An adjustment degree of fitting on fuzzy linear regression model toward manufacturing income

The regression analysis is a common tool in data analysis, while fuzzy regression can be used to analyze uncertain or imprecise data. Manufacturing companies often having difficulty predicting their future income. Thus, a new approach is required for the prediction of future company income. This article analyzed the manufacturing income by using the multiple linear regression (MLR) model and two fuzzy linear regression (FLR) model proposed by Tanaka and Zolfaghari, respectively. In order to find the optimum of the FLR model, the degree of fitting (H) was adjusted in between 0 to 1. The performance of three models has been measured by using mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). Detailed analysis proved that Zolfaghari’s FLR model with the degree of fitting of 0.025 outperformed the MLR and FLR with Tanaka’s model with the smallest error value. In conclusion, the manufacturing income is directly correlated with six independent variables. Furthermore, three independent variables are inversely related to manufacturing income. Based on the results of this model, it appears to be suitable for predicting future manufacturing income

A time series analysis for sales of chicken based food product

This study provides a time series analysis and interpretation of the output for forecast sales of chicken based food product of weekly sales data. These data were collected directly from the outlet shop of one factory in Malacca started from January 2015 to December 2016. Methods of forecasting include autoregressive (AR) method and simple exponential smoothing (SES) method. The accuracy for both methods will be compared using mean squared error (MSE), mean absolute percentage error (MAPE) and mean absolute deviation (MAD). There will be 1 period ahead of predictions for AR method and 1 period ahead for SES method. This analysis found that AR method with AR (1) model is more accurate than SES method and can be used for the future prediction of chicken based food product of weekly sales data. Recommendations for future study is trying out other method to analyse this sales of chicken based food product and using R software to analyse the dataset

individual participant data meta-analysis of randomised trials study protocol

Introduction Parenteral anticoagulants may improve outcomes in patients with cancer by reducing risk of venous thromboembolic disease and through a direct antitumour effect. Study-level systematic reviews indicate a reduction in venous thromboembolism and provide moderate confidence that a small survival benefit exists. It remains unclear if any patient subgroups experience potential benefits. Methods and analysis First, we will perform a comprehensive systematic search of MEDLINE, EMBASE and The Cochrane Library, hand search scientific conference abstracts and check clinical trials registries for randomised control trials of participants with solid cancers who are administered parenteral anticoagulants. We anticipate identifying at least 15 trials, exceeding 9000 participants. Second, we will perform an individual participant data meta-analysis to explore the magnitude of survival benefit and address whether subgroups of patients are more likely to benefit from parenteral anticoagulants. All analyses will follow the intention-to- treat principle. For our primary outcome, mortality, we will use multivariable hierarchical models with patient-level variables as fixed effects and a categorical trial variable as a random effect. We will adjust analysis for important prognostic characteristics. To investigate whether intervention effects vary by predefined subgroups of patients, we will test interaction terms in the statistical model. Furthermore, we will develop a risk-prediction model for venous thromboembolism, with a focus on control patients of randomised trials. Ethics and dissemination Aside from maintaining participant anonymity, there are no major ethical concerns. This will be the first individual participant data meta-analysis addressing heparin use among patients with cancer and will directly influence recommendations in clinical practice guidelines. Major cancer guideline development organisations will use eventual results to inform their guideline recommendations. Several knowledge users will disseminate results through presentations at clinical rounds as well as national and international conferences. We will prepare an evidence brief and facilitate dialogue to engage policymakers and stakeholders in acting on findings. Trial registration number PROSPERO CRD4201300352

Genetic algorithms for outlier detection in multiple regression with different information criteria

WOS: 000285347900002Outliers are abnormal, aberrant or outlying observations in data and can cause distortion of estimations in statistical models. Identification of outliers is an important process for preventing faulty conclusions in statistical analysis. Simultaneous outlier detection, which genetic algorithms (GA) provide, is more successful than the methods based on detecting outliers one by one when an order of detection is important. In this study, we derived new approaches of information criteria which are based on Akaike's information criterion (AIC) and Bozdogan's information complexity (ICOMP) information criterion and we used them as the fitness function of GAs to detect outliers in multiple regression. Performances of AIC' and ICOMP' that we derived are compared by Bayesian information criterion (BIC'). Simulation results of AIC', BIC' and ICOMP' obtained from different sample sizes, penalized kappa values of information criteria and different numbers of explanatory variables are presented and discussed

