is found almost uniquely in autism and its cause is currently unknown (Baird et al., 2008). We present an artificial neural network model of developmental regression, exploring the hypothesis that regression is caused by…
Applied regression analysis a research tool
Pantula, Sastry; Dickey, David
1998-01-01
Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...
PLUTO: Penalized Unbiased Logistic Regression Trees
Zhang, Wenwen; Loh, Wei-Yin
2014-01-01
We propose a new algorithm called PLUTO for building logistic regression trees to binary response data. PLUTO can capture the nonlinear and interaction patterns in messy data by recursively partitioning the sample space. It fits a simple or a multiple linear logistic regression model in each partition. PLUTO employs the cyclical coordinate descent method for estimation of multiple linear logistic regression models with elastic net penalties, which allows it to deal with high-dimensional data ...
LRGS: Linear Regression by Gibbs Sampling
Mantz, Adam B.
2016-02-01
LRGS (Linear Regression by Gibbs Sampling) implements a Gibbs sampler to solve the problem of multivariate linear regression with uncertainties in all measured quantities and intrinsic scatter. LRGS extends an algorithm by Kelly (2007) that used Gibbs sampling for performing linear regression in fairly general cases in two ways: generalizing the procedure for multiple response variables, and modeling the prior distribution of covariates using a Dirichlet process.
Data Mining within a Regression Framework
Berk, Richard A.
Regression analysis can imply a far wider range of statistical procedures than often appreciated. In this chapter, a number of common Data Mining procedures are discussed within a regression framework. These include non-parametric smoothers, classification and regression trees, bagging, and random forests. In each case, the goal is to characterize one or more of the distributional features of a response conditional on a set of predictors.
High-dimensional regression with unknown variance
Giraud, Christophe; Verzelen, Nicolas
2011-01-01
We review recent results for high-dimensional sparse linear regression in the practical case of unknown variance. Different sparsity settings are covered, including coordinate-sparsity, group-sparsity and variation-sparsity. The emphasize is put on non-asymptotic analyses and feasible procedures. In addition, a small numerical study compares the practical performance of three schemes for tuning the Lasso esti- mator and some references are collected for some more general models, including multivariate regression and nonparametric regression.
International Nuclear Information System (INIS)
Radiodiagnosis is applied to determine the causes of acute dyspnea. Acute dyspnea is shown to aggravate the course of pulmonary diseases (bronchial asthma, obstructive bronchitis, pulmonary edema, throboembolism of pulmonary arteries etc) and cardiovascular diseases (desiseas of myocardium). The main tasks of radiodiagnosis are to determine volume and state of the lungs, localization and type of pulmonary injuries, to verify heart disease and to reveal concomitant complications
New ridge parameters for ridge regression
Directory of Open Access Journals (Sweden)
A.V. Dorugade
2014-04-01
Full Text Available Hoerl and Kennard (1970a introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation. In this article, a new method for estimating ridge parameters in both situations of ordinary ridge regression (ORR and generalized ridge regression (GRR is proposed. The simulation study evaluates the performance of the proposed estimator based on the mean squared error (MSE criterion and indicates that under certain conditions the proposed estimators perform well compared to OLS and other well-known estimators reviewed in this article.
Logistic Regression for Evolving Data Streams Classification
Institute of Scientific and Technical Information of China (English)
YIN Zhi-wu; HUANG Shang-teng; XUE Gui-rong
2007-01-01
Logistic regression is a fast classifier and can achieve higher accuracy on small training data. Moreover,it can work on both discrete and continuous attributes with nonlinear patterns. Based on these properties of logistic regression, this paper proposed an algorithm, called evolutionary logistical regression classifier (ELRClass), to solve the classification of evolving data streams. This algorithm applies logistic regression repeatedly to a sliding window of samples in order to update the existing classifier, to keep this classifier if its performance is deteriorated by the reason of bursting noise, or to construct a new classifier if a major concept drift is detected. The intensive experimental results demonstrate the effectiveness of this algorithm.
Tydén Patrik; Engström Gunnar; Schlyter Mona; André-Petersson Lena; Hedblad Bo
2011-01-01
Abstract Background Psychosocial stress has been identified as a risk factor in association with cardiovascular disease but less attention has been paid to heterogeneity in vulnerability to stress. The serial Color Word Test (CWT) measures adaptation to a stressful situation and it can be used to identify individuals that are vulnerable to stress. Prospective studies have shown that individuals with a maladaptive behavior in this test are exposed to an increased risk of future cardiovascular ...
Green, Nella; Hoenigl, Martin; Morris, Sheldon; Little, Susan J.
2015-01-01
Abstract The transgender community represents an understudied population in the literature. The objective of this study was to compare risk behavior, and HIV and sexually transmitted infection (STI) rates between transgender women and transgender men undergoing community-based HIV testing. With this retrospective analysis of a cohort study, we characterize HIV infection rates as well as reported risk behaviors and reported STI in 151 individual transgender women and 30 individual transgender ...
Linear regression and sensitivity analysis in nuclear reactor design
International Nuclear Information System (INIS)
Highlights: • Presented a benchmark for the applicability of linear regression to complex systems. • Applied linear regression to a nuclear reactor power system. • Performed neutronics, thermal–hydraulics, and energy conversion using Brayton’s cycle for the design of a GCFBR. • Performed detailed sensitivity analysis to a set of parameters in a nuclear reactor power system. • Modeled and developed reactor design using MCNP, regression using R, and thermal–hydraulics in Java. - Abstract: The paper presents a general strategy applicable for sensitivity analysis (SA), and uncertainity quantification analysis (UA) of parameters related to a nuclear reactor design. This work also validates the use of linear regression (LR) for predictive analysis in a nuclear reactor design. The analysis helps to determine the parameters on which a LR model can be fit for predictive analysis. For those parameters, a regression surface is created based on trial data and predictions are made using this surface. A general strategy of SA to determine and identify the influential parameters those affect the operation of the reactor is mentioned. Identification of design parameters and validation of linearity assumption for the application of LR of reactor design based on a set of tests is performed. The testing methods used to determine the behavior of the parameters can be used as a general strategy for UA, and SA of nuclear reactor models, and thermal hydraulics calculations. A design of a gas cooled fast breeder reactor (GCFBR), with thermal–hydraulics, and energy transfer has been used for the demonstration of this method. MCNP6 is used to simulate the GCFBR design, and perform the necessary criticality calculations. Java is used to build and run input samples, and to extract data from the output files of MCNP6, and R is used to perform regression analysis and other multivariate variance, and analysis of the collinearity of data
Acute myelogenous leukemia (AML) - children
Acute myelogenous leukemia - children; AML; Acute myeloid leukemia - children; Acute granulocytic leukemia - children; Acute myeloblastic leukemia - children; Acute non-lymphocytic leukemia (ANLL) - children
A Simulation Investigation of Principal Component Regression.
Allen, David E.
Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…
Regression Analysis and the Sociological Imagination
De Maio, Fernando
2014-01-01
Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.
Model selection in kernel ridge regression
DEFF Research Database (Denmark)
Exterkate, Peter
2013-01-01
Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different context...
Power Prediction in Smart Grids with Evolutionary Local Kernel Regression
Kramer, Oliver; Satzger, Benjamin; Lässig, Jörg
Electric grids are moving from a centralized single supply chain towards a decentralized bidirectional grid of suppliers and consumers in an uncertain and dynamic scenario. Soon, the growing smart meter infrastructure will allow the collection of terabytes of detailed data about the grid condition, e.g., the state of renewable electric energy producers or the power consumption of millions of private customers, in very short time steps. For reliable prediction strong and fast regression methods are necessary that are able to cope with these challenges. In this paper we introduce a novel regression technique, i.e., evolutionary local kernel regression, a kernel regression variant based on local Nadaraya-Watson estimators with independent bandwidths distributed in data space. The model is regularized with the CMA-ES, a stochastic non-convex optimization method. We experimentally analyze the load forecast behavior on real power consumption data. The proposed method is easily parallelizable, and therefore well appropriate for large-scale scenarios in smart grids.
Robust regression for large-scale neuroimaging studies.
Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand
2015-05-01
Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies.
Regression of Environmental Noise in LIGO Data
Tiwari, Vaibhav; Frolov, Valery; Klimenko, Sergey; Mitselmakher, Guenakh; Necula, Valentin; Prodi, Giovanni; Re, Virginia; Salemi, Francesco; Vedovato, Gabriele; Yakushin, Igor
2015-01-01
We address the problem of noise regression in the output of gravitational-wave (GW) interferometers, using data from the physical environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the gravitational-wave channel from the PEM measurements. One of the most promising regression method is based on the construction of Wiener-Kolmogorov filters. Using this method, the seismic noise cancellation from the LIGO GW channel has already been performed. In the presented approach the Wiener-Kolmogorov method has been extended, incorporating banks of Wiener filters in the time-frequency domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we presents the first results on regression of the bi-coherent noise in the LIGO data.
2013-01-01
Background Inappropriate antibiotic prescribing for nonbacterial infections leads to increases in the costs of care, antibiotic resistance among bacteria, and adverse drug events. Acute respiratory infections (ARIs) are the most common reason for inappropriate antibiotic use. Most prior efforts to decrease inappropriate antibiotic prescribing for ARIs (e.g., educational or informational interventions) have relied on the implicit assumption that clinicians inappropriately prescribe antibiotics because they are unaware of guideline recommendations for ARIs. If lack of guideline awareness is not the reason for inappropriate prescribing, educational interventions may have limited impact on prescribing rates. Instead, interventions that apply social psychological and behavioral economic principles may be more effective in deterring inappropriate antibiotic prescribing for ARIs by well-informed clinicians. Methods/design The Application of Behavioral Economics to Improve the Treatment of Acute Respiratory Infections (BEARI) Trial is a multisite, cluster-randomized controlled trial with practice as the unit of randomization. The primary aim is to test the ability of three interventions based on behavioral economic principles to reduce the rate of inappropriate antibiotic prescribing for ARIs. We randomized practices in a 2 × 2 × 2 factorial design to receive up to three interventions for non-antibiotic-appropriate diagnoses: 1) Accountable Justifications: When prescribing an antibiotic for an ARI, clinicians are prompted to record an explicit justification that appears in the patient electronic health record; 2) Suggested Alternatives: Through computerized clinical decision support, clinicians prescribing an antibiotic for an ARI receive a list of non-antibiotic treatment choices (including prescription options) prior to completing the antibiotic prescription; and 3) Peer Comparison: Each provider’s rate of inappropriate antibiotic prescribing relative to top
Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro
2012-11-01
Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan.
Darnah
2016-04-01
Poisson regression has been used if the response variable is count data that based on the Poisson distribution. The Poisson distribution assumed equal dispersion. In fact, a situation where count data are over dispersion or under dispersion so that Poisson regression inappropriate because it may underestimate the standard errors and overstate the significance of the regression parameters, and consequently, giving misleading inference about the regression parameters. This paper suggests the generalized Poisson regression model to handling over dispersion and under dispersion on the Poisson regression model. The Poisson regression model and generalized Poisson regression model will be applied the number of filariasis cases in East Java. Based regression Poisson model the factors influence of filariasis are the percentage of families who don't behave clean and healthy living and the percentage of families who don't have a healthy house. The Poisson regression model occurs over dispersion so that we using generalized Poisson regression. The best generalized Poisson regression model showing the factor influence of filariasis is percentage of families who don't have healthy house. Interpretation of result the model is each additional 1 percentage of families who don't have healthy house will add 1 people filariasis patient.
Applied Regression Modeling A Business Approach
Pardoe, Iain
2012-01-01
An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a
Regression of altitude-produced cardiac hypertrophy.
Sizemore, D. A.; Mcintyre, T. W.; Van Liere, E. J.; Wilson , M. F.
1973-01-01
The rate of regression of cardiac hypertrophy with time has been determined in adult male albino rats. The hypertrophy was induced by intermittent exposure to simulated high altitude. The percentage hypertrophy was much greater (46%) in the right ventricle than in the left (16%). The regression could be adequately fitted to a single exponential function with a half-time of 6.73 plus or minus 0.71 days (90% CI). There was no significant difference in the rates of regression for the two ventricles.
A Regression Analysis Model Based on Wavelet Networks
Institute of Scientific and Technical Information of China (English)
XIONG Zheng-feng
2002-01-01
In this paper, an approach is proposed to combine wavelet networks and techniques of regression analysis. The resulting wavelet regression estimator is well suited for regression estimation of moderately large dimension, in particular for regressions with localized irregularities.
Robust Logistic Regression to Static Geometric Representation of Ratios
Directory of Open Access Journals (Sweden)
Alireza Bahiraie
2009-01-01
Full Text Available Problem statement: Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-salacity were solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. This new method would be a general methodological guideline associated with financial data and bankruptcy risk. Approach: We proposed the use of a new measure of risk, the Share Risk (SR measure. We provided evidence of the extent to which changes in values of this index are associated with changes in each axis values and how this may alter our economic interpretation of changes in the patterns and directions. Our simple methodology provided a geometric illustration of the new proposed risk measure and transformation behavior. This study also employed Robust logit method, which extends the logit model by considering outlier. Results: Results showed new SR method obtained better numerical results in compare to common ratios approach. With respect to accuracy results, Logistic and Robust Logistic Regression Analysis illustrated that this new transformation (SR produced more accurate prediction statistically and can be used as an alternative for common ratios. Additionally, robust logit model outperforms logit model in both approaches and was substantially superior to the logit method in predictions to assess sample forecast performances and regressions. Conclusion/Recommendations: This study presented a new perspective on the study of firm financial statement and bankruptcy. In this study, a new dimension to risk measurement and data representation with the advent of the Share Risk method (SR was proposed. With respect to forecast results, robust loigt method was substantially superior to the logit method. It was strongly suggested the use of SR methodology for ratio analysis, which provided a conceptual and complimentary methodological solution to many problems associated with the
Some Simple Computational Formulas for Multiple Regression
Aiken, Lewis R., Jr.
1974-01-01
Short-cut formulas are presented for direct computation of the beta weights, the standard errors of the beta weights, and the multiple correlation coefficient for multiple regression problems involving three independent variables and one dependent variable. (Author)
Patterns of Regression in Rett Syndrome
Directory of Open Access Journals (Sweden)
J Gordon Millichap
2002-10-01
Full Text Available Patterns and features of regression in a case series of 53 girls and women with Rett syndrome were studied at the Institute of Child Health and Great Ormond Street Children’s Hospital, London, UK.
Regression Analysis with a Stochastic Design Variable
Sazak,, Hakan S.; Moti L Tiku; Qamarul Islam, M.
2006-01-01
In regression models, the design variable has primarily been treated as a nonstochastic variable. In numerous situations, however, the design variable is stochastic. The estimation and hypothesis testing problems in such situations are considered. Real life examples are given.
An Improved Volumetric Estimation Using Polynomial Regression
Directory of Open Access Journals (Sweden)
Noraini Abdullah
2011-12-01
Full Text Available The polynomial regression (PR technique is used to estimate the parameters of the dependent variable having a polynomial relationship with the independent variable. Normality and nonlinearity exhibit polynomial characterization of power terms greater than 2. Polynomial Regression models (PRM with the auxiliary variables are considered up to their third order interactions. Preliminary, multicollinearity between the independent variables is minimized and statistical tests involving the Global, Correlation Coefficient, Wald, and Goodness-of-Fit tests, are carried out to select significant variables with their possible interactions. Comparisons between the polynomial regression models (PRM are made using the eight selection criteria (8SC. The best regression model is identified based on the minimum value of the eight selection criteria (8SC. The use of an appropriate transformation will increase in the degree of a statistically valid polynomial, hence, providing a better estimation for the model.
Vectors, a tool in statistical regression theory
Corsten, L.C.A.
1958-01-01
Using linear algebra this thesis developed linear regression analysis including analysis of variance, covariance analysis, special experimental designs, linear and fertility adjustments, analysis of experiments at different places and times. The determination of the orthogonal projection, yielding e
A new bivariate negative binomial regression model
Faroughi, Pouya; Ismail, Noriszura
2014-12-01
This paper introduces a new form of bivariate negative binomial (BNB-1) regression which can be fitted to bivariate and correlated count data with covariates. The BNB regression discussed in this study can be fitted to bivariate and overdispersed count data with positive, zero or negative correlations. The joint p.m.f. of the BNB1 distribution is derived from the product of two negative binomial marginals with a multiplicative factor parameter. Several testing methods were used to check overdispersion and goodness-of-fit of the model. Application of BNB-1 regression is illustrated on Malaysian motor insurance dataset. The results indicated that BNB-1 regression has better fit than bivariate Poisson and BNB-2 models with regards to Akaike information criterion.
Heteroscedastic regression analysis method for mixed data
Institute of Scientific and Technical Information of China (English)
FU Hui-min; YUE Xiao-rui
2011-01-01
The heteroscedastic regression model was established and the heteroscedastic regression analysis method was presented for mixed data composed of complete data, type- I censored data and type- Ⅱ censored data from the location-scale distribution. The best unbiased estimations of regression coefficients, as well as the confidence limits of the location parameter and scale parameter were given. Furthermore, the point estimations and confidence limits of percentiles were obtained. Thus, the traditional multiple regression analysis method which is only suitable to the complete data from normal distribution can be extended to the cases of heteroscedastic mixed data and the location-scale distribution. So the presented method has a broad range of promising applications.
Prediction of Dynamical Systems by Symbolic Regression
Quade, Markus; Shafi, Kamran; Niven, Robert K; Noack, Bernd R
2016-01-01
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting a...
Chauke, Miyetani; Malisch, Jessica L.; Robinson, Cymphonee; de Jong, Trynke R.; Saltzman, Wendy
2011-01-01
In several mammalian species, lactating females show blunted neural, hormonal, and behavioral responses to stressors. It is not known whether new fathers also show stress hyporesponsiveness in species in which males provide infant care. To test this possibility, we determined the effects of male and female reproductive status on stress responsiveness in the biparental, monogamous California mouse (Peromyscus californicus).Breeding (N=8 females, 8 males), nonbreeding (N=10 females, 10 males) a...
Bayesian nonparametric regression with varying residual density
Pati, Debdeep; Dunson, David B.
2013-01-01
We consider the problem of robust Bayesian inference on the mean regression function allowing the residual density to change flexibly with predictors. The proposed class of models is based on a Gaussian process prior for the mean regression function and mixtures of Gaussians for the collection of residual densities indexed by predictors. Initially considering the homoscedastic case, we propose priors for the residual density based on probit stick-breaking (PSB) scale mixtures and symmetrized ...
Tests in contingency tables as regression tests
Stanislav Anatolyev; Grigory Kosenok
2006-01-01
Applied researchers often use tests based on contingency tables in preliminary data analysis and diagnostic testing. We show that many of such tests may be alternatively implemented by testing for coecient restrictions in linear regression systems (as a rule, employing the Wald test). This uni es the theories of regression analysis and contingency tables, sheds more light on intuitive contents of contingency table tests, and provides a more convenient and familiar tool for practitioners.
Regression Models for Market-Shares
DEFF Research Database (Denmark)
Birch, Kristina; Olsen, Jørgen Kai; Tjur, Tue
2005-01-01
On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put on the...... interpretation of the parameters in relation to models for the total sales based on discrete choice models.Key words and phrases. MCI model, discrete choice model, market-shares, price elasitcity, regression model....
Asymptotic equivalence for regression under fractional noise
Schmidt-Hieber, Johannes
2013-01-01
Consider estimation of the regression function based on a model with equidistant design and measurement errors generated from a fractional Gaussian noise process. In previous literature, this model has been heuristically linked to an experiment, where the anti-derivative of the regression function is continuously observed under additive perturbation by a fractional Brownian motion. Based on a reformulation of the problem using reproducing kernel Hilbert spaces, we derive abstract approximatio...
Spontaneous partial regression of cerebral arteriovenous malformation
Energy Technology Data Exchange (ETDEWEB)
Choi, Jae Ho; Shin, Ji Hoon; Cho, Seong Shik; Choi, Deuk Lin; Byun, Bark Jang; Kim, Dong Won [Soonchunhyang University College of Medicine, Seoul (Korea, Republic of)
2002-01-01
Arteriovenous malformation (AVM) of the brain is one of the important pathologic conditions which cause intracerebral or subarachnoid hemorrhage, epilepsy, or chronic cerebral ischemia. The spontaneous regression of cerebral AVM is reported to be very rare and more likely to occur when the AVM is small, is accompanied by hemorrhage, and has fewer arterial feeders. We report a case of right occipital AVM which at follow-up angiography performed four years later showed near-complete spontaneous regression.
Marginal longitudinal semiparametric regression via penalized splines
Al Kadiri, M.
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Lognormal and Gamma Mixed Negative Binomial Regression
Zhou, Mingyuan; Li, Lingbo; Dunson, David; Carin, Lawrence
2012-01-01
In regression analysis of counts, a lack of simple and efficient algorithms for posterior computation has made Bayesian approaches appear unattractive and thus underdeveloped. We propose a lognormal and gamma mixed negative binomial (NB) regression model for counts, and present efficient closed-form Bayesian inference; unlike conventional Poisson models, the proposed approach has two free parameters to include two different kinds of random effects, and allows the incorporation of prior inform...
The Infinite Hierarchical Factor Regression Model
Rai, Piyush
2009-01-01
We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.
An Improved Volumetric Estimation Using Polynomial Regression
Noraini Abdullah; Amran Ahmed; Zainodin Hj. Jubok
2011-01-01
The polynomial regression (PR) technique is used to estimate the parameters of the dependent variable having a polynomial relationship with the independent variable. Normality and nonlinearity exhibit polynomial characterization of power terms greater than 2. Polynomial Regression models (PRM) with the auxiliary variables are considered up to their third order interactions. Preliminary, multicollinearity between the independent variables is minimized and statistical tests involving the Global...
Spontaneous regression of metastatic Merkel cell carcinoma.
LENUS (Irish Health Repository)
Hassan, S J
2010-01-01
Merkel cell carcinoma is a rare aggressive neuroendocrine carcinoma of the skin predominantly affecting elderly Caucasians. It has a high rate of local recurrence and regional lymph node metastases. It is associated with a poor prognosis. Complete spontaneous regression of Merkel cell carcinoma has been reported but is a poorly understood phenomenon. Here we present a case of complete spontaneous regression of metastatic Merkel cell carcinoma demonstrating a markedly different pattern of events from those previously published.
Marginal longitudinal semiparametric regression via penalized splines.
Kadiri, M Al; Carroll, R J; Wand, M P
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Post-processing through linear regression
Directory of Open Access Journals (Sweden)
B. Van Schaeybroeck
2011-03-01
Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.
These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.
Post-processing through linear regression
van Schaeybroeck, B.; Vannitsem, S.
2011-03-01
Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.
Synthesizing regression results: a factored likelihood method.
Wu, Meng-Jia; Becker, Betsy Jane
2013-06-01
Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported in the regression studies to calculate synthesized standardized slopes. It uses available correlations to estimate missing ones through a series of regressions, allowing us to synthesize correlations among variables as if each included study contained all the same variables. Great accuracy and stability of this method under fixed-effects models were found through Monte Carlo simulation. An example was provided to demonstrate the steps for calculating the synthesized slopes through sweep operators. By rearranging the predictors in the included regression models or omitting a relatively small number of correlations from those models, we can easily apply the factored likelihood method to many situations involving synthesis of linear models. Limitations and other possible methods for synthesizing more complicated models are discussed. Copyright © 2012 John Wiley & Sons, Ltd. PMID:26053653
Institute of Scientific and Technical Information of China (English)
余学; 戴秀英; 李秋丽; 王玲玲; 李林贵
2014-01-01
Objective To understand the behavioral problems and related factors of left-behind children in rural areas of Ningxia . Methods A total of 2000 students were sampled by stratified randomly and cluster from the whole class of the southern rural areas in Ningxia.The general self-made questionnaire,Egma Minnen av Bardndosnauppforstran (EMBU),Eysenck Personality Questionnaire(EPQ Children),Piers-Harri Children's Self-concept Scale(PHCSS)and Achenbach's Child behavior Checklist(CBCL parent version)were used to investigate the related factors .Results ①The overall detection rate of child behavior problems was 18.0%(343/1905).The detection rate of left-behind children and non-left-behind children was 20.9%and 16.0%respectively,and the difference was significant between the two groups(χ2 =7.66,P=0.006).The behavior problems of Han left behind and non-left-behind children were detected in 17.0%and 11.2%respectively,and there was significant difference between two groups (χ2 =6.64,P=0.010).The detection rate of Muslim left-behind children behavioral problems (25.1%) was significantly higher than that of Han left-behind children(17.0%)(χ2 =7.51,P=0.006).②Multivariate logistic regression analysis showed that parents working outside (OR=1.239),Extraversion personality (OR=0.807),Neurotic personality(OR=1.310),father overprotection(OR=1.727),mother refusing and denying(OR=1.561)and total score of self-awareness(OR=0.613)eventually entered the equation,which could be directly predicted the occurrence of psycholog-ical and behavioral problems .Emotional instability ,father overprotection ,mother refusing and denying ,and both parents working outside were risk factors ,whereas the extroversion ( high score features ) and good self-awareness were protective factors .Conclusion Left-behind children have higher incidence of behavioral problems in rural areas of Ningxia ,which has many influence factors .Measures should be taken from social ,family,character building and other
Directory of Open Access Journals (Sweden)
Wig J
1978-01-01
Full Text Available 550 cases of acute abdomen have been analysed in detail includ-ing their clinical presentation and operative findings. Males are more frequently affected than females in a ratio of 3: 1. More than 45% of patients presented after 48 hours of onset of symptoms. Intestinal obstruction was the commonest cause of acute abdomen (47.6%. External hernia was responsible for 26% of cases of intestinal obstruction. Perforated peptic ulcer was the commonest cause of peritonitis in the present series (31.7% while incidence of biliary peritonitis was only 2.4%.. The clinical accuracy rate was 87%. The mortality in operated cases was high (10% while the over-all mortality rate was 7.5%.
Ginty, Annie T; Williams, Sarah E; Jones, Alexander; Roseboom, Tessa J; Phillips, Anna C; Painter, Rebecca C; Carroll, Douglas; de Rooij, Susanne R
2016-06-01
Recent evidence demonstrates that individuals with low heart rate (HR) reactions to acute psychological stress are more likely to be obese or smokers. Smoking and obesity are established risk factors for increased carotid intima-media thickness (IMT). The aim of this study was to examine the potential pathways linking intima-media thickness, smoking, body mass index (BMI), and HR stress reactivity. A total of 552 participants, 47.6% male, M (SD) age = 58.3 (0.94) years, were exposed to three psychological stress tasks (Stroop, mirror drawing, and speech) preceded by a resting baseline period; HR was recorded throughout. HR reactivity was calculated as the average response across the three tasks minus average baseline HR. Smoking status, BMI, and IMT were determined by trained personnel. Controlling for important covariates (e.g., socioeconomic status), structural equation modeling revealed that BMI and smoking mediated the negative relationship between HR reactivity and IMT. The hypothesized model demonstrated a good overall fit to the data, χ(2) (8) = 0.692, p = .403; CFI = 1.00; TLI = 1.00 SRMR = .01; RMSEA < .001 (90% CI < 0.01-0.11). HR reactivity was negatively related to BMI (β = -.16) and smoking (β = -.18), and these in turn were positively associated with IMT (BMI: β = .10; smoking: β = .17). Diminished HR stress reactivity appears to be a marker for enlarged IMT and appears to be exerting its impact through already established risks. Future research should examine this relationship longitudinally and aim to intervene early. PMID:27005834
Hierarchical regression for analyses of multiple outcomes.
Richardson, David B; Hamra, Ghassan B; MacLehose, Richard F; Cole, Stephen R; Chu, Haitao
2015-09-01
In cohort mortality studies, there often is interest in associations between an exposure of primary interest and mortality due to a range of different causes. A standard approach to such analyses involves fitting a separate regression model for each type of outcome. However, the statistical precision of some estimated associations may be poor because of sparse data. In this paper, we describe a hierarchical regression model for estimation of parameters describing outcome-specific relative rate functions and associated credible intervals. The proposed model uses background stratification to provide flexible control for the outcome-specific associations of potential confounders, and it employs a hierarchical "shrinkage" approach to stabilize estimates of an exposure's associations with mortality due to different causes of death. The approach is illustrated in analyses of cancer mortality in 2 cohorts: a cohort of dioxin-exposed US chemical workers and a cohort of radiation-exposed Japanese atomic bomb survivors. Compared with standard regression estimates of associations, hierarchical regression yielded estimates with improved precision that tended to have less extreme values. The hierarchical regression approach also allowed the fitting of models with effect-measure modification. The proposed hierarchical approach can yield estimates of association that are more precise than conventional estimates when one wishes to estimate associations with multiple outcomes. PMID:26232395
Regression Test Selection for C# Programs
Directory of Open Access Journals (Sweden)
Nashat Mansour
2009-01-01
Full Text Available We present a regression test selection technique for C# programs. C# is fairly new and is often used within the Microsoft .Net framework to give programmers a solid base to develop a variety of applications. Regression testing is done after modifying a program. Regression test selection refers to selecting a suitable subset of test cases from the original test suite in order to be rerun. It aims to provide confidence that the modifications are correct and did not affect other unmodified parts of the program. The regression test selection technique presented in this paper accounts for C#.Net specific features. Our technique is based on three phases; the first phase builds an Affected Class Diagram consisting of classes that are affected by the change in the source code. The second phase builds a C# Interclass Graph (CIG from the affected class diagram based on C# specific features. In this phase, we reduce the number of selected test cases. The third phase involves further reduction and a new metric for assigning weights to test cases for prioritizing the selected test cases. We have empirically validated the proposed technique by using case studies. The empirical results show the usefulness of the proposed regression testing technique for C#.Net programs.
Mental chronometry with simple linear regression.
Chen, J Y
1997-10-01
Typically, mental chronometry is performed by means of introducing an independent variable postulated to affect selectively some stage of a presumed multistage process. However, the effect could be a global one that spreads proportionally over all stages of the process. Currently, there is no method to test this possibility although simple linear regression might serve the purpose. In the present study, the regression approach was tested with tasks (memory scanning and mental rotation) that involved a selective effect and with a task (word superiority effect) that involved a global effect, by the dominant theories. The results indicate (1) the manipulation of the size of a memory set or of angular disparity affects the intercept of the regression function that relates the times for memory scanning with different set sizes or for mental rotation with different angular disparities and (2) the manipulation of context affects the slope of the regression function that relates the times for detecting a target character under word and nonword conditions. These ratify the regression approach as a useful method for doing mental chronometry. PMID:9347535
On the interactions between top-down anticipation and bottom-up regression
Directory of Open Access Journals (Sweden)
Jun Tani
2007-11-01
Full Text Available This paper discusses the importance of anticipation and regression in modeling cognitive behavior. The meanings of these cognitive functions are explained by describing our proposed neural network model which has been implemented on a set of cognitive robotics experiments. The reviews of these experiments suggest that the essences of embodied cognition may reside in the phenomena of the break-down between the top-down anticipation and the bottom-up regression and in its recovery process.
Regressão da fibrose hepática Regression of hepatic fibrosis
Directory of Open Access Journals (Sweden)
Zilton A. Andrade
2005-12-01
Full Text Available Durante muito tempo, se acreditou que a fibrose hepática extensa e de longa duração fosse um processo irreversível. As investigações sobre o comportamento da fibrose hepática, nas formas avançadas da esquistossomose, vieram abalar este conceito e hoje em dia está se estabelecendo a noção de que qualquer fibrose é reversível, inclusive aquela associada à cirrose hepática. O problema é identificar sua causa e removê-la. Embora, a fibrose hepática tenha per se pouca significação fisiopatológica, sua gravidade está relacionada com as alterações vasculares que ela encerra. O que dá ao assunto primordial importância são os indícios até aqui obtidos de que, a regressão da fibrose costuma se acompanhar de uma remodelação das alterações vasculares no seu interior. Mas, há peculiaridades relativas ao tipo anatômico e ao papel fisiológico que certas fibroses exibem, e tais peculiaridades podem interferir com o processo regressivo da mesma, o que pode significar que por vezes a fibrose pode se tornar permanente. Esses assuntos, alguns deles controversos, são aqui apresentados e discutidos.Extensive and persistent hepatic fibrosis has for a long time been considered irreversible. However, recent studies on the behavior of hepatic fibrosis, especially those related to evolution and involution of advanced schistosomiasis in man, have challenged this concept, and nowadays it is becoming clear that any type of fibrosis is reversible, including that associated with hepatic cirrhosis. The problem consists in identifying and eliminating its cause. Although fibrosis in the liver has little functional significance by itself, its severity derives from associated vascular changes. However, new data on fibrosis regression indicate that disappearance of fibrosis is usually accompanied by remodeling of vascular changes. But, there are peculiarities related to the anatomic type of fibrosis and to its functional significance, which
Rahier, J F; Lion, L; Dewit, O; Lambert, M
2005-01-01
The association of inflammatory bowel disease and acute febrile neutrophilic dermatitis (Sweet's syndrome) has infrequently been reported in the literature. We describe the case of a 41-year-old Caucasian woman with ileo- anal Crohn's disease who presented simultaneously an erythema nodosum and a Sweet's syndrome. A dramatic regression of the cutaneous lesions was observed after infliximab treatment, indicating that this therapy might be useful for both Crohn's disease and Sweet's syndrome. PMID:16268426
Directory of Open Access Journals (Sweden)
Federico A. Sturzeneger
1992-03-01
Full Text Available Currency Substitution and the Regressivity of Inflationary Taxation The purpose of this paper is to show that in the presence of financial adaptation or currency substitution. the inflation tax is extremely regressive. This regressivity arises from the existence of a fixed cost of switching to inflation-proof transactions technologies. This fixed cost makes it optimal only for those agents with sufficiently high incomes to switch out of domestic currency. The effects are illustrated and quantified for a particular case.
Directory of Open Access Journals (Sweden)
David C. Randall
2011-08-01
Full Text Available We recorded via telemetry the arterial blood pressure (BP and heart rate (HR response to classical conditioning following the spontaneous onset of autoimmune diabetes in BBDP/Wor rats versus age-matched, diabetes resistant control (BBDR/Wor rats. Our purpose was to evaluate the autonomic regulatory responses to an acute stress in a diabetic state of up to 12 months duration. The stress was a 15 sec. pulsed tone (CS+ followed by a 0.5 sec. tail shock. The initial, transient increase in BP (i.e., the ‘first component’, or C1, known to be derived from an orienting response and produced by a sympathetic increase in peripheral resistance, was similar in diabetic and control rats through ~9 months of diabetes; it was smaller in diabetic rats 10 months after diabetes onset. Weakening of the C1 BP increase in rats that were diabetic for > 10 months is consistent with the effects of sympathetic neuropathy. A longer-latency, smaller, but sustained ‘second component’ (C2 conditional increase in BP, that is acquired as a rat learns the association between CS+ and the shock, and which results from an increase in cardiac output, was smaller in the diabetic vs. control rats starting from the first month of diabetes. A concomitant HR slowing was also smaller in diabetic rats. The difference in the C2 BP increase, as observed already during the first month of diabetes, is probably secondary to the effects of hyperglycemia upon myocardial metabolism and contractile function, but it may also result from effects on cognition. The small HR slowing concomitant with the C2 pressor event is probably secondary to differences in baroreflex activation or function, though parasympathetic dysfunction may contribute later in the duration of diabetes. The nearly immediate deficit after disease onset in the C2 response indicates that diabetes alters BP and HR responses to external challenges prior to the development of structural changes in the vasculature or autonomic
KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS
Directory of Open Access Journals (Sweden)
HANY DEVITA
2015-02-01
Full Text Available Ordinary least square is a parameter estimations for minimizing residual sum of squares. If the multicollinearity was found in the data, unbias estimator with minimum variance could not be reached. Multicollinearity is a linear correlation between independent variabels in model. Jackknife Ridge Regression(JRR as an extension of Generalized Ridge Regression (GRR for solving multicollinearity. Generalized Ridge Regression is used to overcome the bias of estimators caused of presents multicollinearity by adding different bias parameter for each independent variabel in least square equation after transforming the data into an orthoghonal form. Beside that, JRR can reduce the bias of the ridge estimator. The result showed that JRR model out performs GRR model.
On spline approximation of sliced inverse regression
Institute of Scientific and Technical Information of China (English)
Li-ping ZHU; Zhou YU
2007-01-01
The dimension reduction is helpful and often necessary in exploring the nonparametric regression structure. In this area, Sliced inverse regression (SIR) is a promising tool to estimate the central dimension reduction (CDR) space. To estimate the kernel matrix of the SIR, we herein suggest the spline approximation using the least squares regression. The heteroscedasticity can be incorporated well by introducing an appropriate weight function. The root-n asymptotic normality can be achieved for a wide range choice of knots. This is essentially analogous to the kernel estimation. Moreover,we also propose a modified Bayes information criterion (BIC) based on the eigenvalues of the SIR matrix. This modified BIC can be applied to any form of the SIR and other related methods. The methodology and some of the practical issues are illustrated through the horse mussel data. Empirical studies evidence the performance of our proposed spline approximation by comparison of the existing estimators.
On Solving Lq-Penalized Regressions
Directory of Open Access Journals (Sweden)
Tracy Zhou Wu
2007-01-01
Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.
Linear and robust Gaussian regression filters
International Nuclear Information System (INIS)
This paper presents a brief overview about Gaussian regression filters to extract surface roughness. The mathematical background in the spatial as well as in the frequency domain is discussed. It is shown that Gaussian regression filters work without any running in and running out sections and can approximate form up to pth degree. In the industrial world it is well known that linear filters are non robust, which means that any protruding peak or valley (also called 'outlier') leads to a distorted roughness topography and effects the calculation of surface parameters directly. In particular plateau like surfaces are good candidates for such critical datasets. In the paper it is shown that such a distortion can be avoided by choosing an appropriate Ψ function. This proceeding leads to the so called robust Gaussian regression filter with all the advanced properties of the linear one
Variable and subset selection in PLS regression
DEFF Research Database (Denmark)
Høskuldsson, Agnar
2001-01-01
The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...... obtained by different methods. We also present an approach to orthogonal scatter correction. The procedures and comparisons are applied to industrial data. (C) 2001 Elsevier Science B.V. All rights reserved....
Principal component regression for crop yield estimation
Suryanarayana, T M V
2016-01-01
This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...
Uncertainty quantification in DIC with Kriging regression
Wang, Dezhi; DiazDelaO, F. A.; Wang, Weizhuo; Lin, Xiaoshan; Patterson, Eann A.; Mottershead, John E.
2016-03-01
A Kriging regression model is developed as a post-processing technique for the treatment of measurement uncertainty in classical subset-based Digital Image Correlation (DIC). Regression is achieved by regularising the sample-point correlation matrix using a local, subset-based, assessment of the measurement error with assumed statistical normality and based on the Sum of Squared Differences (SSD) criterion. This leads to a Kriging-regression model in the form of a Gaussian process representing uncertainty on the Kriging estimate of the measured displacement field. The method is demonstrated using numerical and experimental examples. Kriging estimates of displacement fields are shown to be in excellent agreement with 'true' values for the numerical cases and in the experimental example uncertainty quantification is carried out using the Gaussian random process that forms part of the Kriging model. The root mean square error (RMSE) on the estimated displacements is produced and standard deviations on local strain estimates are determined.
LINEAR REGRESSION WITH R AND HADOOP
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Bogdan OANCEA
2015-07-01
Full Text Available In this paper we present a way to solve the linear regression model with R and Hadoop using the Rhadoop library. We show how the linear regression model can be solved even for very large models that require special technologies. For storing the data we used Hadoop and for computation we used R. The interface between R and Hadoop is the open source library RHadoop. We present the main features of the Hadoop and R software systems and the way of interconnecting them. We then show how the least squares solution for the linear regression problem could be expressed in terms of map-reduce programming paradigm and how could be implemented using the Rhadoop library.
Competing Risks Quantile Regression at Work
DEFF Research Database (Denmark)
Dlugosz, Stephan; Lo, Simon M. S.; Wilke, Ralf
2016-01-01
Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use...... large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights...... into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available....
LINEAR REGRESSION WITH R AND HADOOP
Oancea, Bogdan
2015-01-01
In this paper we present a way to solve the linear regression model with R and Hadoop using the Rhadoop library. We show how the linear regression model can be solved even for very large models that require special technologies. For storing the data we used Hadoop and for computation we used R. The interface between R and Hadoop is the open source library RHadoop. We present the main features of the Hadoop and R software systems and the way of interconnecting them. We then show how the least ...
Panel data specifications in nonparametric kernel regression
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...... parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...... found the estimates of the fully nonparametric panel data model to be more reliable....
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Detecting plant health conditions plays a key role in farm pest management and crop protection. In this study,measurement of hyperspectral leaf reflectance in rice crop (Oryzasativa L.) was conducted on groups of healthy and infected leaves by the fungus Bipolaris oryzae (Helminthosporium oryzae Breda. de Hann) through the wavelength range from 350 to 2 500 nm. The percentage of leaf surface lesions was estimated and defined as the disease severity. Statistical methods like multiple stepwise regression, principal component analysis and partial least-square regression were utilized to calculate and estimate the disease severity of rice brown spot at the leaf level. Our results revealed that multiple stepwise linear regressions could efficiently estimate disease severity with three wavebands in seven steps. The root mean square errors (RMSEs) for training (n=210) and testing (n=53) dataset were 6.5% and 5.8%, respectively. Principal component analysis showed that the first principal component could explain approximately 80% of the variance of the original hyperspectral reflectance. The regression model with the first two principal components predicted a disease severity with RMSEs of 16.3% and 13.9% for the training and testing dataset, respectively. Partial least-square regression with seven extracted factors could most effectively predict disease severity compared with other statistical methods with RMSEs of 4.1% and 2.0% for the training and testing dataset, respectively. Our research demonstrates that it is feasible to estimate the disease severity office brown spot using hyperspectral reflectance data at the leaf level.
Recurrence of hepatocellular carcinoma with rapid growth after spontaneous regression
Institute of Scientific and Technical Information of China (English)
Tomoki Nakajima; Michihisa Moriguchi; Tadashi Watanabe; Masao Noda; Nobuaki Fuji; Masahito Minami; Yoshito Itoh; Takeshi Okanoue
2004-01-01
We report an 80-year-old man who presented with spontaneous regression of hepatocellular carcinoma (HCC). He complained of sudden right flank pain and low-grade fever.The level of protein induced by vitamin K antagonist (PIVKA)-Ⅱ was 1 137 mAU/mL. A computed tomography scan in November 2000 demonstrated a low-density mass located in liver S4 with marginal enhancement and a cystic mass of 68 mmx55 mm in liver S6, with slightly high density content and without marginal enhancement. Angiography revealed that the tumor in S4 with a size of 25 mm×20 mm was a typical hypervascular HCC, and transarterial chemoembolization was performed. However, the tumor in S6 was hypovascular and atypical of HCC, and thus no therapy was given. In December 2000, the cystic mass regressed spontaneously to 57 mmx44 mm, and aspiration cytology revealed bloody fluid, and the mass was diagnosed cytologically as class Ⅰ.The tumor in S4 was treated successfully with a 5 mm margin of safety around it. The PⅣKA-Ⅱ level normalized in February2001. In July 2001, the tumor regressed further but presented with an enhanced area at the posterior margin. In November2001, the enhanced area extended, and a biopsy revealed well-differentiated HCC, although the previous tumor in S4 disappeared. Angiography demonstrated two tumor stains, one was in S6, which was previously hypovascular,and the other was in S8. Subsequently, the PⅣKA-Ⅱ level started to rise with the doubling time of 2-3 wk, and the tumor grew rapidly despite repeated transarterial embolization with gel foam. In February 2003, the patient died of bleeding into the peritoneal cavity from the tumor that occupied almost the entire right lobe. Considering the acute onset of the symptoms, we speculate that local ischemia possibly due to rapid tumor growth, resulted in intratumoral bleeding and/or hemorrhagic necrosis, and finally spontaneous regression of the initial tumor in S6.
Institute of Scientific and Technical Information of China (English)
杨亚佳; 陆群峰; 曾莉
2013-01-01
[目的]通过对急性冠脉综合征(Acute Coronary Syndrome,ACS)患者进行心理状态评估及干预,评价认知行为干预在ACS患者护理中的作用.[方法]本研究连续选取2011年10月至2012年2月期间,在同济大学附属第十人民医院CCU住院的174例ACS患者,分为干预组和对照组,在各组中进行临床特点比较,完成抑郁自评量表(SDS)和焦虑自评量表(SAS)测评,干预组进行认知行为干预3个月后进行再次心理评估,观察SDS、SAS分值变化以及预后情况.[结果]在ACS患者中进行干预对照研究结果显示,干预组患者的临床症状缓解较对照组明显,且二次心理量表测评抑郁焦虑程度较前明显好转.[结论]ACS患者中有相当一部分存在焦虑抑郁情绪,认知行为干预对其症状缓解起到积极作用,需重视认知行为干预.%[Objective] To assess the role of cognitive behavior intervention in the nursing of patients with acute coronary syndrome (ACS) through the evaluation and intervention of mental state of ACS patients. [Methods] In the study, 174 ACS inpatients in CCU of the tenth people's hospital affiliated to Tongji university from Oct. 2011 to Feb. 2012 were continuously chosen. All patients were divided into intervention group and control group. Clinical characteristics were compared between two groups. Self-rating depression scale (SDS ) and self-rating anxiety scale (SAS) assessment were completed. Psychological assessment was performed for the intervention group 3 months after cognitive behavioral intervention. The changes of SDS and SAS scores and prognosis were observed. [Results] The results of the comparative study of the intervention for ACS patients showed that the remission of clinical symptoms of patients in intervention group was more obvious than that in control group, and anxiety and depression by two psychological assessments were improved compared with before intervention SDS score: 0. 468±0. 069 vs 0. 437±0. 067, P =0
Demonstration of a Fiber Optic Regression Probe
Korman, Valentin; Polzin, Kurt A.
2010-01-01
The capability to provide localized, real-time monitoring of material regression rates in various applications has the potential to provide a new stream of data for development testing of various components and systems, as well as serving as a monitoring tool in flight applications. These applications include, but are not limited to, the regression of a combusting solid fuel surface, the ablation of the throat in a chemical rocket or the heat shield of an aeroshell, and the monitoring of erosion in long-life plasma thrusters. The rate of regression in the first application is very fast, while the second and third are increasingly slower. A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor is optical, using two different, co-located fiber-optics to perform the regression measurement. The disparate optical transmission properties of the two fiber-optics makes it possible to measure the regression rate by monitoring the relative light attenuation through the fibers. As the fibers regress along with the parent material in which they are embedded, the relative light intensities through the two fibers changes, providing a measure of the regression rate. The optical nature of the system makes it relatively easy to use in a variety of harsh, high temperature environments, and it is also unaffected by the presence of electric and magnetic fields. In addition, the sensor could be used to perform optical spectroscopy on the light emitted by a process and collected by fibers, giving localized measurements of various properties. The capability to perform an in-situ measurement of material regression rates is useful in addressing a variety of physical issues in various applications. An in-situ measurement allows for real-time data regarding the erosion rates, providing a quick method for
Logistic regression when binary predictor variables are highly correlated.
Barker, L; Brown, C
Standard logistic regression can produce estimates having large mean square error when predictor variables are multicollinear. Ridge regression and principal components regression can reduce the impact of multicollinearity in ordinary least squares regression. Generalizations of these, applicable in the logistic regression framework, are alternatives to standard logistic regression. It is shown that estimates obtained via ridge and principal components logistic regression can have smaller mean square error than estimates obtained through standard logistic regression. Recommendations for choosing among standard, ridge and principal components logistic regression are developed. Published in 2001 by John Wiley & Sons, Ltd.
Modeling data for pancreatitis in presence of a duodenal diverticula using logistic regression
Dineva, S.; Prodanova, K.; Mlachkova, D.
2013-12-01
The presence of a periampullary duodenal diverticulum (PDD) is often observed during upper digestive tract barium meal studies and endoscopic retrograde cholangiopancreatography (ERCP). A few papers reported that the diverticulum had something to do with the incidence of pancreatitis. The aim of this study is to investigate if the presence of duodenal diverticula predisposes to the development of a pancreatic disease. A total 3966 patients who had undergone ERCP were studied retrospectively. They were divided into 2 groups-with and without PDD. Patients with a duodenal diverticula had a higher rate of acute pancreatitis. The duodenal diverticula is a risk factor for acute idiopathic pancreatitis. A multiple logistic regression to obtain adjusted estimate of odds and to identify if a PDD is a predictor of acute or chronic pancreatitis was performed. The software package STATISTICA 10.0 was used for analyzing the real data.
Bayesian nonparametric regression with varying residual density.
Pati, Debdeep; Dunson, David B
2014-02-01
We consider the problem of robust Bayesian inference on the mean regression function allowing the residual density to change flexibly with predictors. The proposed class of models is based on a Gaussian process prior for the mean regression function and mixtures of Gaussians for the collection of residual densities indexed by predictors. Initially considering the homoscedastic case, we propose priors for the residual density based on probit stick-breaking (PSB) scale mixtures and symmetrized PSB (sPSB) location-scale mixtures. Both priors restrict the residual density to be symmetric about zero, with the sPSB prior more flexible in allowing multimodal densities. We provide sufficient conditions to ensure strong posterior consistency in estimating the regression function under the sPSB prior, generalizing existing theory focused on parametric residual distributions. The PSB and sPSB priors are generalized to allow residual densities to change nonparametrically with predictors through incorporating Gaussian processes in the stick-breaking components. This leads to a robust Bayesian regression procedure that automatically down-weights outliers and influential observations in a locally-adaptive manner. Posterior computation relies on an efficient data augmentation exact block Gibbs sampler. The methods are illustrated using simulated and real data applications. PMID:24465053
The M Word: Multicollinearity in Multiple Regression.
Morrow-Howell, Nancy
1994-01-01
Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…
Genetic Programming Transforms in Linear Regression Situations
Castillo, Flor; Kordon, Arthur; Villa, Carlos
The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.
Model Selection in Kernel Ridge Regression
DEFF Research Database (Denmark)
Exterkate, Peter
Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels...
Nonparametric regression with martingale increment errors
Delattre, Sylvain
2010-01-01
We consider the problem of adaptive estimation of the regression function in a framework where we replace ergodicity assumptions (such as independence or mixing) by another structural assumption on the model. Namely, we propose adaptive upper bounds for kernel estimators with data-driven bandwidth (Lepski's selection rule) in a regression model where the noise is an increment of martingale. It includes, as very particular cases, the usual i.i.d. regression and auto-regressive models. The cornerstone tool for this study is a new result for self-normalized martingales, called ``stability'', which is of independent interest. In a first part, we only use the martingale increment structure of the noise. We give an adaptive upper bound using a random rate, that involves the occupation time near the estimation point. Thanks to this approach, the theoretical study of the statistical procedure is disconnected from usual ergodicity properties like mixing. Then, in a second part, we make a link with the usual minimax th...
Targeting: Logistic Regression, Special Cases and Extensions
Directory of Open Access Journals (Sweden)
Helmut Schaeben
2014-12-01
Full Text Available Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form. Weights-of-evidence is an ordinary logistic regression with parameters equal to the differences of the weights of evidence if all predictor variables are discrete and conditionally independent given the target variable. The hypothesis of conditional independence can be tested in terms of log-linear models. If the assumption of conditional independence is violated, the application of weights-of-evidence does not only corrupt the predicted conditional probabilities, but also their rank transform. Logistic regression models, including the interaction terms, can account for the lack of conditional independence, appropriate interaction terms compensate exactly for violations of conditional independence. Multilayer artificial neural nets may be seen as nested regression-like models, with some sigmoidal activation function. Most often, the logistic function is used as the activation function. If the net topology, i.e., its control, is sufficiently versatile to mimic interaction terms, artificial neural nets are able to account for violations of conditional independence and yield very similar results. Weights-of-evidence cannot reasonably include interaction terms; subsequent modifications of the weights, as often suggested, cannot emulate the effect of interaction terms.
Selecting a Regression Saturated by Indicators
DEFF Research Database (Denmark)
Hendry, David F.; Johansen, Søren; Santos, Carlos
We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain...
Measurement error in education and growth regressions
Portela, Miguel; Teulings, Coen; Alessie, R.
2004-01-01
The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations cons
Measurement Error in Education and Growth Regressions
Portela, M.; Teulings, C.N.; Alessie, R.
2004-01-01
The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations cons
Finite Algorithms for Robust Linear Regression
DEFF Research Database (Denmark)
Madsen, Kaj; Nielsen, Hans Bruun
1990-01-01
The Huber M-estimator for robust linear regression is analyzed. Newton type methods for solution of the problem are defined and analyzed, and finite convergence is proved. Numerical experiments with a large number of test problems demonstrate efficiency and indicate that this kind of approach may...
Hybrid Particle Swarm Optimization for Regression Testing
Directory of Open Access Journals (Sweden)
Dr. Arvinder Kaur
2011-05-01
Full Text Available Regression Testing ensures that any enhancement made to software will not affect specified functionality of software. The execution of all test cases can be long and complex to run; this makes it a costlier process. The prioritization of test cases can help in reduction in cost of regression testing, as it is inefficient to re- run each and every test case. In this research paper, the criterion considered is of maximum fault coverage in minimum execution time. In this research paper, the Hybrid Particle Swarm Optimization (HPSO algorithm has been used, to make regression testing efficient. The HPSO is acombination of Particle Swarm Optimization (PSO technique and Genetic Algorithms (GA, to widen the search space for the solution. The Genetic Algorithm (GA operators provides optimized way to performprioritization in regression testing and on blending it with Particle Swarm Optimization (PSO technique makes it effective and provides fast solution. The Genetic Algorithm (GA operator that has been used is Mutation operator which allows the search engine to evaluate all aspects of the search space. Here, AVERAGE PERCENTAGE OF FAULTS DETECTED (APFD metric has been used to represent the solution derived from HPSO for better transparency in proposed algorithm.
Spontaneous regression of an intraspinal disc cyst
Energy Technology Data Exchange (ETDEWEB)
Demaerel, P.; Eerens, I.; Wilms, G. [University Hospital, Leuven (Belgium). Dept. of Radiology; Goffin, J. [Dept. of Neurosurgery, University Hospitals, Leuven (Belgium)
2001-11-01
We present a patient with a so-called disc cyst. Its location in the ventrolateral epidural space and its communication with the herniated disc are clearly shown. The disc cyst developed rapidly and regressed spontaneously. This observation, which has not been reported until now, appears to support focal degeneration with cyst formation as the pathogenesis. (orig.)
Prediction of dynamical systems by symbolic regression
Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.
2016-07-01
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.
Regression Discontinuity Designs Based on Population Thresholds
DEFF Research Database (Denmark)
Eggers, Andrew C.; Freier, Ronny; Grembi, Veronica;
In many countries, important features of municipal government (such as the electoral system, mayors' salaries, and the number of councillors) depend on whether the municipality is above or below arbitrary population thresholds. Several papers have used a regression discontinuity design (RDD) to...
Modeling confounding by half-sibling regression
DEFF Research Database (Denmark)
Schölkopf, Bernhard; Hogg, David W; Wang, Dun;
2016-01-01
We describe a method for removing the effect of confounders to reconstruct a latent quantity of interest. The method, referred to as "half-sibling regression," is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification, discussing both indep...
Nonparametric and semiparametric dynamic additive regression models
DEFF Research Database (Denmark)
Scheike, Thomas Harder; Martinussen, Torben
Dynamic additive regression models provide a flexible class of models for analysis of longitudinal data. The approach suggested in this work is suited for measurements obtained at random time points and aims at estimating time-varying effects. Both fully nonparametric and semiparametric models can...
Commonality Analysis for the Regression Case.
Murthy, Kavita
Commonality analysis is a procedure for decomposing the coefficient of determination (R superscript 2) in multiple regression analyses into the percent of variance in the dependent variable associated with each independent variable uniquely, and the proportion of explained variance associated with the common effects of predictors in various…
Piecewise linear regression splines with hyperbolic covariates
International Nuclear Information System (INIS)
Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)
Regression testing Ajax applications: coping with dynamism
Roest, D.; Mesbah, A.; Van Deursen, A.
2009-01-01
Note: This paper is a pre-print of: Danny Roest, Ali Mesbah and Arie van Deursen. Regression Testing AJAX Applications: Coping with Dynamism. In Proceedings of the 3rd International Conference on Software Testing, Verification and Validation (ICST’10), Paris, France. IEEE Computer Society, 2010. Th
Functional data analysis of generalized regression quantiles
Guo, Mengmeng
2013-11-05
Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.
Prediction of dynamical systems by symbolic regression.
Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K; Noack, Bernd R
2016-07-01
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast. PMID:27575130
Empirical Bayes Estimation in Regression Model
Institute of Scientific and Technical Information of China (English)
Li-chun Wang
2005-01-01
This paper considers the empirical Bayes (EB) estimation problem for the parameterβ of the linear regression model y = Xβ + ε with ε～ N(0, σ2I) givenβ. Based on Pitman closeness (PC) criterion and mean square error matrix (MSEM) criterion, we prove the superiority of the EB estimator over the ordinary least square estimator (OLSE).
Bootstrap inference longitudinal semiparametric regression model
Pane, Rahmawati; Otok, Bambang Widjanarko; Zain, Ismaini; Budiantara, I. Nyoman
2016-02-01
Semiparametric regression contains two components, i.e. parametric and nonparametric component. Semiparametric regression model is represented by yt i=μ (x˜'ti,zt i)+εt i where μ (x˜'ti,zt i)=x˜'tiβ ˜+g (zt i) and yti is response variable. It is assumed to have a linear relationship with the predictor variables x˜'ti=(x1 i 1,x2 i 2,…,xT i r) . Random error εti, i = 1, …, n, t = 1, …, T is normally distributed with zero mean and variance σ2 and g(zti) is a nonparametric component. The results of this study showed that the PLS approach on longitudinal semiparametric regression models obtain estimators β˜^t=[X'H(λ)X]-1X'H(λ )y ˜ and g˜^λ(z )=M (λ )y ˜ . The result also show that bootstrap was valid on longitudinal semiparametric regression model with g^λ(b )(z ) as nonparametric component estimator.
Combes, Alain
2013-05-01
Myocarditis is defined as inflammation of the myocardium accompanied by myocellular necrosis. Acute myocarditis must be considered in patients who present with recent onset of cardiac failure or arrhythmia. Fulminant myocarditis is a distinct entity characterized by sudden onset of severe congestive heart failure or cardiogenic shock, usually following a flu-like illness, parvovirus B19, human herpesvirus 6, coxsackievirus and adenovirus being the most frequently viruses responsible for the disease. Treatment of myocarditis remains largely supportive, since immunosuppression has not been proven to be beneficial for acute lymphocytic myocarditis. Trials of antiviral therapies, or immunostimulants such as interferons, suggest a potential therapeutic role but require further investigation. Lastly, early recognition of patients rapidly progressing to refractory cardiac failure and their immediate transfer to a medical-surgical center experienced in mechanical circulatory support is warranted. In this setting, ECMO should be the first-line mechanical assistance. For highly unstable patients, a Mobile Cardiac Assistance Unit, that rapidly travels to primary care hospitals with a portable ECMO system and hooks it up before refractory multiorgan failure takes hold, is the preferred option. PMID:23789482
Directory of Open Access Journals (Sweden)
Iman Zarei
2013-02-01
Full Text Available Background: The development of toxicity tests regarding toxic responses of different fish species could be more effectively used in predictive toxicology and risk assessment. In this study lethal concentrations (LC50-96 h values of copper sulphate; an important toxic industrial pollutant, on Capoeta fusca were determined. Behavioral changes at different concentrations of CuSO4 were determined for the C.fusca. Methods: The sample fishes were collected from Qanat in Birjand and were transported to the laboratory in polythene bags. The exposure time of fish to CuSO4 was 96 hours. Mortalities were recorded at 24, 48, 72, and 96 hours of exposure, and the dead fish were removed regularly from the test aquariums. Physicochemical parameters, such as dissolved oxygen, pH and Total hardness of aquaria were monitored daily. Results: The LC50 values for CuSO4 at 24, 48, 72, and 96 h of exposure, were 43.62, 12.6, 7.66, and 6.85 mg/L, respectively. The median LC50 value of CuSO4 for C.fusca was found to be 6.928 mg/L by EPA method and estimated to be 6.787 mg/L with SPSS statistical software. Conclusion: The mortality decreased with time, and most of the deaths occurred during the first 24 h. In addition, behavioural changes increased with increased concentration. This metal is an important constituent in industrial effluents discharged into freshwaters. The results obtained in this study clearly revealed the fact that it is necessary to control the use of a heavy metal such as copper.
RECURRENT SEASONAL ACUTE PSYCHOSIS
Agarwal, Vivek
1999-01-01
Acute psychoses have been reported to occur more frequently in summer. This is a report of seasonal recurrence of acute psychosis in a patient. This case report emphasizes towards the biological etiology of acute psychoses.
Kidney failure; Renal failure; Renal failure - acute; ARF; Kidney injury - acute ... To prevent acute kidney failure: Health problems such as high blood pressure or diabetes should be well controlled. Avoid drugs and medicines that can cause kidney injury.
Cerebellar ataxia; Ataxia - acute cerebellar; Cerebellitis; Post-varicella acute cerebellar ataxia; PVACA ... Acute cerebellar ataxia in children, especially younger than age 3, may occur several weeks after an illness caused by a virus. ...
Progression and regression of the atherosclerotic plaque.
de Feyter, P J; Vos, J; Deckers, J W
1995-08-01
In animals in which atherosclerosis was induced experimentally (by a high cholesterol diet) regression of the atherosclerotic lesion was demonstrated after serum cholesterol was reduced by cholesterol- lowering drugs or a low-fat diet. Whether regression of advanced coronary arterly lesions also takes place in humans after a similar intervention remains conjectural. However, several randomized studies, primarily employing lipid-lowering intervention or comprehensive changes in lifestyle, have demonstrated, using serial angiograms, that it is possible to achieve less progression, arrest or even (small) regression of atherosclerotic lesions. The lipid-lowering trials (NHBLI, CLAS, POSCH, FATS, SCOR and STARS) studied 1240 symptomatic patients, mostly men, with moderately elevated cholesterol levels and moderately severe angiographic-proven coronary artery disease. A variety of lipid-lowering drugs, in addition to a diet, were used over an intervention period ranging from 2 to 3 years. In all but one study (NHBLI), the progression of coronary atherosclerosis was less in the treated group, but regression was induced in only a few patients. The overall relative risk of progression of coronary atherosclerosis was 0 x 62 and 2 x 13, respectively. The induced angiographic differences were small and did not produce any significant haemodynamic benefit. The most important result was tht the disease process could be stabilized in the majority of patients. Three comprehensive lifestyle change trials (the Lifestyle Heart study, STARS and the Heidelberg Study) studied 183 patients, who were subjected to stress management, and/or intensive exercise, in addition to a low fat diet, over a period ranging from 1 to 3 years. All three trials demonstrated less progression, and more regression with overall relative risks of 0 x 40 and 2 x 35 respectively, in the intervention groups. Angiographic trials demonstrated that retardation or arrest of coronary atherosclerosis was possible
Prevention and Regression of Atherosclerosis: Emerging Treatments
Directory of Open Access Journals (Sweden)
Aliosvi Rodríguez Rodríguez
2014-06-01
Full Text Available Occlusive vascular diseases such as acute coronary syndrome, cerebral stroke, and peripheral arterial disease, represent a serious health problem worldwide. In recent decades, there has been significant progress in the diagnosis and treatment of atherosclerosis. Intravascular ultrasound imaging provides detailed information on the anatomy of the plaque and it has been used in several studies to evaluate the results. Atherosclerosis destabilizes the normal protective mechanism provided by the endothelium and this mechanism has been involved in the pathophysiology of acute coronary disease and brain stroke. Main efforts focus on prevention, especially at early ages. This paper is a review of 68 updated bibliographic citations in order to show the current options available for the prevention and reversal of the atherosclerotic process.
Polat, Esra; Gunay, Suleyman
2013-10-01
One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.
Interpreting parameters in the logistic regression model with random effects
DEFF Research Database (Denmark)
Larsen, Klaus; Petersen, Jørgen Holm; Budtz-Jørgensen, Esben;
2000-01-01
interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects......interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects...
Acute Myopericarditis Mimicking Acute Myocardial Infarction
Seval İzdeş; Neriman Defne Altıntaş; Gülin Karaaslan; Recep Uygun; Abdulkadir But
2011-01-01
Acute coronary syndromes among young adults are relatively low when compared with older population in the intensive care unit. Electrocardiographic abnormalities mimicking acute coronary syndromes may be caused by non-coronary syndromes and the differential diagnosis requires a detailed evaluation. We are reporting a case of myopericarditis presenting with acute ST elevation and elevated cardiac enzymes simulating acute coronary syndrome. In this case report, the literature is reviewed to dis...
Wavelet Scattering Regression of Quantum Chemical Energies
Hirn, Matthew; Poilvert, Nicolas
2016-01-01
We introduce multiscale invariant dictionaries to estimate quantum chemical energies of organic molecules, from training databases. Molecular energies are invariant to isometric atomic displacements, and are Lipschitz continuous to molecular deformations. Similarly to density functional theory (DFT), the molecule is represented by an electronic density function. A multiscale invariant dictionary is calculated with wavelet scattering invariants. It cascades a first wavelet transform which separates scales, with a second wavelet transform which computes interactions across scales. Sparse scattering regressions give state of the art results over two databases of organic planar molecules. On these databases, the regression error is of the order of the error produced by DFT codes, but at a fraction of the computational cost.
A Gibbs Sampler for Multivariate Linear Regression
Mantz, Adam B
2015-01-01
Kelly (2007, hereafter K07) described an efficient algorithm, using Gibbs sampling, for performing linear regression in the fairly general case where non-zero measurement errors exist for both the covariates and response variables, where these measurements may be correlated (for the same data point), where the response variable is affected by intrinsic scatter in addition to measurement error, and where the prior distribution of covariates is modeled by a flexible mixture of Gaussians rather than assumed to be uniform. Here I extend the K07 algorithm in two ways. First, the procedure is generalized to the case of multiple response variables. Second, I describe how to model the prior distribution of covariates using a Dirichlet process, which can be thought of as a Gaussian mixture where the number of mixture components is learned from the data. I present an example of multivariate regression using the extended algorithm, namely fitting scaling relations of the gas mass, temperature, and luminosity of dynamica...
Constrained regression models for optimization and forecasting
Directory of Open Access Journals (Sweden)
P.J.S. Bruwer
2003-12-01
Full Text Available Linear regression models and the interpretation of such models are investigated. In practice problems often arise with the interpretation and use of a given regression model in spite of the fact that researchers may be quite "satisfied" with the model. In this article methods are proposed which overcome these problems. This is achieved by constructing a model where the "area of experience" of the researcher is taken into account. This area of experience is represented as a convex hull of available data points. With the aid of a linear programming model it is shown how conclusions can be formed in a practical way regarding aspects such as optimal levels of decision variables and forecasting.
Controlling attribute effect in linear regression
Calders, Toon
2013-12-01
In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.
Online support vector regression for reinforcement learning
Institute of Scientific and Technical Information of China (English)
Yu Zhenhua; Cai Yuanli
2007-01-01
The goal in reinforcement learning is to learn the value of state-action pair in order to maximize the total reward. For continuous states and actions in the real world, the representation of value functions is critical. Furthermore, the samples in value functions are sequentially obtained. Therefore, an online support vector regression (OSVR) is set up, which is a function approximator to estimate value functions in reinforcement learning. OSVR updates the regression function by analyzing the possible variation of support vector sets after new samples are inserted to the training set. To evaluate the OSVR learning ability, it is applied to the mountain-car task. The simulation results indicate that the OSVR has a preferable convergence speed and can solve continuous problems that are infeasible using lookup table.
Are increases in cigarette taxation regressive?
Borren, P; Sutton, M
1992-12-01
Using the latest published data from Tobacco Advisory Council surveys, this paper re-evaluates the question of whether or not increases in cigarette taxation are regressive in the United Kingdom. The extended data set shows no evidence of increasing price-elasticity by social class as found in a major previous study. To the contrary, there appears to be no clear pattern in the price responsiveness of smoking behaviour across different social classes. Increases in cigarette taxation, while reducing smoking levels in all groups, fall most heavily on men and women in the lowest social class. Men and women in social class five can expect to pay eight and eleven times more of a tax increase respectively, than their social class one counterparts. Taken as a proportion of relative incomes, the regressive nature of increases in cigarette taxation is even more pronounced.
Realization of Ridge Regression in MATLAB
Dimitrov, S.; Kovacheva, S.; Prodanova, K.
2008-10-01
The least square estimator (LSE) of the coefficients in the classical linear regression models is unbiased. In the case of multicollinearity of the vectors of design matrix, LSE has very big variance, i.e., the estimator is unstable. A more stable estimator (but biased) can be constructed using ridge-estimator (RE). In this paper the basic methods of obtaining of Ridge-estimators and numerical procedures of its realization in MATLAB are considered. An application to Pharmacokinetics problem is considered.
Average Regression-Adjusted Controlled Regenerative Estimates
Lewis, Peter A.W.; Ressler, Richard
1991-01-01
Proceedings of the 1991 Winter Simulation Conference Barry L. Nelson, W. David Kelton, Gordon M. Clark (eds.) One often uses computer simulations of queueing systems to generate estimates of system characteristics along with estimates of their precision. Obtaining precise estimates, espescially for high traffic intensities, can require large amounts of computer time. Average regression-adjusted controlled regenerative estimates result from combining the two techniques ...
When Redistribution Leads to Regressive Taxation
Cyril Hariton; Gwen�el Piaser; Gwena�l Piaser
2006-01-01
We introduce labor contracts, in a framework of optimal redistribution: firms have some local market power and try to discriminate among heterogeneous workers. In this setting we show that if the firms have perfect information, i.e, they perfectly discriminate against workers and take all the surplus, the best tax function is flat. If the firms have imperfect information, i.e, if they offert incentive contracts, then (under some assumptions) the best redistributive taxation is regressive.
When redistribution leads to regressive taxation
HARITON, Cyril; PIASER, Gwenaël
2004-01-01
We introduce labor contracts, in a framework of optimal redistribution: firms have some local market power and try to discriminate among heterogeneous workers. In this setting we show that if the firms have perfect information, i.e, they perfectly discriminate against workers and take all the surplus, the best tax function is flat. If the firms have imperfect information, i.e, if they offert incentive contracts, then (under some assumptions) the best redistributive taxation is regressive.
Logistic regression a self-learning text
Kleinbaum, David G
1994-01-01
This textbook provides students and professionals in the health sciences with a presentation of the use of logistic regression in research. The text is self-contained, and designed to be used both in class or as a tool for self-study. It arises from the author's many years of experience teaching this material and the notes on which it is based have been extensively used throughout the world.
Specification Testing for Nonlinear Multivariate Cointegrating Regressions
Chaohua Dong; Jiti Gao; Dag Tjostheim; Jiying Yin
2014-01-01
This paper considers a general model specification test for nonlinear multivariate cointegrating regressions where the regressor consists of a univariate integrated time series and a vector of stationary time series. The regressors and the errors are generated from the same innovations, so that the model accommodates endogeniety. A new and simple test is proposed and the resulting asymptotic theory is established. The test statistic is constructed based on a natural distance function between ...
Pricing Single Malt Whisky : A Regression Analysis
Bjartmar Hylta, Sanna; Lundquist, Emma
2016-01-01
This thesis examines the factors that affect the price of whisky. Multiple regression analysis is used to model the relationship between the identified covariates that are believed to impact the price of whisky. The optimal marketing strategy for whisky producers in the regions Islay and Campbeltown are discussed. This analysis is based on the Marketing Mix. Furthermore, a Porter’s five forces analysis, focusing on the regions Campeltown and Islay, is examined. Finally the findings are summar...
Nonexistence in Reciprocal and Logarithmic Regression
Institute of Scientific and Technical Information of China (English)
Josef Bukac
2003-01-01
Fitting logarithmic b ln(clx), a+bln(c+x) or reciprocal b/(c+x), a+b/(c+x) regression models to data by the least squares method asks for the determination of the closure of the set of each type of these functions defined on a finite domain. It follows that a minimal solution may not exist. But it does exist when the closure is considered.
Spontaneous Partial Regression of Cerebral Arteriovenous Malformation
Choi, Jae Ho; Shin, Ji Hoon; Cho, Seong Shik; Choi, Deuk Lin; Byun, Bark Jang; Kim, Dong Won
2002-01-01
Arteriovenous malformation (AVM) of the brain is one of the important pathologic conditions which cause intracerebral or subarachnoid hemorrhage, epilepsy, or chronic cerebral ischemia. The spontaneous regression of cerebral AVM is reported to be very rare and more likely to occur when the AVM is small, is accompanied by hemorrhage, and has fewer arterial feeders. We report a case of right occipital AVM which at follow-up angiography performed four years later showed near-complete spontaneous...
General regression and representation model for classification.
Directory of Open Access Journals (Sweden)
Jianjun Qian
Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.
A Dirty Model for Multiple Sparse Regression
Jalali, Ali; Sanghavi, Sujay
2011-01-01
Sparse linear regression -- finding an unknown vector from linear measurements -- is now known to be possible with fewer samples than variables, via methods like the LASSO. We consider the multiple sparse linear regression problem, where several related vectors -- with partially shared support sets -- have to be recovered. A natural question in this setting is whether one can use the sharing to further decrease the overall number of samples required. A line of recent research has studied the use of \\ell_1/\\ell_q norm block-regularizations with q>1 for such problems; however these could actually perform worse in sample complexity -- vis a vis solving each problem separately ignoring sharing -- depending on the level of sharing. We present a new method for multiple sparse linear regression that can leverage support and parameter overlap when it exists, but not pay a penalty when it does not. A very simple idea: we decompose the parameters into two components and regularize these differently. We show both theore...
On spline approximation of sliced inverse regression
Institute of Scientific and Technical Information of China (English)
2007-01-01
The dimension reduction is helpful and often necessary in exploring the nonparametric regression structure.In this area,Sliced inverse regression (SIR) is a promising tool to estimate the central dimension reduction (CDR) space.To estimate the kernel matrix of the SIR,we herein suggest the spline approximation using the least squares regression.The heteroscedasticity can be incorporated well by introducing an appropriate weight function.The root-n asymptotic normality can be achieved for a wide range choice of knots.This is essentially analogous to the kernel estimation.Moreover, we also propose a modified Bayes information criterion (BIC) based on the eigenvalues of the SIR matrix.This modified BIC can be applied to any form of the SIR and other related methods.The methodology and some of the practical issues are illustrated through the horse mussel data.Empirical studies evidence the performance of our proposed spline approximation by comparison of the existing estimators.
Spontaneous Regression of a Cervical Disk Herniation
Directory of Open Access Journals (Sweden)
Emre Delen
2014-03-01
Full Text Available A 54 years old female patient was admitted to our outpatient clinic with a two months history of muscle spasms of her neck and pain radiating to the left upper extremity. Magnetic resonance imaging had shown a large left-sided paracentral disk herniation at the C6-C7 disk space (Figure 1. Neurological examination showed no obvious neurological deficit. She received conservative treatment including bed rest, rehabilitation, and analgesic drugs. After 13 months, requested by the patient, a second magnetic resonance imaging study showed resolution of the disc herniation.(Figure 2 Although the literature contains several reports about spontaneous regression of herniated lumbar disc without surgical intervention, that of phenomenon reported for herniated cervical level is rare, and such reports are few[1]. In conclusion, herniated intervertebral disc have the potential to spontaneously regress independently from the spine level. With further studies, determining the predictive signs for prognostic evaluation for spontaneous regression which would yield to conservative treatment would be beneficial.
Face Alignment via Regressing Local Binary Features.
Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian
2016-03-01
This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.
Modeling oil production based on symbolic regression
International Nuclear Information System (INIS)
Numerous models have been proposed to forecast the future trends of oil production and almost all of them are based on some predefined assumptions with various uncertainties. In this study, we propose a novel data-driven approach that uses symbolic regression to model oil production. We validate our approach on both synthetic and real data, and the results prove that symbolic regression could effectively identify the true models beneath the oil production data and also make reliable predictions. Symbolic regression indicates that world oil production will peak in 2021, which broadly agrees with other techniques used by researchers. Our results also show that the rate of decline after the peak is almost half the rate of increase before the peak, and it takes nearly 12 years to drop 4% from the peak. These predictions are more optimistic than those in several other reports, and the smoother decline will provide the world, especially the developing countries, with more time to orchestrate mitigation plans. -- Highlights: •A data-driven approach has been shown to be effective at modeling the oil production. •The Hubbert model could be discovered automatically from data. •The peak of world oil production is predicted to appear in 2021. •The decline rate after peak is half of the increase rate before peak. •Oil production projected to decline 4% post-peak
Bayesian Inference of a Multivariate Regression Model
Directory of Open Access Journals (Sweden)
Marick S. Sinay
2014-01-01
Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.
Institute of Scientific and Technical Information of China (English)
谢萍; 许勤; 陈娟
2015-01-01
目的：调查急性胰腺炎出院患者健康行为能力的现状,分析其影响因素。方法采用一般资料评估表、健康行为能力自评量表( SRAHP)、健康意识量表、抑郁自评量表( SDS)、社会支持评定量表( SSRS)对入住某三甲医院胆胰中心的193例首发急性胰腺炎出院患者进行调查。结果急性胰腺炎出院患者健康行为能力平均得分为(64.09±15.25)分。4个维度中,运动维度得分最高,其次是心理调适、营养和健康责任。70例(36.27%)患者健康行为能力处于良好水平,118例(61.14%)处于中等水平,5例(2.59%)处于较差水平。急性胰腺炎出院患者健康意识平均得分为(7.19±3.12)分,抑郁平均得分为(49.86±8.04)分。单因素分析显示,职业、文化程度、个人月收入、医疗费用承担情况、生活方式状况、社会支持、抑郁状况与健康意识是急性胰腺炎出院患者健康行为能力的影响因素(P<0.05)。多元逐步回归分析显示,患者的健康意识、生活方式状况、社会支持状况、医疗费用承担情况与健康行为能力呈正相关(β值分别为0.99,1.00,0.56,1.01；P<0.05)；抑郁状况与健康行为能力呈负相关(β=-0.68,P<0.05)。结论急性急性胰腺炎出院患者的健康行为能力亟待提高,护理人员在制定干预措施时,要注重帮助患者建立和强化健康意识,改变其不良生活方式,提高社会支持水平,保持良好情绪,以更好地提高其健康行为能力。%Objective To conduct the research on the health behavior ability of discharged acute pancreatitis ( AP) patients, and analyze the relevant influencing factors. Methods Totals of 193 first-episode discharged AP in a third-grade class-A hospital were investigated with the General Information Evaluation Scale, Self-rated Abilities for Health Practices Scale ( SRAHP) , Health Awareness Scale, Self-rating Depression Scale ( SDS) and Social Support Rate Scale ( SSRS) . Results Among
Quantile regression modeling for Malaysian automobile insurance premium data
Fuzi, Mohd Fadzli Mohd; Ismail, Noriszura; Jemain, Abd Aziz
2015-09-01
Quantile regression is a robust regression to outliers compared to mean regression models. Traditional mean regression models like Generalized Linear Model (GLM) are not able to capture the entire distribution of premium data. In this paper we demonstrate how a quantile regression approach can be used to model net premium data to study the effects of change in the estimates of regression parameters (rating classes) on the magnitude of response variable (pure premium). We then compare the results of quantile regression model with Gamma regression model. The results from quantile regression show that some rating classes increase as quantile increases and some decrease with decreasing quantile. Further, we found that the confidence interval of median regression (τ = O.5) is always smaller than Gamma regression in all risk factors.
TWO-STAGE QUANTILE REGRESSION WHEN THE FIRST STAGE IS BASED ON QUANTILE REGRESSION
Christophe Muller; Tae-Hwan Kim
2004-01-01
We present the asymptotic properties of double-stage quantile regression estimators with random regressors, where the first stage is based on quantile regressions with the same quantile as in the second stage, which ensures robustness of the estimation procedure. We derive invariance properties with respect to the reformulation of the dependent variable. We propose a consistent estimator of the variance-covariance matrix of the new estimator. Finally, we investigate finite sample properties o...
Acute pollution of recipients in urban areas
DEFF Research Database (Denmark)
Rauch, W.; Harremoës, P.
1997-01-01
Oxygen and ammonia concentration are key parameters of acute water pollution in urban rivers. These two abiotic parameters are statistically assessed for a historical rain series by means of a simplified deterministic model of the integrated drainage system. Continuous simulation of the system...... performance indicates that acute water pollution is caused by intermittent discharges from both sewer system and wastewater treatment plant. Neglecting one of them in the evaluation of the environmental impact gives a wrong impression of total system behavior. Detention basins and alternative operational...... modes in the treatment plant under wet weather loading have a limited positive effect for minimizing acute water pollution. (C) 1997 IAWQ. Published by Elsevier Science Ltd....
Computed tomography perfusion imaging denoising using Gaussian process regression
Zhu, Fan; Carpenter, Trevor; Rodriguez Gonzalez, David; Atkinson, Malcolm; Wardlaw, Joanna
2012-06-01
Brain perfusion weighted images acquired using dynamic contrast studies have an important clinical role in acute stroke diagnosis and treatment decisions. However, computed tomography (CT) images suffer from low contrast-to-noise ratios (CNR) as a consequence of the limitation of the exposure to radiation of the patient. As a consequence, the developments of methods for improving the CNR are valuable. The majority of existing approaches for denoising CT images are optimized for 3D (spatial) information, including spatial decimation (spatially weighted mean filters) and techniques based on wavelet and curvelet transforms. However, perfusion imaging data is 4D as it also contains temporal information. Our approach using Gaussian process regression (GPR), which takes advantage of the temporal information, to reduce the noise level. Over the entire image, GPR gains a 99% CNR improvement over the raw images and also improves the quality of haemodynamic maps allowing a better identification of edges and detailed information. At the level of individual voxel, GPR provides a stable baseline, helps us to identify key parameters from tissue time-concentration curves and reduces the oscillations in the curve. GPR is superior to the comparable techniques used in this study.
Dynamic Regression Intervention Modeling for the Malaysian Daily Load
Directory of Open Access Journals (Sweden)
Fadhilah Abdrazak
2014-05-01
Full Text Available Malaysia is a unique country due to having both fixed and moving holidays. These moving holidays may overlap with other fixed holidays and therefore, increase the complexity of the load forecasting activities. The errors due to holidays’ effects in the load forecasting are known to be higher than other factors. If these effects can be estimated and removed, the behavior of the series could be better viewed. Thus, the aim of this paper is to improve the forecasting errors by using a dynamic regression model with intervention analysis. Based on the linear transfer function method, a daily load model consists of either peak or average is developed. The developed model outperformed the seasonal ARIMA model in estimating the fixed and moving holidays’ effects and achieved a smaller Mean Absolute Percentage Error (MAPE in load forecast.
Buruck, Gabriele; Wendsche, Johannes; Melzer, Marlen; Strobel, Alexander; Dörfel, Denise
2014-01-01
Psychosocial stress affects resources for adequate coping with environmental demands. A crucial question in this context is the extent to which acute psychosocial stressors impact empathy and emotion regulation. In the present study, 120 participants were randomly assigned to a control group vs. a group confronted with the Trier Social Stress Test (TSST), an established paradigm for the induction of acute psychosocial stress. Empathy for pain as a specific subgroup of empathy was assessed via pain intensity ratings during a pain-picture task. Self-reported emotion regulation skills were measured as predictors using an established questionnaire. Stressed individuals scored significantly lower on the appraisal of pain pictures. A regression model was chosen to find variables that further predict the pain ratings. These findings implicate that acute psychosocial stress might impair empathic processes to observed pain in another person and the ability to accept one's emotion additionally predicts the empathic reaction. Furthermore, the ability to tolerate negative emotions modulated the relation between stress and pain judgments, and thus influenced core cognitive-affective functions relevant for coping with environmental challenges. In conclusion, our study emphasizes the necessity of reducing negative emotions in terms of empathic distress when confronted with pain of another person under psychosocial stress, in order to be able to retain pro-social behavior. PMID:24910626
Buruck, Gabriele; Wendsche, Johannes; Melzer, Marlen; Strobel, Alexander; Dörfel, Denise
2014-01-01
Psychosocial stress affects resources for adequate coping with environmental demands. A crucial question in this context is the extent to which acute psychosocial stressors impact empathy and emotion regulation. In the present study, 120 participants were randomly assigned to a control group vs. a group confronted with the Trier Social Stress Test (TSST), an established paradigm for the induction of acute psychosocial stress. Empathy for pain as a specific subgroup of empathy was assessed via pain intensity ratings during a pain-picture task. Self-reported emotion regulation skills were measured as predictors using an established questionnaire. Stressed individuals scored significantly lower on the appraisal of pain pictures. A regression model was chosen to find variables that further predict the pain ratings. These findings implicate that acute psychosocial stress might impair empathic processes to observed pain in another person and the ability to accept one's emotion additionally predicts the empathic reaction. Furthermore, the ability to tolerate negative emotions modulated the relation between stress and pain judgments, and thus influenced core cognitive-affective functions relevant for coping with environmental challenges. In conclusion, our study emphasizes the necessity of reducing negative emotions in terms of empathic distress when confronted with pain of another person under psychosocial stress, in order to be able to retain pro-social behavior.
Directory of Open Access Journals (Sweden)
Gabriele eBuruck
2014-05-01
Full Text Available Psychosocial stress affects resources for adequate coping with environmental demands. A crucial question in this context is the extent to which acute psychosocial stressors impact empathy and emotion regulation. In the present study, 120 participants were randomly assigned to a control group vs. a group confronted with the Trier Social Stress Test, an established paradigm for the induction of acute psychosocial stress. Empathy for pain as a specific subgroup of empathy was assessed via pain intensity ratings during a pain-picture task. Self-reported emotion regulation skills were measured as predictors using an established questionnaire. Stressed individuals scored significantly lower on the appraisal of pain pictures. A regression model was chosen to find variables that further predict the pain ratings. These findings implicate that acute psychosocial stress might impair empathic processes to observed pain in another person and the ability to accept one’s emotion additionally predicts the empathic reaction. Furthermore, the ability to tolerate negative emotions modulated the relation between stress and pain judgments, and thus influenced core cognitive-affective functions relevant for coping with environmental challenges. In conclusion, our study emphasizes the necessity of reducing negative emotions in terms of empathic distress when confronted with pain of another person under psychosocial stress, in order to be able to retain pro-social behavior.
Moretti, Paolo; Peters, Sarika U.; del Gaudio, Daniela; Sahoo, Trilochan; Hyland, Keith; Bottiglieri, Teodoro; Hopkin, Robert J.; Peach, Elizabeth; Min, Sang Hee; Goldman, David; Roa, Benjamin; Bacino, Carlos A.; Scaglia, Fernando
2008-01-01
We studied seven children with CNS folate deficiency (CFD). All cases exhibited psychomotor retardation, regression, cognitive delay, and dyskinesia; six had seizures; four demonstrated neurological abnormalities in the neonatal period. Two subjects had profound neurological abnormalities that precluded formal behavioral testing. Five subjects…
MPTP所致急性帕金森病小鼠焦虑行为的评价%Evaluation of the anxiety behavior in acute PD mice induced by MPTP
Institute of Scientific and Technical Information of China (English)
叶素贞; 张书平; 施剑; 梁艳; 黄汉津
2016-01-01
Objective To investigate the anxious behavior in acute parkinson's mice that were induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) injection.Methods Twenty mice were randomly divided into the control group (n =10) and model group(n =10);The model group was induced by injecting MPTP dosage,and the control group was induced by the same dose of saline.The anxious behaviors in mice were tested by the elevated plus-maze test and the light/dark box.Results The model group mice spent a longer time than the control group in the dark box (P ＜ 0.05).The open arm entry (OE),open arm time (OT) and OE％ of model group was significantly less than that in control group in the elevated plus-maze test (P ＜ 0.01),the OT％ was significantly less than control group (P ＜0.05).Conclusions Anxiety symptoms appeared in the model group of early parkinson disease (PD)mice.%目的 研究1-甲基-4-苯基-1,2,3,6-四氢吡啶(MPTP)所致急性帕金森病(PD)小鼠模型的焦虑行为.方法 选取20只C57BL/6J小鼠,随机分为对照组(n=10)和模型组(n=10);模型组用MPTP制作急性PD小鼠模型,对照组用等量生理盐水注射.用高架十字迷宫和明暗箱检测小鼠的焦虑症行为.结果 模型组小鼠在暗箱的停留时间明显高于对照组(P＜0.05);高架十字迷宫中模型组进入开放臂次数(OE)、开放臂停留时间(OT)及进入开放臂次数比例(OE％)与对照组比较差异有统计学意义(P＜0.01),开放臂停留时间比例(OT％)显著低于对照组(P＜0.05).结论 急性PD小鼠模型早期即会出现焦虑症状.
Regression models for expected length of stay.
Grand, Mia Klinten; Putter, Hein
2016-03-30
In multi-state models, the expected length of stay (ELOS) in a state is not a straightforward object to relate to covariates, and the traditional approach has instead been to construct regression models for the transition intensities and calculate ELOS from these. The disadvantage of this approach is that the effect of covariates on the intensities is not easily translated into the effect on ELOS, and it typically relies on the Markov assumption. We propose to use pseudo-observations to construct regression models for ELOS, thereby allowing a direct interpretation of covariate effects while at the same time avoiding the Markov assumption. For this approach, all we need is a non-parametric consistent estimator for ELOS. For every subject (and for every state of interest), a pseudo-observation is constructed, and they are then used as outcome variables in the regression model. We furthermore show how to construct longitudinal (pseudo-) data when combining the concept of pseudo-observations with landmarking. In doing so, covariates are allowed to be time-varying, and we can investigate potential time-varying effects of the covariates. The models can be fitted using generalized estimating equations, and dependence between observations on the same subject is handled by applying the sandwich estimator. The method is illustrated using data from the US Health and Retirement Study where the impact of socio-economic factors on ELOS in health and disability is explored. Finally, we investigate the performance of our approach under different degrees of left-truncation, non-Markovianity, and right-censoring by means of simulation. PMID:26497637
Multiple linear regression for isotopic measurements
Garcia Alonso, J. I.
2012-04-01
There are two typical applications of isotopic measurements: the detection of natural variations in isotopic systems and the detection man-made variations using enriched isotopes as indicators. For both type of measurements accurate and precise isotope ratio measurements are required. For the so-called non-traditional stable isotopes, multicollector ICP-MS instruments are usually applied. In many cases, chemical separation procedures are required before accurate isotope measurements can be performed. The off-line separation of Rb and Sr or Nd and Sm is the classical procedure employed to eliminate isobaric interferences before multicollector ICP-MS measurement of Sr and Nd isotope ratios. Also, this procedure allows matrix separation for precise and accurate Sr and Nd isotope ratios to be obtained. In our laboratory we have evaluated the separation of Rb-Sr and Nd-Sm isobars by liquid chromatography and on-line multicollector ICP-MS detection. The combination of this chromatographic procedure with multiple linear regression of the raw chromatographic data resulted in Sr and Nd isotope ratios with precisions and accuracies typical of off-line sample preparation procedures. On the other hand, methods for the labelling of individual organisms (such as a given plant, fish or animal) are required for population studies. We have developed a dual isotope labelling procedure which can be unique for a given individual, can be inherited in living organisms and it is stable. The detection of the isotopic signature is based also on multiple linear regression. The labelling of fish and its detection in otoliths by Laser Ablation ICP-MS will be discussed using trout and salmon as examples. As a conclusion, isotope measurement procedures based on multiple linear regression can be a viable alternative in multicollector ICP-MS measurements.
Hierarchical linear regression models for conditional quantiles
Institute of Scientific and Technical Information of China (English)
TIAN Maozai; CHEN Gemai
2006-01-01
The quantile regression has several useful features and therefore is gradually developing into a comprehensive approach to the statistical analysis of linear and nonlinear response models,but it cannot deal effectively with the data with a hierarchical structure.In practice,the existence of such data hierarchies is neither accidental nor ignorable,it is a common phenomenon.To ignore this hierarchical data structure risks overlooking the importance of group effects,and may also render many of the traditional statistical analysis techniques used for studying data relationships invalid.On the other hand,the hierarchical models take a hierarchical data structure into account and have also many applications in statistics,ranging from overdispersion to constructing min-max estimators.However,the hierarchical models are virtually the mean regression,therefore,they cannot be used to characterize the entire conditional distribution of a dependent variable given high-dimensional covariates.Furthermore,the estimated coefficient vector (marginal effects)is sensitive to an outlier observation on the dependent variable.In this article,a new approach,which is based on the Gauss-Seidel iteration and taking a full advantage of the quantile regression and hierarchical models,is developed.On the theoretical front,we also consider the asymptotic properties of the new method,obtaining the simple conditions for an n1/2-convergence and an asymptotic normality.We also illustrate the use of the technique with the real educational data which is hierarchical and how the results can be explained.
Mapping geogenic radon potential by regression kriging.
Pásztor, László; Szabó, Katalin Zsuzsanna; Szatmári, Gábor; Laborczi, Annamária; Horváth, Ákos
2016-02-15
Radon ((222)Rn) gas is produced in the radioactive decay chain of uranium ((238)U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly.
Bayesian model selection in Gaussian regression
Abramovich, Felix
2009-01-01
We consider a Bayesian approach to model selection in Gaussian linear regression, where the number of predictors might be much larger than the number of observations. From a frequentist view, the proposed procedure results in the penalized least squares estimation with a complexity penalty associated with a prior on the model size. We investigate the optimality properties of the resulting estimator. We establish the oracle inequality and specify conditions on the prior that imply its asymptotic minimaxity within a wide range of sparse and dense settings for "nearly-orthogonal" and "multicollinear" designs.
Spectral density regression for bivariate extremes
Castro Camilo, Daniela
2016-05-11
We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods. © 2016 Springer-Verlag Berlin Heidelberg
Neutrosophic Correlation and Simple Linear Regression
Directory of Open Access Journals (Sweden)
A. A. Salama
2014-09-01
Full Text Available Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache. Recently, Salama et al., introduced the concept of correlation coefficient of neutrosophic data. In this paper, we introduce and study the concepts of correlation and correlation coefficient of neutrosophic data in probability spaces and study some of their properties. Also, we introduce and study the neutrosophic simple linear regression model. Possible applications to data processing are touched upon.
Affine Projection Algorithm Using Regressive Estimated Error
Zhang, Shu; Zhi, Yongfeng
2011-01-01
An affine projection algorithm using regressive estimated error (APA-REE) is presented in this paper. By redefining the iterated error of the affine projection algorithm (APA), a new algorithm is obtained, and it improves the adaptive filtering convergence rate. We analyze the iterated error signal and the stability for the APA-REE algorithm. The steady-state weights of the APA-REE algorithm are proved to be unbiased and consist. The simulation results show that the proposed algorithm has a f...
Survival Analysis with Multivariate adaptive Regression Splines
Kriner, Monika
2007-01-01
Multivariate adaptive regression splines (MARS) are a useful tool to identify linear and nonlinear eﬀects and interactions between two covariates. In this dissertation a new proposal to model survival type data with MARS is introduced. Martingale and deviance residuals of a Cox PH model are used as response in a common MARS approach to model functional forms of covariate eﬀects as well as possible interactions in a data-driven way. Simulation studies prove that the new method yields a bett...
Bayesian regression of piecewise homogeneous Poisson processes
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Diego Sevilla
2015-12-01
Full Text Available In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is valuable for detecting breaking points in the count rate of time series for Poisson processes. Received: 2 November 2015, Accepted: 27 November 2015; Edited by: R. Dickman; Reviewed by: M. Hutter, Australian National University, Canberra, Australia.; DOI: http://dx.doi.org/10.4279/PIP.070018 Cite as: D J R Sevilla, Papers in Physics 7, 070018 (2015
Novel Time Aware Regression Testing Technique
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Harsh Bhasin
2013-05-01
Full Text Available Regression testing comes into play when changes are made in the software. It is not possible to re-run all the previous test cases therefore, a minimization technique is required in order to reduce thetest case suit. The present work proposes a time aware minimization technique to accomplish the task. The technique is verified by taking 3 KLOC professional management system developed by Sahib Soft. The proposed work takes into consideration the shortcomings in the existing techniques and presents a theoretically sound model to handle the anomalies of the existing techniques. The initial results obtained are encouraging.
Cyclodextrin promotes atherosclerosis regression via macrophage reprogramming
DEFF Research Database (Denmark)
Zimmer, Sebastian; Grebe, Alena; Bakke, Siril S;
2016-01-01
Atherosclerosis is an inflammatory disease linked to elevated blood cholesterol concentrations. Despite ongoing advances in the prevention and treatment of atherosclerosis, cardiovascular disease remains the leading cause of death worldwide. Continuous retention of apolipoprotein B...... that increases cholesterol solubility in preventing and reversing atherosclerosis. We showed that CD treatment of murine atherosclerosis reduced atherosclerotic plaque size and CC load and promoted plaque regression even with a continued cholesterol-rich diet. Mechanistically, CD increased oxysterol production...... of CD as well as for augmented reverse cholesterol transport. Because CD treatment in humans is safe and CD beneficially affects key mechanisms of atherogenesis, it may therefore be used clinically to prevent or treat human atherosclerosis....
Convex Regression with Interpretable Sharp Partitions
Petersen, Ashley; Simon, Noah; Witten, Daniela
2016-01-01
We consider the problem of predicting an outcome variable on the basis of a small number of covariates, using an interpretable yet non-additive model. We propose convex regression with interpretable sharp partitions (CRISP) for this task. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. We explore the properties of CRISP, and evaluate its performance in a simulation study and on a housing price data set.
Inferring gene regression networks with model trees
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Aguilar-Ruiz Jesus S
2010-10-01
Full Text Available Abstract Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear
Paraneoplastic pemphigus regression after thymoma resection
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Stergiou Eleni
2008-08-01
Full Text Available Abstract Background Among human neoplasms thymomas are associated with highest frequency with paraneoplastic autoimmune diseases. Case presentation A case of a 42-year-old woman with paraneoplastic pemphigus as the first manifestation of thymoma is reported. Transsternal complete thymoma resection achieved pemphigus regression. The clinical correlations between pemphigus and thymoma are presented. Conclusion Our case report provides further evidence for the important role of autoantibodies in the pathogenesis of paraneoplastic skin diseases in thymoma patients. It also documents the improvement of the associated pemphigus after radical treatment of the thymoma.
Giannotti, Flavia; Cortesi, Flavia; Cerquiglini, Antonella; Miraglia, Daniela; Vagnoni, Cristina; Sebastiani, Teresa; Bernabei, Paola
2008-01-01
This study investigated sleep of children with autism and developmental regression and the possible relationship with epilepsy and epileptiform abnormalities. Participants were 104 children with autism (70 non-regressed, 34 regressed) and 162 typically developing children (TD). Results suggested that the regressed group had higher incidence of…
Supporting Regularized Logistic Regression Privately and Efficiently.
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.
Regression Models for Count Data in R
Directory of Open Access Journals (Sweden)
Christian Kleiber
2008-06-01
Full Text Available The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inﬂated regression models in the functions hurdle( and zeroinfl( from the package pscl is introduced. It re-uses design and functionality of the basic R functions just as the underlying conceptual tools extend the classical models. Both hurdle and zero-inﬂated model, are able to incorporate over-dispersion and excess zeros-two problems that typically occur in count data sets in economics and the social sciences—better than their classical counterparts. Using cross-section data on the demand for medical care, it is illustrated how the classical as well as the zero-augmented models can be ﬁtted, inspected and tested in practice.
Jackknife bias reduction for polychotomous logistic regression.
Bull, S B; Greenwood, C M; Hauck, W W
1997-03-15
Despite theoretical and empirical evidence that the usual MLEs can be misleading in finite samples and some evidence that bias reduced estimates are less biased and more efficient, they have not seen a wide application in practice. One can obtain bias reduced estimates by jackknife methods, with or without full iteration, or by use of higher order terms in a Taylor series expansion of the log-likelihood to approximate asymptotic bias. We provide details of these methods for polychotomous logistic regression with a nominal categorical response. We conducted a Monte Carlo comparison of the jackknife and Taylor series estimates in moderate sample sizes in a general logistic regression setting, to investigate dichotomous and trichotomous responses and a mixture of correlated and uncorrelated binary and normal covariates. We found an approximate two-step jackknife and the Taylor series methods useful when the ratio of the number of observations to the number of parameters is greater than 15, but we cannot recommend the two-step and the fully iterated jackknife estimates when this ratio is less than 20, especially when there are large effects, binary covariates, or multicollinearity in the covariates.
Bayesian nonlinear regression for large small problems
Chakraborty, Sounak
2012-07-01
Statistical modeling and inference problems with sample sizes substantially smaller than the number of available covariates are challenging. This is known as large p small n problem. Furthermore, the problem is more complicated when we have multiple correlated responses. We develop multivariate nonlinear regression models in this setup for accurate prediction. In this paper, we introduce a full Bayesian support vector regression model with Vapnik\\'s ε-insensitive loss function, based on reproducing kernel Hilbert spaces (RKHS) under the multivariate correlated response setup. This provides a full probabilistic description of support vector machine (SVM) rather than an algorithm for fitting purposes. We have also introduced a multivariate version of the relevance vector machine (RVM). Instead of the original treatment of the RVM relying on the use of type II maximum likelihood estimates of the hyper-parameters, we put a prior on the hyper-parameters and use Markov chain Monte Carlo technique for computation. We have also proposed an empirical Bayes method for our RVM and SVM. Our methods are illustrated with a prediction problem in the near-infrared (NIR) spectroscopy. A simulation study is also undertaken to check the prediction accuracy of our models. © 2012 Elsevier Inc.
Variable Selection in Logistic Regression Mo del
Institute of Scientific and Technical Information of China (English)
ZHANG Shangli; ZHANG Lili; QIU Kuanmin; LU Ying; CAI Baigen
2015-01-01
Variable selection is one of the most impor-tant problems in pattern recognition. In linear regression model, there are many methods can solve this problem, such as Least absolute shrinkage and selection operator (LASSO) and many improved LASSO methods, but there are few variable selection methods in generalized linear models. We study the variable selection problem in logis-tic regression model. We propose a new variable selection method–the logistic elastic net, prove that it has grouping eff ect which means that the strongly correlated predictors tend to be in or out of the model together. The logistic elastic net is particularly useful when the number of pre-dictors (p) is much bigger than the number of observations (n). By contrast, the LASSO is not a very satisfactory vari-able selection method in the case when p is more larger than n. The advantage and eff ectiveness of this method are demonstrated by real leukemia data and a simulation study.
Regression Models For Saffron Yields in Iran
S. H, Sanaeinejad; S. N, Hosseini
Saffron is an important crop in social and economical aspects in Khorassan Province (Northeast of Iran). In this research wetried to evaluate trends of saffron yield in recent years and to study the relationship between saffron yield and the climate change. A regression analysis was used to predict saffron yield based on 20 years of yield data in Birjand, Ghaen and Ferdows cities.Climatologically data for the same periods was provided by database of Khorassan Climatology Center. Climatologically data includedtemperature, rainfall, relative humidity and sunshine hours for ModelI, and temperature and rainfall for Model II. The results showed the coefficients of determination for Birjand, Ferdows and Ghaen for Model I were 0.69, 0.50 and 0.81 respectively. Also coefficients of determination for the same cities for model II were 0.53, 0.50 and 0.72 respectively. Multiple regression analysisindicated that among weather variables, temperature was the key parameter for variation ofsaffron yield. It was concluded that increasing temperature at spring was the main cause of declined saffron yield during recent years across the province. Finally, yield trend was predicted for the last 5 years using time series analysis.
A Gibbs sampler for multivariate linear regression
Mantz, Adam B.
2016-04-01
Kelly described an efficient algorithm, using Gibbs sampling, for performing linear regression in the fairly general case where non-zero measurement errors exist for both the covariates and response variables, where these measurements may be correlated (for the same data point), where the response variable is affected by intrinsic scatter in addition to measurement error, and where the prior distribution of covariates is modelled by a flexible mixture of Gaussians rather than assumed to be uniform. Here, I extend the Kelly algorithm in two ways. First, the procedure is generalized to the case of multiple response variables. Secondly, I describe how to model the prior distribution of covariates using a Dirichlet process, which can be thought of as a Gaussian mixture where the number of mixture components is learned from the data. I present an example of multivariate regression using the extended algorithm, namely fitting scaling relations of the gas mass, temperature, and luminosity of dynamically relaxed galaxy clusters as a function of their mass and redshift. An implementation of the Gibbs sampler in the R language, called LRGS, is provided.
Optimization of DWDM Demultiplexer Using Regression Analysis
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Venkatachalam Rajarajan Balaji
2016-01-01
Full Text Available We propose a novel twelve-channel Dense Wavelength Division Multiplexing (DWDM demultiplexer, using the two-dimensional photonic crystal (2D PC with square resonant cavity (SRC of ITU-T G.694.1 standard. The DWDM demultiplexer consists of an input waveguide, SRC, and output waveguide. The SRC in the proposed demultiplexer consists of square resonator and microcavity. The microcavity center rod radius (Rm is proportional to refractive index. The refractive index property of the rods filters the wavelengths of odd and even channels. The proposed microcavity can filter twelve ITU-T G.694.1 standard wavelengths with 0.2 nm/25 GHz channel spacing between the wavelengths. From the simulation, we optimize the rod radius and wavelength with linear regression analysis. From the regression analysis, we can achieve 95% of accuracy with an average quality factor of 7890, the uniform spectral line-width of 0.2 nm, the transmission efficiency of 90%, crosstalk of −42 dB, and footprint of about 784 μm2.
Supporting Regularized Logistic Regression Privately and Efficiently.
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738
Shape regression for vertebra fracture quantification
Lund, Michael Tillge; de Bruijne, Marleen; Tanko, Laszlo B.; Nielsen, Mads
2005-04-01
Accurate and reliable identification and quantification of vertebral fractures constitute a challenge both in clinical trials and in diagnosis of osteoporosis. Various efforts have been made to develop reliable, objective, and reproducible methods for assessing vertebral fractures, but at present there is no consensus concerning a universally accepted diagnostic definition of vertebral fractures. In this project we want to investigate whether or not it is possible to accurately reconstruct the shape of a normal vertebra, using a neighbouring vertebra as prior information. The reconstructed shape can then be used to develop a novel vertebra fracture measure, by comparing the segmented vertebra shape with its reconstructed normal shape. The vertebrae in lateral x-rays of the lumbar spine were manually annotated by a medical expert. With this dataset we built a shape model, with equidistant point distribution between the four corner points. Based on the shape model, a multiple linear regression model of a normal vertebra shape was developed for each dataset using leave-one-out cross-validation. The reconstructed shape was calculated for each dataset using these regression models. The average prediction error for the annotated shape was on average 3%.
Multiple Linear Regression Models in Outlier Detection
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S.M.A.Khaleelur Rahman
2012-02-01
Full Text Available Identifying anomalous values in the real-world database is important both for improving the quality of original data and for reducing the impact of anomalous values in the process of knowledge discovery in databases. Such anomalous values give useful information to the data analyst in discovering useful patterns. Through isolation, these data may be separated and analyzed. The analysis of outliers and influential points is an important step of the regression diagnostics. In this paper, our aim is to detect the points which are very different from the others points. They do not seem to belong to a particular population and behave differently. If these influential points are to be removed it will lead to a different model. Distinction between these points is not always obvious and clear. Hence several indicators are used for identifying and analyzing outliers. Existing methods of outlier detection are based on manual inspection of graphically represented data. In this paper, we present a new approach in automating the process of detecting and isolating outliers. Impact of anomalous values on the dataset has been established by using two indicators DFFITS and Cook’sD. The process is based on modeling the human perception of exceptional values by using multiple linear regression analysis.
Supporting Regularized Logistic Regression Privately and Efficiently
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738
Revisit of Sheppard corrections in linear regression
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
Dempster and Rubin(D&R) in their JRSSB paper considered the statistical error caused by data rounding in a linear regression model and compared the Sheppard correction,BRB correction and the ordinary LSE by simulations.Some asymptotic results when the rounding scale tends to 0 were also presented.In a previous research,we found that the ordinary sample variance of rounded data from normal populations is always inconsistent while the sample mean of rounded data is consistent if and only if the true mean is a multiple of the half rounding scale.In the light of these results,in this paper we further investigate the rounding errors in linear regressions.We notice that these results form the basic reasons that the Sheppard corrections perform better than other methods in D&R examples and their conclusion in general cases is incorrect.Examples in which the Sheppard correction works worse than the BRB correction are also given.Furthermore,we propose a new approach to estimate the parameters,called "two-stage estimator",and establish the consistency and asymptotic normality of the new estimators.
Stochastic search, optimization and regression with energy applications
Hannah, Lauren A.
models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.
Wheeler, David; Tiefelsdorf, Michael
2005-06-01
Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.
Acute chylous peritonitis due to acute pancreatitis
2012-01-01
We report a case of acute chylous ascites formation presenting as peritonitis (acute chylous peritonitis) in a patient suffering from acute pancreatitis due to hypertriglyceridemia and alcohol abuse. The development of chylous ascites is usually a chronic process mostly involving malignancy, trauma or surgery, and symptoms arise as a result of progressive abdominal distention. However, when accumulation of “chyle” occurs rapidly, the patient may present with signs of peritonitis. Preoperative...
Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation
Directory of Open Access Journals (Sweden)
Sharad Damodar Gore
2009-10-01
Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.
Directory of Open Access Journals (Sweden)
Hong-Juan Li
2013-04-01
Full Text Available Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR, this paper presents a SVR model hybridized with the empirical mode decomposition (EMD method and auto regression (AR for electric load forecasting. The electric load data of the New South Wales (Australia market are employed for comparing the forecasting performances of different forecasting models. The results confirm the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.
Directory of Open Access Journals (Sweden)
David Darmon
2014-12-01
Full Text Available A popular approach in the investigation of the short-term behavior of a non-stationary time series is to assume that the time series decomposes additively into a long-term trend and short-term fluctuations. A first step towards investigating the short-term behavior requires estimation of the trend, typically via smoothing in the time domain. We propose a method for time-domain smoothing, called complexity-regularized regression (CRR. This method extends recent work, which infers a regression function that makes residuals from a model “look random”. Our approach operationalizes non-randomness in the residuals by applying ideas from computational mechanics, in particular the statistical complexity of the residual process. The method is compared to generalized cross-validation (GCV, a standard approach for inferring regression functions, and shown to outperform GCV when the error terms are serially correlated. Regression under serially-correlated residuals has applications to time series analysis, where the residuals may represent short timescale activity. We apply CRR to a time series drawn from the Dow Jones Industrial Average and examine how both the long-term and short-term behavior of the market have changed over time.
Xu, Qian; Chai, Shou-jie; Qian, Ying-Ying; Zhang, Min; Wang, Kai
2012-01-01
Aim: To determine the roles of breast regression protein-39 (BRP-39) in regulating dendritic cell maturation and in pathology of acute asthma. Methods: Mouse bone marrow-derived dendritic cells (BMDCs) were prepared, and infected with adenovirus over-expressing BRP-39. Ovalbumin (OVA)-induced murine model of acute asthma was made in female BALB/c mice by sensitizing and challenging with chicken OVA and Imject Alum. The transfected BMDCs were adoptively transferred into OVA-treated mice via in...
Remaining Phosphorus Estimate Through Multiple Regression Analysis
Institute of Scientific and Technical Information of China (English)
M. E. ALVES; A. LAVORENTI
2006-01-01
The remaining phosphorus (Prem), P concentration that remains in solution after shaking soil with 0.01 mol L-1 CaCl2 containing 60 μg mL-1 P, is a very useful index for studies related to the chemistry of variable charge soils. Although the Prem determination is a simple procedure, the possibility of estimating accurate values of this index from easily and/or routinely determined soil properties can be very useful for practical purposes. The present research evaluated the Premestimation through multiple regression analysis in which routinely determined soil chemical data, soil clay content and soil pH measured in 1 mol L-1 NaF (pHNaF) figured as Prem predictor variables. The Prem can be estimated with acceptable accuracy using the above-mentioned approach, and PHNaF not only substitutes for clay content as a predictor variable but also confers more accuracy to the Prem estimates.
Statistical learning from a regression perspective
Berk, Richard A
2016-01-01
This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response. As a first approximation, this can be seen as an extension of nonparametric regression. This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives from sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. A continued emphasis on the implications for practice runs through the text. Among the statistical learning procedures examined are bagging, random forests, boosting, support vector machines and neural networks. Response variables may be quantitative or categorical. As in the first edition, a unifying theme is supervised learning that can be trea...
BANK FAILURE PREDICTION WITH LOGISTIC REGRESSION
Directory of Open Access Journals (Sweden)
Taha Zaghdoudi
2013-04-01
Full Text Available In recent years the economic and financial world is shaken by a wave of financial crisis and resulted in violent bank fairly huge losses. Several authors have focused on the study of the crises in order to develop an early warning model. It is in the same path that our work takes its inspiration. Indeed, we have tried to develop a predictive model of Tunisian bank failures with the contribution of the binary logistic regression method. The specificity of our prediction model is that it takes into account microeconomic indicators of bank failures. The results obtained using our provisional model show that a bank's ability to repay its debt, the coefficient of banking operations, bank profitability per employee and leverage financial ratio has a negative impact on the probability of failure.
Nonparametric additive regression for repeatedly measured data
Carroll, R. J.
2009-05-20
We develop an easily computed smooth backfitting algorithm for additive model fitting in repeated measures problems. Our methodology easily copes with various settings, such as when some covariates are the same over repeated response measurements. We allow for a working covariance matrix for the regression errors, showing that our method is most efficient when the correct covariance matrix is used. The component functions achieve the known asymptotic variance lower bound for the scalar argument case. Smooth backfitting also leads directly to design-independent biases in the local linear case. Simulations show our estimator has smaller variance than the usual kernel estimator. This is also illustrated by an example from nutritional epidemiology. © 2009 Biometrika Trust.
Adaptive Rank Penalized Estimators in Multivariate Regression
Bunea, Florentina; Wegkamp, Marten
2010-01-01
We introduce a new criterion, the Rank Selection Criterion (RSC), for selecting the optimal reduced rank estimator of the coefficient matrix in multivariate response regression models. The corresponding RSC estimator minimizes the Frobenius norm of the fit plus a regularization term proportional to the number of parameters in the reduced rank model. The rank of the RSC estimator provides a consistent estimator of the rank of the coefficient matrix. The consistency results are valid not only in the classic asymptotic regime, when the number of responses $n$ and predictors $p$ stays bounded, and the number of observations $m$ grows, but also when either, or both, $n$ and $p$ grow, possibly much faster than $m$. Our finite sample prediction and estimation performance bounds show that the RSC estimator achieves the optimal balance between the approximation error and the penalty term. Furthermore, our procedure has very low computational complexity, linear in the number of candidate models, making it particularly ...
Logistic regression against a divergent Bayesian network
Directory of Open Access Journals (Sweden)
Noel Antonio Sánchez Trujillo
2015-01-01
Full Text Available This article is a discussion about two statistical tools used for prediction and causality assessment: logistic regression and Bayesian networks. Using data of a simulated example from a study assessing factors that might predict pulmonary emphysema (where fingertip pigmentation and smoking are considered; we posed the following questions. Is pigmentation a confounding, causal or predictive factor? Is there perhaps another factor, like smoking, that confounds? Is there a synergy between pigmentation and smoking? The results, in terms of prediction, are similar with the two techniques; regarding causation, differences arise. We conclude that, in decision-making, the sum of both: a statistical tool, used with common sense, and previous evidence, taking years or even centuries to develop; is better than the automatic and exclusive use of statistical resources.
Adaptive regression for modeling nonlinear relationships
Knafl, George J
2016-01-01
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the s...
Estimates on compressed neural networks regression.
Zhang, Yongquan; Li, Youmei; Sun, Jianyong; Ji, Jiabing
2015-03-01
When the neural element number n of neural networks is larger than the sample size m, the overfitting problem arises since there are more parameters than actual data (more variable than constraints). In order to overcome the overfitting problem, we propose to reduce the number of neural elements by using compressed projection A which does not need to satisfy the condition of Restricted Isometric Property (RIP). By applying probability inequalities and approximation properties of the feedforward neural networks (FNNs), we prove that solving the FNNs regression learning algorithm in the compressed domain instead of the original domain reduces the sample error at the price of an increased (but controlled) approximation error, where the covering number theory is used to estimate the excess error, and an upper bound of the excess error is given.
Collaborative regression-based anatomical landmark detection
Gao, Yaozong; Shen, Dinggang
2015-12-01
Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods.
Logistic Regression Applied to Seismic Discrimination
Energy Technology Data Exchange (ETDEWEB)
BG Amindan; DN Hagedorn
1998-10-08
The usefulness of logistic discrimination was examined in an effort to learn how it performs in a regional seismic setting. Logistic discrimination provides an easily understood method, works with user-defined models and few assumptions about the population distributions, and handles both continuous and discrete data. Seismic event measurements from a data set compiled by Los Alamos National Laboratory (LANL) of Chinese events recorded at station WMQ were used in this demonstration study. PNNL applied logistic regression techniques to the data. All possible combinations of the Lg and Pg measurements were tried, and a best-fit logistic model was created. The best combination of Lg and Pg frequencies for predicting the source of a seismic event (earthquake or explosion) used Lg{sub 3.0-6.0} and Pg{sub 3.0-6.0} as the predictor variables. A cross-validation test was run, which showed that this model was able to correctly predict 99.7% earthquakes and 98.0% explosions for this given data set. Two other models were identified that used Pg and Lg measurements from the 1.5 to 3.0 Hz frequency range. Although these other models did a good job of correctly predicting the earthquakes, they were not as effective at predicting the explosions. Two possible biases were discovered which affect the predicted probabilities for each outcome. The first bias was due to this being a case-controlled study. The sampling fractions caused a bias in the probabilities that were calculated using the models. The second bias is caused by a change in the proportions for each event. If at a later date the proportions (a priori probabilities) of explosions versus earthquakes change, this would cause a bias in the predicted probability for an event. When using logistic regression, the user needs to be aware of the possible biases and what affect they will have on the predicted probabilities.
Pentoxifylline Treatment in Acute Pancreatitis (AP)
2016-09-14
Acute Pancreatitis (AP); Gallstone Pancreatitis; Alcoholic Pancreatitis; Post-ERCP/Post-procedural Pancreatitis; Trauma Acute Pancreatitis; Hypertriglyceridemia Acute Pancreatitis; Idiopathic (Unknown) Acute Pancreatitis; Medication Induced Acute Pancreatitis; Cancer Acute Pancreatitis; Miscellaneous (i.e. Acute on Chronic Pancreatitis)
Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR for Load Forecasting
Directory of Open Access Journals (Sweden)
Cheng-Wen Lee
2016-10-01
Full Text Available Hybridizing chaotic evolutionary algorithms with support vector regression (SVR to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives.
Directory of Open Access Journals (Sweden)
Makoto Suzuki
Full Text Available Cognitive disorders in the acute stage of stroke are common and are important independent predictors of adverse outcome in the long term. Despite the impact of cognitive disorders on both patients and their families, it is still difficult to predict the extent or duration of cognitive impairments. The objective of the present study was, therefore, to provide data on predicting the recovery of cognitive function soon after stroke by differential modeling with logarithmic and linear regression. This study included two rounds of data collection comprising 57 stroke patients enrolled in the first round for the purpose of identifying the time course of cognitive recovery in the early-phase group data, and 43 stroke patients in the second round for the purpose of ensuring that the correlation of the early-phase group data applied to the prediction of each individual's degree of cognitive recovery. In the first round, Mini-Mental State Examination (MMSE scores were assessed 3 times during hospitalization, and the scores were regressed on the logarithm and linear of time. In the second round, calculations of MMSE scores were made for the first two scoring times after admission to tailor the structures of logarithmic and linear regression formulae to fit an individual's degree of functional recovery. The time course of early-phase recovery for cognitive functions resembled both logarithmic and linear functions. However, MMSE scores sampled at two baseline points based on logarithmic regression modeling could estimate prediction of cognitive recovery more accurately than could linear regression modeling (logarithmic modeling, R(2 = 0.676, P<0.0001; linear regression modeling, R(2 = 0.598, P<0.0001. Logarithmic modeling based on MMSE scores could accurately predict the recovery of cognitive function soon after the occurrence of stroke. This logarithmic modeling with mathematical procedures is simple enough to be adopted in daily clinical practice.
Dyslipidemia and Outcome in Patients with Acute Ischemic Stroke
Institute of Scientific and Technical Information of China (English)
XU Tian; ZHANG Jin Tao; YANG Mei; ZHANG Huan; LIU Wen Qing; KONG Yan; XU Tan; ZHANG Yong Hong
2014-01-01
ObjectiveTo study the relationship between dyslipidemia and outcome in patients with acute ischemic stroke. MethodsData about 1 568 patients with acute ischemic stroke werecollected from 4 hospitals in Shandong Province from January 2006 to December 2008. National Institute of Health Stroke Scale (NIHSS) >10 at discharge or death was defined as the outcome. Effect of dyslipidemia on outcome in patients with acute ischemic stroke was analyzed by multivariate logistic regression analysis and propensity score-adjusted analysis, respectively. ResultsThe serum levels of TC, LDL-C, and HDL-C were significantly associated with the outcome in patients with acute ischemic stroke. Multivariate logistic regression analysis and propensity score-adjusted analysis showed that the ORs and 95% CIs were 3.013 (1.259, 7.214)/2.655 (1.298, 5.43), 3.157(1.306, 7.631)/3.405(1.621, 7.154), and 0.482 (0.245, 0.946)/0.51 (0.282, 0.921), respectively, for patients with acute ischemic stroke. Hosmer-Lemeshow goodness-of-fit test showed no significant difference in observed and predicted risk in patients with acute ischemic stroke (chi-square=8.235, P=0.411). ConclusionSerum levels of TC, LDL-C, and HDL-C are positively related with the outcome in patients with acute ischemic stroke.
Vargas, M.; Crossa, J.; Eeuwijk, van F.A.; Ramirez, M.E.; Sayre, K.
1999-01-01
Partial least squares (PLS) and factorial regression (FR) are statistical models that incorporate external environmental and/or cultivar variables for studying and interpreting genotype × environment interaction (GEl). The Additive Main effect and Multiplicative Interaction (AMMI) model uses only th
Directory of Open Access Journals (Sweden)
Qiutong Jin
2016-06-01
Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.
An Additive-Multiplicative Cox-Aalen Regression Model
DEFF Research Database (Denmark)
Scheike, Thomas H.; Zhang, Mei-Jie
2002-01-01
Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects...
Security Regression Testing Framework For Web Application Development
Waheed, Usman
2014-01-01
A framework and process that explains how to perform security regression testing for web applications. This paper discusses and proposes a framework based on open source tools that can be used to perform automated security regression testing of web applications.
Acute Pancreatitis in Children
... a feeding tube or an IV to prevent malnutrition and improve healing. Does my child have to ... intestines. Can my child die from acute pancreatitis? Death from acute pancreatitis is quite rare in children– ...
Spatial vulnerability assessments by regression kriging
Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor
2016-04-01
information representing IEW or GRP forming environmental factors were taken into account to support the spatial inference of the locally experienced IEW frequency and measured GRP values respectively. An efficient spatial prediction methodology was applied to construct reliable maps, namely regression kriging (RK) using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Application of RK also provides the possibility of inherent accuracy assessment. The resulting maps are characterized by global and local measures of its accuracy. Additionally the method enables interval estimation for spatial extension of the areas of predefined risk categories. All of these outputs provide useful contribution to spatial planning, action planning and decision making. Acknowledgement: Our work was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).
Diagnosing and Treating Acute Bronchitis
... Lung Disease Lookup > Acute Bronchitis Diagnosing and Treating Acute Bronchitis It is important to get your questions about ... Symptoms that last a few weeks How Is Acute Bronchitis Diagnosed? Healthcare providers diagnose acute bronchitis by asking ...
Tsorbatzoudis, Haralambos; Emmanouilidou, Maria
2005-06-01
This study aimed to examine the potential of the Theory of Planned Behavior to predict moral behavior in primary school physical education classes. Primary school children (N=611) completed a questionnaire including the Theory of Planned Behavior variables. Also, 21 teachers filled in an adapted version of Horrocks' Prosocial Play Behavior Inventory which assesses five moral behavior facets. Hierarchical regression analysis showed that attitudes toward moral behavior and perceived behavioral control were significant predictors of intention towards moral behavior (54%). Intention and perceived behavioral control predicted teacher-reported moral behavior (41%). The present results indicated that the theory provides a valuable framework for study of primary school children's moral behavior. PMID:16158692
Kernel regression for fMRI pattern prediction
Chu, Carlton; Ni, Yizhao; Tan, Geoffrey; Saunders, Craig J.; Ashburner, John
2011-01-01
This paper introduces two kernel-based regression schemes to decode or predict brain states from functional brain scans as part of the Pittsburgh Brain Activity Interpretation Competition (PBAIC) 2007, in which our team was awarded first place. Our procedure involved image realignment, spatial smoothing, detrending of low-frequency drifts, and application of multivariate linear and non-linear kernel regression methods: namely kernel ridge regression (KRR) and relevance vector regression (RVR)...
Relationship between Multiple Regression and Selected Multivariable Methods.
Schumacker, Randall E.
The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…
Meta-Modeling by Symbolic Regression and Pareto Simulated Annealing
Stinstra, E.; Rennen, G.; Teeuwen, G.J.A.
2006-01-01
The subject of this paper is a new approach to Symbolic Regression.Other publications on Symbolic Regression use Genetic Programming.This paper describes an alternative method based on Pareto Simulated Annealing.Our method is based on linear regression for the estimation of constants.Interval arithm
Using Time-Series Regression to Predict Academic Library Circulations.
Brooks, Terrence A.
1984-01-01
Four methods were used to forecast monthly circulation totals in 15 midwestern academic libraries: dummy time-series regression, lagged time-series regression, simple average (straight-line forecasting), monthly average (naive forecasting). In tests of forecasting accuracy, dummy regression method and monthly mean method exhibited smallest average…
Metformin induced acute pancreatitis
Alsubaie, Sadeem; Almalki, Mussa H.
2013-01-01
Acute pancreatitis frequently presents with abdomen pain but may presents with various skin manifestations as rash and rarely, pancreatic panniculitis. Metformin, one of the most effective and valuable oral hypoglycemic agents in the biguanide class was linked to acute pancreatitis in few cases. Here, we report a case of metformin induce acute pancreatitis in young healthy man with normal renal function.
DEFF Research Database (Denmark)
Anthonsen, Kristian; Høstmark, Karianne; Hansen, Søren;
2013-01-01
Conservative treatment of acute otitis media may lead to more complications. This study evaluates changes in incidence, the clinical and microbiological findings, the complications and the outcome of acute mastoiditis in children in a country employing conservative guidelines in treating acute...... otitis media....
Satish, S.; Rajesh, R.; Kurian, G.; Seethalekshmi, N. V.; Unni, M.; Unni, V. N.
2010-01-01
While acute renal failure secondary to intravascular hemolysis is well described in hemolytic anemias, recurrent acute renal failure as the presenting manifestation of a hemolytic anemia is rare. We report a patient with recurrent acute renal failure who was found to have paroxysmal nocturnal hemoglobinuria (PNH), on evaluation.
Acute Glucose Response Properties Beyond Feeding.
Burnett, C Joseph; Krashes, Michael J
2016-05-01
Hypothalamic AgRP neurons potently coordinate feeding behavior to ensure an organism's viability. However, their acute role in glucose-regulatory function remains to be addressed. Steculorum et al. now report that activation of a specific set of AgRP neurons results in an impairment of insulin-stimulated glucose uptake in brown fat through a myogenic signature program. PMID:27052261
Free Software Development. 1. Fitting Statistical Regressions
Directory of Open Access Journals (Sweden)
Lorentz JÄNTSCHI
2002-12-01
Full Text Available The present paper is focused on modeling of statistical data processing with applications in field of material science and engineering. A new method of data processing is presented and applied on a set of 10 Ni–Mn–Ga ferromagnetic ordered shape memory alloys that are known to exhibit phonon softening and soft mode condensation into a premartensitic phase prior to the martensitic transformation itself. The method allows to identify the correlations between data sets and to exploit them later in statistical study of alloys. An algorithm for computing data was implemented in preprocessed hypertext language (PHP, a hypertext markup language interface for them was also realized and put onto comp.east.utcluj.ro educational web server, and it is accessible via http protocol at the address http://vl.academicdirect.ro/applied_statistics/linear_regression/multiple/v1.5/. The program running for the set of alloys allow to identify groups of alloys properties and give qualitative measure of correlations between properties. Surfaces of property dependencies are also fitted.
Sparse Regression as a Sparse Eigenvalue Problem
Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai
2008-01-01
We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization
Father regression. Clinical narratives and theoretical reflections.
Stein, Ruth
2006-08-01
The author deals with love-hate enthrallment and submission to a primitive paternal object. This is a father-son relationship that extends through increasing degrees of 'primitiveness' or extremeness, and is illustrated through three different constellations that constitute a continuum. One pole of the continuum encompasses certain male patients who show a loving, de-individuated connection to a father experienced as trustworthy, soft, and in need of protection. Further along the continuum is the case of a transsexual patient whose analysis revealed an intense 'God-transference', a bondage to an idealized, feared, and ostensibly protective father-God introject. A great part of this patient's analysis consisted in a fierce struggle to liberate himself from this figure. The other end of the continuum is occupied by religious terrorists, who exemplify the most radical thralldom to a persecutory, godly object, a regressive submission that banishes woman and enthrones a cruel superego, and that ends in destruction and self-destruction. Psychoanalytic thinking has traditionally dealt with the oedipal father and recently with the nurturing father, but there is a gap in thinking about the phallic, archaic father, and his relations with his son(s). The author aims at filling this gap, at the same time as she also raises the very question of 'What is a father?' linking it with literary and religious themes. PMID:16877249
Stahel-Donoho kernel estimation for fixed design nonparametric regression models
Institute of Scientific and Technical Information of China (English)
LIN; Lu
2006-01-01
This paper reports a robust kernel estimation for fixed design nonparametric regression models.A Stahel-Donoho kernel estimation is introduced,in which the weight functions depend on both the depths of data and the distances between the design points and the estimation points.Based on a local approximation,a computational technique is given to approximate to the incomputable depths of the errors.As a result the new estimator is computationally efficient.The proposed estimator attains a high breakdown point and has perfect asymptotic behaviors such as the asymptotic normality and convergence in the mean squared error.Unlike the depth-weighted estimator for parametric regression models,this depth-weighted nonparametric estimator has a simple variance structure and then we can compare its efficiency with the original one.Some simulations show that the new method can smooth the regression estimation and achieve some desirable balances between robustness and efficiency.
A note on constrained M-estimation and its recursive analog in multivariate linear regression models
Institute of Scientific and Technical Information of China (English)
RAO; Calyampudi; R
2009-01-01
In this paper,the constrained M-estimation of the regression coeffcients and scatter parameters in a general multivariate linear regression model is considered.Since the constrained M-estimation is not easy to compute,an up-dating recursion procedure is proposed to simplify the com-putation of the estimators when a new observation is obtained.We show that,under mild conditions,the recursion estimates are strongly consistent.In addition,the asymptotic normality of the recursive constrained M-estimators of regression coeffcients is established.A Monte Carlo simulation study of the recursion estimates is also provided.Besides,robustness and asymptotic behavior of constrained M-estimators are briefly discussed.
Greening, Leilani; Stoppelbein, Laura; Luebbe, Aaron
2010-04-01
Given that parenting practices have been linked to suicidal behavior in adolescence, examining the moderating effect of parenting styles on suicidal behavior early in development could offer potential insight into possible buffers as well as directions for suicide prevention and intervention later in adolescence. Hence, the moderating effects of parenting styles, including authoritarian, permissive, and features of authoritative parenting, on depressed and aggressive children's suicidal behavior, including ideation and attempts, were evaluated with young children (N = 172; 72% male, 28% female) ranging from 6 to 12 years of age. African American (69%) and Caucasian (31%) children admitted for acute psychiatric inpatient care completed standardized measures of suicidal behavior, depressive symptoms, and proactive and reaction aggression. Their parents also completed standardized measures of parental distress and parenting style. Hierarchical regression analyses revealed that, while statistically controlling for age and gender, children who endorsed more depressive symptoms or reactive aggression reported more current and past suicidal behavior than children who endorsed fewer depressive or aggressive symptoms. The significant positive relationship observed between depressive symptoms and childhood suicidal behavior, however, was attenuated by parental use of authoritarian parenting practices for African-American and older children but not for younger and Caucasian children. The ethnic/racial difference observed for the buffering effect of authoritarian parenting practices offers potential theoretical and clinical implications for conceptualizing the moderating effects of parenting styles on African-American and Caucasian children's suicidal behavior.
Acute solvent exposures may contribute to automobile accidents because they increase reaction time and decrease attention, in addition to impairing other behaviors. These effects resemble those of ethanol consumption, both with respect to behavioral effects and neurological mecha...
Imaging of Acute Pancreatitis.
Thoeni, Ruedi F
2015-11-01
Acute pancreatitis is an acute inflammation of the pancreas. Several classification systems have been used in the past but were considered unsatisfactory. A revised Atlanta classification of acute pancreatitis was published that assessed the clinical course and severity of disease; divided acute pancreatitis into interstitial edematous pancreatitis and necrotizing pancreatitis; discerned an early phase (first week) from a late phase (after the first week); and focused on systemic inflammatory response syndrome and organ failure. This article focuses on the revised classification of acute pancreatitis, with emphasis on imaging features, particularly on newly-termed fluid collections and implications for the radiologist.
Directory of Open Access Journals (Sweden)
Mehndiratta M
2002-01-01
Full Text Available Pharmacotherapy for migraine involves treatment for the acute attack as well as using long-term prophylaxis in order to reduce the frequency and severity of the attacks. Based on severity, there are a number of drugs available to treat the acute attacks. For mild to moderate attacks, analgesics, NSAIDs and Ergotamine are effective but severe attacks may need Dihydroergotamine (DHE or a triptan. Sumatriptan and the second generation triptans have revolutionized the acute treatment of migraine. Early and appropriate treatment holds the key to successful therapy of the acute attack. This article discusses the various acute treatment options available.
Ahn, Kuk-Hyun; Palmer, Richard
2016-09-01
Despite wide use of regression-based regional flood frequency analysis (RFFA) methods, the majority are based on either ordinary least squares (OLS) or generalized least squares (GLS). This paper proposes 'spatial proximity' based RFFA methods using the spatial lagged model (SLM) and spatial error model (SEM). The proposed methods are represented by two frameworks: the quantile regression technique (QRT) and parameter regression technique (PRT). The QRT develops prediction equations for flooding quantiles in average recurrence intervals (ARIs) of 2, 5, 10, 20, and 100 years whereas the PRT provides prediction of three parameters for the selected distribution. The proposed methods are tested using data incorporating 30 basin characteristics from 237 basins in Northeastern United States. Results show that generalized extreme value (GEV) distribution properly represents flood frequencies in the study gages. Also, basin area, stream network, and precipitation seasonality are found to be the most effective explanatory variables in prediction modeling by the QRT and PRT. 'Spatial proximity' based RFFA methods provide reliable flood quantile estimates compared to simpler methods. Compared to the QRT, the PRT may be recommended due to its accuracy and computational simplicity. The results presented in this paper may serve as one possible guidepost for hydrologists interested in flood analysis at ungaged sites.
Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan
2015-06-01
Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations. PMID:26572015
Effects of Cadmium and Body Mass on Two Anti-Predator Behaviors of Five Species of Crayfish
Directory of Open Access Journals (Sweden)
E.M. Fryman-Gripshover
2010-01-01
Full Text Available Five crayfish species (Orconectes placidus, O. virilis, Procambarus acutus, P. alleni and P. clarkii were subjected to Cd exposure in 96 h acute toxicity tests to assess changes in two anti-predator behaviors, the tail-flip response and the claw-raise response. The tail-flip response was significantly affected by Cd exposure in three of five cases (ANOVA p-1 for O. virilis. Regression analysis detected significant decreasing trends in the tail-flip behavior as cadmium concentrations increased in four species of crayfish (p0.42. In two cases, planned comparisons with Duncans test revealed that at least one exposure concentration of Cd increased the frequency of the claw-raise response significantly compared to controls (p-1 for P. clarkii. Regression analysis indicated that the claw-raise behavior was related to Cd concentration in two species (p0.50. When control groups were compared across species, a significant correlation was measured between body mass and both the tail flip and claw raise behaviors. Across the five species, as body mass increased, the tail flip response decreased in frequency (r = -0.72; p<0.001 and the claw raise response increased in frequency (r = 0.70; p = 0.001. Interference with either behavior, but especially the tail flip response, could have important survival consequences, especially for juvenile crayfish which are typically more sensitive to cadmium exposure.
Deep Human Parsing with Active Template Regression.
Liang, Xiaodan; Liu, Si; Shen, Xiaohui; Yang, Jianchao; Liu, Luoqi; Dong, Jian; Lin, Liang; Yan, Shuicheng
2015-12-01
In this work, the human parsing task, namely decomposing a human image into semantic fashion/body regions, is formulated as an active template regression (ATR) problem, where the normalized mask of each fashion/body item is expressed as the linear combination of the learned mask templates, and then morphed to a more precise mask with the active shape parameters, including position, scale and visibility of each semantic region. The mask template coefficients and the active shape parameters together can generate the human parsing results, and are thus called the structure outputs for human parsing. The deep Convolutional Neural Network (CNN) is utilized to build the end-to-end relation between the input human image and the structure outputs for human parsing. More specifically, the structure outputs are predicted by two separate networks. The first CNN network is with max-pooling, and designed to predict the template coefficients for each label mask, while the second CNN network is without max-pooling to preserve sensitivity to label mask position and accurately predict the active shape parameters. For a new image, the structure outputs of the two networks are fused to generate the probability of each label for each pixel, and super-pixel smoothing is finally used to refine the human parsing result. Comprehensive evaluations on a large dataset well demonstrate the significant superiority of the ATR framework over other state-of-the-arts for human parsing. In particular, the F1-score reaches 64.38 percent by our ATR framework, significantly higher than 44.76 percent based on the state-of-the-art algorithm [28]. PMID:26539846
Deep Human Parsing with Active Template Regression.
Liang, Xiaodan; Liu, Si; Shen, Xiaohui; Yang, Jianchao; Liu, Luoqi; Dong, Jian; Lin, Liang; Yan, Shuicheng
2015-12-01
In this work, the human parsing task, namely decomposing a human image into semantic fashion/body regions, is formulated as an active template regression (ATR) problem, where the normalized mask of each fashion/body item is expressed as the linear combination of the learned mask templates, and then morphed to a more precise mask with the active shape parameters, including position, scale and visibility of each semantic region. The mask template coefficients and the active shape parameters together can generate the human parsing results, and are thus called the structure outputs for human parsing. The deep Convolutional Neural Network (CNN) is utilized to build the end-to-end relation between the input human image and the structure outputs for human parsing. More specifically, the structure outputs are predicted by two separate networks. The first CNN network is with max-pooling, and designed to predict the template coefficients for each label mask, while the second CNN network is without max-pooling to preserve sensitivity to label mask position and accurately predict the active shape parameters. For a new image, the structure outputs of the two networks are fused to generate the probability of each label for each pixel, and super-pixel smoothing is finally used to refine the human parsing result. Comprehensive evaluations on a large dataset well demonstrate the significant superiority of the ATR framework over other state-of-the-arts for human parsing. In particular, the F1-score reaches 64.38 percent by our ATR framework, significantly higher than 44.76 percent based on the state-of-the-art algorithm [28].
Using Raw VAR Regression Coefficients to Build Networks can be Misleading.
Bulteel, Kirsten; Tuerlinckx, Francis; Brose, Annette; Ceulemans, Eva
2016-01-01
Many questions in the behavioral sciences focus on the causal interplay of a number of variables across time. To reveal the dynamic relations between the variables, their (auto- or cross-) regressive effects across time may be inspected by fitting a lag-one vector autoregressive, or VAR(1), model and visualizing the resulting regression coefficients as the edges of a weighted directed network. Usually, the raw VAR(1) regression coefficients are drawn, but we argue that this may yield misleading network figures and characteristics because of two problems. First, the raw regression coefficients are sensitive to scale and variance differences among the variables and therefore may lack comparability, which is needed if one wants to calculate, for example, centrality measures. Second, they only represent the unique direct effects of the variables, which may give a distorted picture when variables correlate strongly. To deal with these problems, we propose to use other VAR(1)-based measures as edges. Specifically, to solve the comparability issue, the standardized VAR(1) regression coefficients can be displayed. Furthermore, relative importance metrics can be computed to include direct as well as shared and indirect effects into the network.
Institute of Scientific and Technical Information of China (English)
喻秋珺; 赵晶; 刘芳娥; 李静; 朱伟军; 李小康
2006-01-01
组大鼠行为和情绪的变化.结果:纳人大鼠49只,最终进入结果分析49只,无脱失值.①大鼠情绪状态观察结果:实验结束后观察显示,睡眠剥夺+被动吸烟24 h组较睡眠剥夺24 h组,睡眠剥夺+被动吸烟54 h组较睡眠剥夺54 h组,睡眠剥夺54 h组较睡眠剥夺24 h组情绪低靡,蜷缩喜静,对外界刺激不敏感,反应冷漠,对其他鼠的攻击行为较少.②旷场实验测试结果:睡眠剥夺24 h组距旷场中心的平均距离明显小于空白对照组及睡眠剥夺+被动吸烟24 h组[(53.93±1.83,58.21±4.45,58.11±1.62)cm,(P＜0.01～0.05)],睡眠剥夺54 h组距旷场中心平均距离明显大于睡眠剥夺24 h组[(61.53±3.02,58.11±1.62)cm,(P＜0.01)],睡眠剥夺24 h组的运动总距离明显大于睡眠剥夺+被动吸烟24h组及空白对照组[(3 310.45±1 445.97,1 818.20±733.25,2 338.15±694.70)cm,(P＜0.01～0.05)],睡眠剥夺54 h组运动总距离明显大于睡眠剥夺+被动吸烟54 h组,小于睡眠剥夺24h组[(2410.70±548.64,1 473.50±945.89,3 310.45±1445.97)cm,(P＜0.05)].结论:大鼠的行为和情绪反应随睡眠剥夺时间的延长呈现先兴奋后抑制的趋势,而被动吸烟在整个大鼠睡眠剥夺过程中对大鼠的行为和情绪状态起抑制作用.%BACKGROUND:Sleep deprivation, resulting in a series of physiological and psychological reactions, is a common phenomenon in our modem society. Recently, many physical and medical therapies are on their way to eliminate the negative influence the sleep deprivation exerted on our human beings, and a large number of cigarette smokers believe that cigarette smoke can obviously improve their abnormal behavioral performance and negative emotional fluctuation caused by sleep deprivation in short terms.However, there are few researches but many disputes when it comes to effect of passive smoking on the behavior and emotion of rats on the occasion of acute sleep deprivation.OBJECTIVE: To investigate the effect of passive smoking (PS) on the
Directory of Open Access Journals (Sweden)
Deshmukh P
2009-08-01
Full Text Available Background: In India, common morbidities among children under 3 years of age are fever, acute respiratory infections, diarrhea. Effective early management at the home level and health care-seeking behavior in case of appearance of danger signs are key strategies to prevent the occurrence of severe and life-threatening complications. Objectives: To find out the prevalence of acute child morbidities, their determinants and health-seeking behavior of the mothers of these children. Setting and Design: The cross-sectional study was carried out in Wardha district of central India. 0 Material and Methods: We interviewed 990 mothers of children below 3 years of age using 30-cluster sampling method. Nutritional status was defined by National Center for Health Statistics (NCHS reference. Composite index of anthropometric failure (CIAF was constructed. Hemoglobin concentration in each child was estimated using the ′filter paper cyanm ethemoglobin method.′ Using World Health Organization guidelines, anemia was defined as hemoglobin concentration less than 110 g/L. Post-survey focus group discussions (FGDs were undertaken to bridge gaps in information obtained from the survey. Statistical Analysis: The data was analyzed by using SPSS 12.0.1 software package. Chi-square was used to test the association, while odds ratios were calculated to measure the strength of association. Multiple logistic regression analysis was applied to derive the final model. Results: Anemia was detected in 80.3% of children, and 59.6% of children were undernourished as indicated by CIAF. The overall prevalence of acute morbidity was 59.9%. Children with mild anemia, moderate anemia and severe anemia had 1.52, 1.61 and 9.21 times higher risk of being morbid, respectively. Similarly, children with single, 2 and 3 anthropometric failures had 1.16, 1.29 and 2.27 times higher risk of being morbid, respectively. Out of 594 (60% children with at least one of the acute morbidities, 520
Maximum Likelihood Estimation of the Bivariate Logistic Regression with Threshold Parameters
Jungpin Wu; Chiung Wen Chang
2005-01-01
In discussing the relationship between the successful probability of a binary random variable and a certain set of explanatory variables, the logistic regression is popular in various fields, especially in medicine researches. For example, (1) using remedy methods to explain the probability of recovery from some disease; (2) building a prediction model for the e-commence customer buying behavior; (3) building a model to decide the cut-point of the life insurance sales hiring; (4) building a c...
The demand for lottery expenditure in Taiwan: a quantile regression approach
Cho-Min Lin; Kung-Cheng Lin
2007-01-01
This paper is a pioneering attempt to apply the quantile regression method (QRM) to the demand for lottery expenditure in order to consider the extreme behavior of lottery expenditure as well as clarify the diverse results obtained from previous studies on lottery expenditure. The results of this study reveal that there exists a complementary correlation both between benevolent donations and lottery expenditure, and between entertainment expenditure and lottery expenditure. By contrast, the r...
Persell, Stephen D.; Friedberg, Mark W.; Meeker, Daniella; Linder, Jeffrey A; Craig R. Fox; Goldstein, Noah J.; Shah, Parth D; Knight, Tara K; Doctor, Jason N
2013-01-01
Abstract Background Inappropriate antibiotic prescribing for nonbacterial infections leads to increases in the costs of care, antibiotic resistance among bacteria, and adverse drug events. Acute respiratory infections (ARIs) are the most common reason for inappropriate antibiotic use. Most prior efforts to decrease inappropriate antibiotic prescribing for ARIs (e.g., educational or informational interventions) have relied on the implicit assumption th...
Kepler AutoRegressive Planet Search
Caceres, Gabriel Antonio; Feigelson, Eric
2016-01-01
The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; AR-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. The analysis procedures of the project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. Our findings to date on real
Association between acute pancreatitis and peptic ulcer disease
Institute of Scientific and Technical Information of China (English)
Kang-Moon Lee; Chang-Nyol Paik; Woo Chul Chung; Jin Mo Yang
2011-01-01
AIM:To evaluate the relationship between peptic ulcer disease (PUD) and acute pancreatitis.METHODS:A cohort of 78 patients with acute pancreatitis were included in this study.The presence of PUD and the Helicobacter pylori (H.pylori ) status were assessed by an endoscopic method.The severity of acute pancreatitis was assessed using Ranson's score, the Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ score,computed tomography severity index and the clinical data during hospitalization,all of which were compared between the patients with and without PUD.The risk factors for PUD were also evaluated. RESULTS:Among 78 patients,41 patients (52.6%) with acute pancreatitis suffered from PUD,but only 13 (31.7%) patients with PUD were infected by H.pylori .On univariate analysis,male gender,an etiology of alcohol-induced pancreatitis,a history of smoking or alcohol consumption, elevated triglyceride and C-reactive protein levels, and high APACHE Ⅱ score were significantly associated with PUD.However,on multivariate logistic regression analysis,the APACHE Ⅱ score (odds ratio:7.69; 95% confidence interval:1.78-33.33; P < 0.01) was found to be the only independent risk factor for PUD.CONCLUSION:Patients with acute pancreatitis are liable to suffer from PUD.PUD is associated with severe acute pancreatitis according to the APACHE Ⅱ score, and treatment for PUD should be considered for patients with severe acute pancreatitis.
Acute otitis media and acute bacterial sinusitis.
Wald, Ellen R
2011-05-01
Acute otitis media and acute bacterial sinusitis are 2 of the most common indications for antimicrobial agents in children. Together, they are responsible for billions of dollars of health care expenditures. The pathogenesis of the 2 conditions is identical. In the majority of children with each condition, a preceding viral upper respiratory tract infection predisposes to the development of the acute bacterial complication. It has been shown that viral upper respiratory tract infection predisposes to the development of acute otitis media in 37% of cases. Currently, precise microbiologic diagnosis of acute otitis media and acute bacterial sinusitis requires performance of tympanocentesis in the former and sinus aspiration in the latter. The identification of a virus from the nasopharynx in either case does not obviate the need for antimicrobial therapy. Furthermore, nasal and nasopharyngeal swabs are not useful in predicting the results of culture of the middle ear or paranasal sinus. However, it is possible that a combination of information regarding nasopharyngeal colonization with bacteria and infection with specific viruses may inform treatment decisions in the future.
Acute chylous peritonitis due to acute pancreatitis
Institute of Scientific and Technical Information of China (English)
Georgios K Georgiou; Haralampos Harissis; Michalis Mitsis; Haralampos Batsis; Michalis Fatouros
2012-01-01
We report a case of acute chylous ascites formation presenting as peritonitis (acute chylous peritonitis) in a patient suffering from acute pancreatitis due to hypertriglyceridemia and alcohol abuse.The development of chylous ascites is usually a chronic process mostly involving malignancy,trauma or surgery,and symptoms arise as a result of progressive abdominal distention.However,when accumulation of "chyle" occurs rapidly,the patient may present with signs of peritonitis.Preoperative diagnosis is difficult since the clinical picture usually suggests hollow organ perforation,appendicitis or visceral ischemia.Less than 100 cases of acute chylous peritonitis have been reported.Pancreatitis is a rare cause of chyloperitoneum and in almost all of the cases chylous ascites is discovered some days (or even weeks) after the onset of symptoms of pancreatitis.This is the second case in the literature where the patient presented with acute chylous peritonitis due to acute pancreatitis,and the presence of chyle within the abdominal cavity was discovered simultaneously with the establishment of the diagnosis of pancreatitis.The patient underwent an exploratory laparotomy for suspected perforated duodenal ulcer,since,due to hypertriglyceridemia,serum amylase values appeared within the normal range.Moreover,abdominal computed tomography imaging was not diagnostic for pancreatitis.Following abdominal lavage and drainage,the patient was successfully treated with total parenteral nutrition and octreotide.
Acute chylous peritonitis due to acute pancreatitis.
Georgiou, Georgios K; Harissis, Haralampos; Mitsis, Michalis; Batsis, Haralampos; Fatouros, Michalis
2012-04-28
We report a case of acute chylous ascites formation presenting as peritonitis (acute chylous peritonitis) in a patient suffering from acute pancreatitis due to hypertriglyceridemia and alcohol abuse. The development of chylous ascites is usually a chronic process mostly involving malignancy, trauma or surgery, and symptoms arise as a result of progressive abdominal distention. However, when accumulation of "chyle" occurs rapidly, the patient may present with signs of peritonitis. Preoperative diagnosis is difficult since the clinical picture usually suggests hollow organ perforation, appendicitis or visceral ischemia. Less than 100 cases of acute chylous peritonitis have been reported. Pancreatitis is a rare cause of chyloperitoneum and in almost all of the cases chylous ascites is discovered some days (or even weeks) after the onset of symptoms of pancreatitis. This is the second case in the literature where the patient presented with acute chylous peritonitis due to acute pancreatitis, and the presence of chyle within the abdominal cavity was discovered simultaneously with the establishment of the diagnosis of pancreatitis. The patient underwent an exploratory laparotomy for suspected perforated duodenal ulcer, since, due to hypertriglyceridemia, serum amylase values appeared within the normal range. Moreover, abdominal computed tomography imaging was not diagnostic for pancreatitis. Following abdominal lavage and drainage, the patient was successfully treated with total parenteral nutrition and octreotide.
Acute pancreatitis in acute viral hepatitis
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
AIM: To elucidate the frequency and characteristics of pancreatic involvement in the course of acute (nonfulminant) viral hepatitis.METHODS: We prospectively assessed the pancreatic involvement in patients with acute viral hepatitis who presented with severe abdomimanl pain.RESULTS: We studied 124 patients with acute viral hepatitis, of whom 24 presented with severe abdominal pain. Seven patients (5.65%) were diagnosed to have acute pancreatitis. All were young males. Five patients had pancreatitis in the first week and two in the fourth week after the onset of jaundice. The pancreatitis was mild and all had uneventful recovery from both pancreatitis and hepatitis on conservative treatment.The etiology of pancreatitis was hepatitis E virus in 4,hepatitis A virus in 2, and hepatitis B virus in 1 patient.One patient had biliary sludge along with HEV infection.The abdominal pain of remaining seventeen patients was attributed to stretching of Glisson's capsule.CONCLUSION: Acute pancreatitis occurs in 5.65% of patients with acute viral hepatitis, it is mild and recovers with conservative management.
Acute chylous peritonitis due to acute pancreatitis.
Georgiou, Georgios K; Harissis, Haralampos; Mitsis, Michalis; Batsis, Haralampos; Fatouros, Michalis
2012-04-28
We report a case of acute chylous ascites formation presenting as peritonitis (acute chylous peritonitis) in a patient suffering from acute pancreatitis due to hypertriglyceridemia and alcohol abuse. The development of chylous ascites is usually a chronic process mostly involving malignancy, trauma or surgery, and symptoms arise as a result of progressive abdominal distention. However, when accumulation of "chyle" occurs rapidly, the patient may present with signs of peritonitis. Preoperative diagnosis is difficult since the clinical picture usually suggests hollow organ perforation, appendicitis or visceral ischemia. Less than 100 cases of acute chylous peritonitis have been reported. Pancreatitis is a rare cause of chyloperitoneum and in almost all of the cases chylous ascites is discovered some days (or even weeks) after the onset of symptoms of pancreatitis. This is the second case in the literature where the patient presented with acute chylous peritonitis due to acute pancreatitis, and the presence of chyle within the abdominal cavity was discovered simultaneously with the establishment of the diagnosis of pancreatitis. The patient underwent an exploratory laparotomy for suspected perforated duodenal ulcer, since, due to hypertriglyceridemia, serum amylase values appeared within the normal range. Moreover, abdominal computed tomography imaging was not diagnostic for pancreatitis. Following abdominal lavage and drainage, the patient was successfully treated with total parenteral nutrition and octreotide. PMID:22563182
Pre-hospital delay in acute myocardial infarction: judgement of symptoms and resistance to pain
Directory of Open Access Journals (Sweden)
Fernanda Carneiro Mussi
2014-02-01
Full Text Available Objective To estimate the time of decision (TD to look for medical care and the time of arrival (TA at the health service for men (M and women (W suffering from acute myocardial infarction and to analyze the influence of the interpretation of pain and pain resistance behaviors during these times. Methods This is an exploratory research, performed at the university hospital in Salvador/Bahia. 43 W and 54 M were interviewed. To study the dependence among sociodemographic and gender variables, the Fisher Exact Test was used. To analyze times, a geometric mean (GM was used. In order to verify the association between the GM of TD and TA and the judgment of pain, and between the GM of TD and TA and the behavior of resistance to pain, as well as to test the time of interaction between the gender variable and other variables of interest, the robust regression model was used. The statistical significance adopted was 5%. Results The GM of the TD for M was 1.13 h; for W, 0.74 h. The GM of the TA was 1.74 h for M and 1.47 h for W. Those who did not recognize the symptoms of AMI and presented behavior of resistance to pain had higher TD and TA, being the associations significant. Gender did not change the associations of interest. Conclusion The findings demonstrate the importance of health education aiming at the benefits of early treatment.
Energy Technology Data Exchange (ETDEWEB)
Umezu, Toyoshi, E-mail: umechan2@nies.go.jp; Shibata, Yasuyuki, E-mail: yshibata@nies.go.jp
2014-09-01
The present study aimed to clarify whether dose–response profiles of acute behavioral effects of 1,2-dichloroethane (DCE), 1,1,1-trichloroethane (TCE), trichloroethylene (TRIC), and tetrachloroethylene (PERC) differ. A test battery involving 6 behavioral endpoints was applied to evaluate the effects of DCE, TCE, TRIC, and PERC in male ICR strain mice under the same experimental conditions. The behavioral effect dose–response profiles of these compounds differed. Regression analysis was used to evaluate the relationship between the dose–response profiles and structural and physical properties of the compounds. Dose–response profile differences correlated significantly with differences in specific structural and physical properties. These results suggest that differences in specific structural and physical properties of DCE, TCE, TRIC, and PERC are responsible for differences in behavioral effects that lead to a variety of dose–response profiles. - Highlights: • We examine effects of 4 chlorinated hydrocarbons on 6 behavioral endpoints in mice. • The behavioral effect dose–response profiles for the 4 compounds are different. • We utilize regression analysis to clarify probable causes of the different profiles. • The compound's physicochemical properties probably produce the different profiles.
A fast nonlinear regression method for estimating permeability in CT perfusion imaging.
Bennink, Edwin; Riordan, Alan J; Horsch, Alexander D; Dankbaar, Jan Willem; Velthuis, Birgitta K; de Jong, Hugo W
2013-11-01
Blood-brain barrier damage, which can be quantified by measuring vascular permeability, is a potential predictor for hemorrhagic transformation in acute ischemic stroke. Permeability is commonly estimated by applying Patlak analysis to computed tomography (CT) perfusion data, but this method lacks precision. Applying more elaborate kinetic models by means of nonlinear regression (NLR) may improve precision, but is more time consuming and therefore less appropriate in an acute stroke setting. We propose a simplified NLR method that may be faster and still precise enough for clinical use. The aim of this study is to evaluate the reliability of in total 12 variations of Patlak analysis and NLR methods, including the simplified NLR method. Confidence intervals for the permeability estimates were evaluated using simulated CT attenuation-time curves with realistic noise, and clinical data from 20 patients. Although fixating the blood volume improved Patlak analysis, the NLR methods yielded significantly more reliable estimates, but took up to 12 × longer to calculate. The simplified NLR method was ∼4 × faster than other NLR methods, while maintaining the same confidence intervals (CIs). In conclusion, the simplified NLR method is a new, reliable way to estimate permeability in stroke, fast enough for clinical application in an acute stroke setting.
Institute of Scientific and Technical Information of China (English)
赵秋利; 李金秀
2012-01-01
Objective To develop a scale for measuring pre-hospital delay behavior intention for high risk of acute myocardial infarction and test its reliability and validity,so as to provide one effective assessment tool for clinic.Methods The scale development of pre-hospital delay behavior intention for high risk of acute myocardial infarction(RSPHDBIHRAMI) was developed based on the framework of theory of planned behavior.First,scale items were constructed by literature reviewing,which further screened by expert evaluation and pilot test.Finally,selected 420 high risk of acute myocardial infarction in Harbin to test the reliability and validity of RSPHDBIHRAMI.Results The rating scale of pre-hospital delay behavior intention for high risk of acute myocardial infarction (RSPHDBIHRAMI) was developed,with good reliability and validity,it composed of six factors ( medical treatment decision-making,symptoms alert,habits of response style,symptoms of the degree of judgment,hinder medical treatment factors and promote medical treatment factors),Cronbach' s coefficients of the scale were 0.744 and the cumulative contribution of variance was 58.694％.Conclusions Psychometric properties analysis showed that the scale has excellent levels of reliability and validity,which not only provide a useful tool for assessment pre-hospital delay behavior intention for high risk of acute myocardial infarction,but also provide assistance for further targeting health education intervene.%目的 初步编制“急性心肌梗死高危者院前延迟行为意向测评量表”,并对其信效度进行检验,为评估急性心肌梗死高危者院前延迟倾向提供一个有效的测评工具.方法 应用量表开发的综合策略,以计划行为理论作为编制量表的基本理论框架,在广泛参阅国内外相关文献资料的基础上,建立条目池,采用专家评议法和预试验法对量表条目进行筛选,形成暂定版量表,并选取哈尔滨420名急性心肌梗死高危
Institute of Scientific and Technical Information of China (English)
陶杨; 丁秀芳; 陈育尧; 孙学刚; 覃桂强; 张艳平; 黄杰春; 吕志平
2011-01-01
目的 观察急性应激状态下大鼠行为学的改变及不同时间点蓝斑内酪氨酸羟化酶(TH)和多巴胺一β一羟化酶(DBH)的基因表达.方法 将24只健康雄性Wistar大鼠随机分为空白对照组和模型组,模型组又分为造模后1、3、6 h组,每组6只.运用束缚和游泳的方法造模,观察其行为学的改变;并分别在造模后相应时间点取出蓝斑,用RT-PCR法检测蓝斑TH、DBH的表达.结果 模型组造模前后比较,1、6 h组的穿越格数和直立次数明显下降(P0.05),TH和DBH两者的表达趋势相似.结论 急性应激使大鼠的行为能力降低,蓝斑去甲肾上腺素能神经元中TH、DBH表达增高,使去甲肾上腺素合成增多,而去甲肾上腺素可以显著影响大鼠的情绪行为,在应激过程中起重要作用;TH、DBH表达的增高可能参与了急性应激所致的行为异常.%Objective To observe the emotional behaviors and stress-induced expression of tyrosine hydroxylas and dopamine-β-hydroxylase in the locus coeruleus.Methods Twenty-four healthy male rats were randomly divided into control group and experimental groups.Rats of the experimental groups received acute stress (i.e.restriction of mobility and swimming)and then the emotional behaviors were examined.Locus coeruleus were collected from the decapitated heads at 1 h, 3 h, and 6 h after the stress application.The levels of mRNA of TH and DBH in the locus coeroleus were determined by RT-PCR.Results After tbe acute stress, the traversing grid decreases in group 1 h,3 h and 6 h (P＜0.05), erect time also reduces in three model groups (P＜0.05,P＜0.01) ,and grooming time only decreases in group 3 h (P＜0.05).Compared with control group, the traversing grid reduces in group 1 h (P＜0.05) ,erect time decreases in group 1 h and 3 h (P＜0.01 ,P＜0.05) ,and grooming time with all model groups have statistical significance (P＜0.01).The levels of mRNA of TH and DBH in the locus coeruleus of the treatment
Local Linear Regression for Data with AR Errors
Institute of Scientific and Technical Information of China (English)
Runze Li; Yan Li
2009-01-01
In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques.We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one.From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.
Regression-kriging for characterizing soils with remotesensing data
Institute of Scientific and Technical Information of China (English)
Yufeng GE; J.Alex THOMASSON; Ruixiu SUI; James WOOTEN
2011-01-01
In precision agriculture regression has been used widely to quantify the relationship between soil attributes and other environmental variables.However,spatial correlation existing in soil samples usually violates a basic assumption of regression:sample independence.In this study,a regression-kriging method was attempted in relating soil properties to the remote sensing image of a cotton field near Vance,Mississippi,USA.The regressionkriging model was developed and tested by using 273 soil samples collected from the field.The result showed that by properly incorporating the spatial correlation information of regression residuals,the regression-kriging model generally achieved higher prediction accuracy than the stepwise multiple linear regression model.Most strikingly,a 50％ increase in prediction accuracy was shown in soil sodium concentration.Potential usages of regressionkriging in future precision agriculture applications include real-time soil sensor development and digital soil mapping.
Asymptotic theory of nonparametric regression estimates with censored data
Institute of Scientific and Technical Information of China (English)
施沛德; 王海燕; 张利华
2000-01-01
For regression analysis, some useful Information may have been lost when the responses are right censored. To estimate nonparametric functions, several estimates based on censored data have been proposed and their consistency and convergence rates have been studied in literat黵e, but the optimal rates of global convergence have not been obtained yet. Because of the possible Information loss, one may think that it is impossible for an estimate based on censored data to achieve the optimal rates of global convergence for nonparametric regression, which were established by Stone based on complete data. This paper constructs a regression spline estimate of a general nonparametric regression f unction based on right-censored response data, and proves, under some regularity condi-tions, that this estimate achieves the optimal rates of global convergence for nonparametric regression. Since the parameters for the nonparametric regression estimate have to be chosen based on a data driven criterion, we also obtai
Forecasting Daily Solar Energy Production Using Robust Regression Techniques
Louppe, Gilles; Prettenhofer, Peter
2014-01-01
We describe a novel approach to forecast daily solar energy production based on the output of a numerical weather prediction (NWP) model using non-parametric robust regression techniques. Our approach comprises two steps: First, we use a non-linear interpolation technique, Gaussian Process regression (also known as Kriging in Geostatistics), to interpolate the coarse NWP grid to the location of the solar energy production facilities. Second, we use Gradient Boosted Regression Trees, a non-par...
Spontaneous Regression of a Large Lumbar Disc Extrusion
Ryu, Sung-Joo; Kim, In Soo
2010-01-01
Although the spontaneous disappearance or decrease in size of a herniated disc is well known, that of a large extruded disc has rarely been reported. This paper reports a case of a spontaneous regression of a large lumbar disc extrusion. The disc regressed spontaneously with clinical improvement and was documented on a follow up MRI study 6 months later. The literature is reviewed and the possible mechanisms of spontaneous disc regression are discussed.
Acupuncture and Spontaneous Regression of a Radiculopathic Cervical Herniated Disc
Kim Sung-Ha; Park Man-Young; Lee Sang-Mi; Jung Ho-Hyun; Kim Jae-Kyoun; Lee Jong-Deok; Kim Dong-Woung; Yeom Seung-Ryong; Lim Jin-Young; Park Min-Jung; Park Se-Woon; Kim Sung-Chul
2012-01-01
The spontaneous regression of herniated cervical discs is not a well-established phenomenon. However, we encountered a case of a spontaneous regression of a severe radiculopathic herniated cervical disc that was treated with acupuncture, pharmacopuncture, and herb medicine. The symptoms were improved within 12 months of treatment. Magnetic resonance imaging (MRI) conducted at that time revealed marked regression of the herniated disc. This case provides an additional example of spontaneous re...
EFFECTIVENESS OF TEST CASE PRIORITIZATION TECHNIQUES BASED ON REGRESSION TESTING
Directory of Open Access Journals (Sweden)
Thillaikarasi Muthusamy
2014-12-01
Full Text Available Regression testing concentrates on finding defects after a major code change has occurred. Specifically, it exposes software regressions or old bugs that have reappeared. It is an expensive testing process that has been estimated to account for almost half of the cost of software maintenance. To improve the regression testing process, test case prioritization techniques organizes the execution level of test cases. Further, it gives an improved rate of fault identification, when test suites cannot run to completion.
Bootstrapped Multinomial Logistic Regression on Apnea Detection Using ECG Data
Sanabila, Hadaiq R.; Fanany, Mohamad Ivan; Jatmiko, Wisnu; Arymurthy, Aniati Murni
2010-01-01
In designing a classification system, one of the most important considerations is how optimal the classifier will adapt and give best generalization when it is given data from unknown model distribution. Unlike linear regression, logistic regression has no simple formula to assess its generalization ability. In such cases, bootstrapping offers an advantage over analytical methods thanks to its simplicity. This paper presents an analysis of bootstrapped multinomial logistic regression appli...
Regression Test Selection when Evolving Software with Aspects
Delamare, Romain; Baudry, Benoit; Le Traon, Yves
2008-01-01
Aspect-oriented software evolution introduces new challenges for regression test selection. When a program, that has been thoroughly tested, evolves by addition of an aspect, it is important for regression test selection to know which test cases are impacted by the new aspects and which are not. The work presented here proposes a classification for regression test cases and introduces an algorithm for impact analysis of aspects on a set of test cases. A major benefit of this analysis is that ...
Steganalysis of LSB Image Steganography using Multiple Regression and Auto Regressive (AR Model
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Souvik Bhattacharyya
2011-07-01
Full Text Available The staggering growth in communication technologyand usage of public domain channels (i.e. Internet has greatly facilitated transfer of data. However, such open communication channelshave greater vulnerability to security threats causing unauthorizedin- formation access. Traditionally, encryption is used to realizethen communication security. However, important information is notprotected once decoded. Steganography is the art and science of communicating in a way which hides the existence of the communication.Important information is ﬁrstly hidden in a host data, such as digitalimage, text, video or audio, etc, and then transmitted secretly tothe receiver. Steganalysis is another important topic in informationhiding which is the art of detecting the presence of steganography. Inthis paper a novel technique for the steganalysis of Image has beenpresented. The proposed technique uses an auto-regressive model todetect the presence of the hidden messages, as well as to estimatethe relative length of the embedded messages.Various auto regressiveparameters are used to classify cover image as well as stego imagewith the help of a SVM classiﬁer. Multiple Regression analysis ofthe cover carrier along with the stego carrier has been carried outin order to ﬁnd out the existence of the negligible amount of thesecret message. Experimental results demonstrate the effectivenessand accuracy of the proposed technique.
Atrial fibrillation (acute onset)
Lip, Gregory Y. H.; Watson, Timothy
2008-01-01
Acute atrial fibrillation is rapid, irregular, and chaotic atrial activity of less than 48 hours' duration. It resolves spontaneously within 24 to 48 hours in over 50% of people. In this review we have included studies on patients with onset up to 7 days previously. Risk factors for acute atrial fibrillation include increasing age, CVD, alcohol abuse, diabetes, and lung disease.Acute atrial fibrillation increases the risk of stroke and heart failure.
Acute generalized exanthematous pustulosis
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K.S. Dhillon
2012-10-01
Full Text Available Acute generalized exanthematous pustulosis (AGEP is a rare reaction pattern with a typical morphology and a short clinical course that in majority of cases is related to medication administration. It is an acute pustular eruption with unique clinical features, a rapid clinical course and a typical histopathology. Herein, we report the case of a patient with acute generalized exanthematous pustulosis for its classical presentation.
Streptococcal acute pharyngitis
2014-01-01
Acute pharyngitis/tonsillitis, which is characterized by inflammation of the posterior pharynx and tonsils, is a common disease. Several viruses and bacteria can cause acute pharyngitis; however, Streptococcus pyogenes (also known as Lancefield group A β-hemolytic streptococci) is the only agent that requires an etiologic diagnosis and specific treatment. S. pyogenes is of major clinical importance because it can trigger post-infection systemic complications, acute rheumatic fever, and post-s...
Energy Technology Data Exchange (ETDEWEB)
Merkle, Elmar M.; Goerich, Johannes [Department of Radiology, University Hospitals of Ulm, Steinhoevel Strasse 9, 89075 Ulm (Germany)
2002-08-01
Acute pancreatitis is defined as an acute inflammatory process of the pancreas with variable involvement of peripancreatic tissues or remote organ systems. This article reports the current classification, definition and terminology, epidemiology and etiology, pathogenesis and pathological findings, clinical and laboratory findings, and finally imaging findings of acute pancreatitis with emphasis on cross-sectional imaging modalities such as ultrasound, computed tomography, and magnetic resonance imaging. (orig.)
Acute Idiopathic Scrotal Edema
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Micheál Breen
2013-01-01
Full Text Available We report a case of acute idiopathic scrotal edema (AISE in a 4-year-old boy who presented with acute scrotal pain and erythema. The clinical features, ultrasound appearance, and natural history of this rare diagnosis are reviewed. In this report, we highlight the importance of good ultrasound technique in differentiating the etiology of the acute scrotum and demonstrate the color Doppler “Fountain Sign” that is highly suggestive of AISE.
Mehndiratta M
2002-01-01
Pharmacotherapy for migraine involves treatment for the acute attack as well as using long-term prophylaxis in order to reduce the frequency and severity of the attacks. Based on severity, there are a number of drugs available to treat the acute attacks. For mild to moderate attacks, analgesics, NSAIDs and Ergotamine are effective but severe attacks may need Dihydroergotamine (DHE) or a triptan. Sumatriptan and the second generation triptans have revolutionized the acute treatment of migra...
Acupuncture and Spontaneous Regression of a Radiculopathic Cervical Herniated Disc
Directory of Open Access Journals (Sweden)
Kim Sung-Ha
2012-06-01
Full Text Available The spontaneous regression of herniated cervical discs is not a well-established phenomenon. However, we encountered a case of a spontaneous regression of a severe radiculopathic herniated cervical disc that was treated with acupuncture, pharmacopuncture, and herb medicine. The symptoms were improved within 12 months of treatment. Magnetic resonance imaging (MRI conducted at that time revealed marked regression of the herniated disc. This case provides an additional example of spontaneous regression of a herniated cervical disc documented by MRI following non-surgical treatment.
Spontaneous Regression of a Carcinoid Tumor following Pregnancy
Directory of Open Access Journals (Sweden)
A. Sewpaul
2014-01-01
Full Text Available We present a case of spontaneous regression of a neuroendocrine tumor following pregnancy in the absence of chemotherapy, radiotherapy, or alternative medicine (including herbal medicine. The diagnosis of a nonsecretory carcinoid tumor was confirmed using CT imaging, octreotide scan, and histology. Furthermore, serial imaging has demonstrated spontaneous regression of the carcinoid suggesting that pregnancy did not worsen the course of the disease but instead may have contributed to tumour regression. We discuss mechanisms underlying tumour regression and the possible effect of pregnancy on these processes.
Meta-Regression: A Framework for Robust Reactive Optimization
DEFF Research Database (Denmark)
McClary, Dan; Syrotiuk, Violet R.; Kulahci, Murat
2007-01-01
Maintaining optimal performance as the conditions of a system change is a challenging problem. To solve this problem, we present meta-regression, a general methodology for alleviating traditional difficulties in nonlinear regression modelling. Meta-regression allows for reactive optimization......, in which system components self-organize to changing conditions in a manner that is robust, or affected minimally by other sources of variability. Meta-regression extends profiling, providing a methodology for model-building when there is incomplete knowledge of the mechanisms and interactions...
Are All Lotteries Regressive? Evidence from the Powerball
OSTER, EMILY
2004-01-01
The regressivity of lotteries has become an increasingly important issue in the U.S. as the number of state–run lotteries has increased. Despite this, we still know relatively little about the nature of lottery regressivity. I use a new dataset on Powerball lotto sales to analyze how regressivity varies with jackpot size within a single lotto game. I find that this large–stakes game is significantly less regressive at higher jackpot sizes. Out–of–sample extrapolation of this result suggests t...
Survival after acute hemodialysis in Pennsylvania, 2005-2007: a retrospective cohort study.
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Sarah J Ramer
Full Text Available BACKGROUND: Little is known about acute hemodialysis in the US. Here we describe predictors of receipt of acute hemodialysis in one state and estimate the marginal impact of acute hemodialysis on survival after accounting for confounding due to illness severity. MATERIALS AND METHODS: This is a retrospective cohort study of acute-care hospitalizations in Pennsylvania from October 2005 to December 2007 using data from the Pennsylvania Health Care Cost Containment Council. Exposure variable is acute hemodialysis; dependent variable is survival following acute hemodialysis. We used multivariable logistic regression to determine propensity to receive acute hemodialysis and then, for a Cox proportional hazards model, matched acute hemodialysis and non-acute hemodialysis patients 1∶5 on this propensity. RESULTS: In 2,131,248 admissions of adults without end-stage renal disease, there were 6,657 instances of acute hemodialysis. In analyses adjusted for predicted probability of death upon admission plus other covariates and stratified on age, being male, black, and insured were independent predictors of receipt of acute hemodialysis. One-year post-admission mortality was 43% for those receiving acute hemodialysis, compared to 13% among those not receiving acute hemodialysis. After matching on propensity to receive acute hemodialysis and adjusting for predicted probability of death upon admission, patients who received acute hemodialysis had a higher risk of death than patients who did not over at least 1 year of follow-up (hazard ratio 1·82, 95% confidence interval 1·68-1·97. CONCLUSIONS: In a populous US state, receipt of acute hemodialysis varied by age, sex, race, and insurance status even after adjustment for illness severity. In a comparison of patients with similar propensity to receive acute hemodialysis, those who did receive it were less likely to survive than those who did not. These findings raise questions about reasons for lack of
Mixed phenotype acute leukemia
Institute of Scientific and Technical Information of China (English)
Ye Zixing; Wang Shujie
2014-01-01
Objective To highlight the current understanding of mixed phenotype acute leukemia (MPAL).Data sources We collected the relevant articles in PubMed (from 1985 to present),using the terms "mixed phenotype acute leukemia","hybrid acute leukemia","biphenotypic acute leukemia",and "mixed lineage leukemia".We also collected the relevant studies in WanFang Data base (from 2000 to present),using the terms "mixed phenotype acute leukemia" and "hybrid acute leukemia".Study selection We included all relevant studies concerning mixed phenotype acute leukemia in English and Chinese version,with no limitation of research design.The duplicated articles are excluded.Results MPAL is a rare subgroup of acute leukemia which expresses the myeloid and lymphoid markers simultaneously.The clinical manifestations of MPAL are similar to other acute leukemias.The World Health Organization classification and the European Group for Immunological classification of Leukaemias 1998 cdteria are most widely used.MPAL does not have a standard therapy regimen.Its treatment depends mostly on the patient's unique immunophenotypic and cytogenetic features,and also the experience of individual physician.The lack of effective treatment contributes to an undesirable prognosis.Conclusion Our understanding about MPAL is still limited.The diagnostic criteria have not been unified.The treatment of MPAL remains to be investigated.The prognostic factor is largely unclear yet.A better diagnostic cdteria and targeted therapeutics will improve the therapy effect and a subsequently better prognosis.
Institute of Scientific and Technical Information of China (English)
吕书红; 田本淳; 杨廷忠; 陈定湾; 池延花
2010-01-01
Objective To find out the perceived stress in general public during prevalence of severe acute respiratory syndrome (SARS) and its impact on health behavior. Methods A retrospective survey was conducted in Guangzhou, Hangzhou, and Taiyuan according to the epidemic situations of SARS, and 2532 subjects were randomly selected from constructive industry, school, and commercial business and residents in urban and rural areas. The perceive stress was measured by Chinese perceived stress scale (CPSS), and health related behavior during SARS was tested by uniform and self-made questionnaire. EpiData 2. 0 was used for data management and CPSS value was calculated according to answer to 14 questions contained in the scale. Health risk stress among different population group and health related behavior among low, medium and high stress state were analyzed by SPSS 11.5. Results 2424 subjects were involved in the survey. The CPSS value was measured from 0 -49(22.7±6. 8) ,M =24. 0. 39.3% (953/2379) subjects were under the health risk stress. The health related behaviors such as washing hands, opening the window for air, keeping away from others when cough and sneeze,doing exercises etc were reduced with the stress increased. Logistic regression indicated that compared with the persons with the thoughts of nothing serious of SARS,without any dread of SARS,and knowing nothing about prevention of SARS,the perceived stress was significantly related with perceiving of the thread to certain extent (β = 0. 41, Wald χ~2 = 4. 84, P = 0. 03), worrying little about the epidemic (β = 0. 50, Wald χ~2 = 6. 69, P = 0. 01), worrying about it to certain extent (β= 1.39, Wald χ~2 = 48. 59 ,P = 0. 00)and scared so much (β = 1.77, Wald χ~2= 53.59, P = 0. 00), and knowing little about the prevention(β = 0. 74, Wald χ~2 = 4. 48, P = 0. 03), knowing something about prevention (β = - 0. 98, Wald χ~2 = 8. 29, P = 0. 00) and knowing the prevention very well (β = - 1.18, Wald χ~2 = 10. 66
Regression calibration with more surrogates than mismeasured variables
Kipnis, Victor
2012-06-29
In a recent paper (Weller EA, Milton DK, Eisen EA, Spiegelman D. Regression calibration for logistic regression with multiple surrogates for one exposure. Journal of Statistical Planning and Inference 2007; 137: 449-461), the authors discussed fitting logistic regression models when a scalar main explanatory variable is measured with error by several surrogates, that is, a situation with more surrogates than variables measured with error. They compared two methods of adjusting for measurement error using a regression calibration approximate model as if it were exact. One is the standard regression calibration approach consisting of substituting an estimated conditional expectation of the true covariate given observed data in the logistic regression. The other is a novel two-stage approach when the logistic regression is fitted to multiple surrogates, and then a linear combination of estimated slopes is formed as the estimate of interest. Applying estimated asymptotic variances for both methods in a single data set with some sensitivity analysis, the authors asserted superiority of their two-stage approach. We investigate this claim in some detail. A troubling aspect of the proposed two-stage method is that, unlike standard regression calibration and a natural form of maximum likelihood, the resulting estimates are not invariant to reparameterization of nuisance parameters in the model. We show, however, that, under the regression calibration approximation, the two-stage method is asymptotically equivalent to a maximum likelihood formulation, and is therefore in theory superior to standard regression calibration. However, our extensive finite-sample simulations in the practically important parameter space where the regression calibration model provides a good approximation failed to uncover such superiority of the two-stage method. We also discuss extensions to different data structures.
Directory of Open Access Journals (Sweden)
Horst Entorf
2015-07-01
Full Text Available Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the magnitude of the link between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we use quantile regressions applied to German district panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature, quantile regression reveals that size and importance of the relationship are conditional on the crime rate. The partial effect is significantly positive for moderately low and median quantiles of local assault rates.
Acute rhabdomyolysis following synthetic cannabinoid ingestion
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Demilade A Adedinsewo
2016-01-01
Full Text Available Context: Novel psychoactive substances, including synthetic cannabinoids, are becoming increasingly popular, with more patients being seen in the emergency room following acute ingestion. These substances have been associated with a wide range of adverse effects. However, identification of complications, clinical toxicity, and management remain challenging. Case Report: We present the case of a young African-American male who developed severe agitation and bizarre behavior following acute K2 ingestion. Laboratory studies revealed markedly elevated serum creatine phosphokinase (CPK with normal renal function. The patient was managed with aggressive intravenous (IV fluid hydration and treatment of underlying psychiatric illness. Conclusion: We recommend the routine evaluation of renal function and CPK levels with early initiation of IV hydration among patients who present to the emergency department following acute ingestion of synthetic cannabinoids to identify potential complications early as well as institute early supportive therapy.
An Effect Size for Regression Predictors in Meta-Analysis
Aloe, Ariel M.; Becker, Betsy Jane
2012-01-01
A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…
General Nature of Multicollinearity in Multiple Regression Analysis.
Liu, Richard
1981-01-01
Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)
Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications
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Guoqi Qian
2016-01-01
Full Text Available Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method.
About regression-kriging: from equations to case studies
Hengl, T.; Heuvelink, G.B.M.; Rossiter, D.G.
2007-01-01
This paper discusses the characteristics of regression-kriging (RK), its strengths and limitations, and illustrates these with a simple example and three case studies. RK is a spatial interpolation technique that combines a regression of the dependent variable on auxiliary variables (such as land su