Evaluating prophylactic heparin in ambulatory patients with solid tumours: a systematic review and individual participant data meta-analysis

Background Study-level meta-analyses provide high-certainty evidence that heparin reduces the risk of symptomatic venous thromboembolism for patients with cancer; however, whether the benefits and harms associated with heparin differ by cancer type is unclear. This individual participant data meta-analysis of randomised controlled trials examines the effect of heparin on survival, venous thromboembolism, and bleeding in patients with cancer in general and by type.Methods In this systematic review and meta-analysis we searched MEDLINE, Embase, and The Cochrane Library for randomised controlled trials comparing parenteral anticoagulants with placebo or standard care in ambulatory patients with solid tumours and no indication for anticoagulation published from the inception of each database to January 14, 2017, and updated it on May 14, 2020, without language restrictions. We calculated the effect of parenteral anticoagulant administration on all-cause mortality, venous thromboembolism occurrence, and bleeding related outcomes through multivariable hierarchical models with patient-level variables as fixed effects and a categorical trial variable as a random effect, adjusting for age, cancer type, and metastatic status. Interaction terms were tested to investigate effects in predefined subgroups. This study is registered with PROSPERO, CRD42013003526.Findings We obtained individual participant data from 14 of 20 eligible randomised controlled trials (8278 [79%] of 10 431 participants; 4139 included in the low-molecular-weight heparin group and 4139 in the control group). Meta- analysis showed an adjusted relative risk (RR) of mortality at 1 year of 0·99 (95% CI 0·93–1·06) and a hazard ratio of 1·01 (95% CI 0·96–1·07). The number of patients with venous thromboembolic events was 158 (4·0%) of 3958 with available data in the low-molecular-weight heparin group compared with 279 (7·1%) of 3957 in the control group. Major bleeding events occurred in 71 (1·7%) of 4139 patients in the control population and 88 (2·1%) in the low- molecular-weight heparin group, and minor bleeding events in 478 (12·1%) of 3945 patients with available data in the control group and 652 (16·6%) of 3937 patients in the low-molecular-weight heparin group. The adjusted RR was 0·58 (95% CI 0·47–0·71) for venous thromboembolism, 1·27 (0·92–1·74) for major bleeding, and 1·34 (1·19–1·51) for minor bleeding. Prespecified subgroup analysis of venous thromboembolism occurrence by cancer type identified the most certain benefit from heparin treatment in patients with lung cancer (RR 0·59 [95% CI 0·42–0·81]), which dominated the overall reduction in venous thromboembolism. Certainty of the evidence for the outcomes ranged from moderate to high.Interpretation Low-molecular-weight heparin reduces risk of venous thromboembolism without increasing risk of major bleeding compared with placebo or standard care in patients with solid tumours, but it does not improve survival.Funding Canadian Institutes of Health Research

Use of heparins in patients with cancer: Individual participant data metaanalysis of randomised trials study protocol

39sinoneIntroduction: Parenteral anticoagulants may improve outcomes in patients with cancer by reducing risk of venous thromboembolic disease and through a direct antitumour effect. Study-level systematic reviews indicate a reduction in venous thromboembolism and provide moderate confidence that a small survival benefit exists. It remains unclear if any patient subgroups experience potential benefits. Methods and analysis: First, we will perform a comprehensive systematic search of MEDLINE, EMBASE and The Cochrane Library, hand search scientific conference abstracts and check clinical trials registries for randomised control trials of participants with solid cancers who are administered parenteral anticoagulants. We anticipate identifying at least 15 trials, exceeding 9000 participants. Second, we will perform an individual participant data metaanalysis to explore the magnitude of survival benefit and address whether subgroups of patients are more likely to benefit from parenteral anticoagulants. All analyses will follow the intention-to-treat principle. For our primary outcome, mortality, we will use multivariable hierarchical models with patient-level variables as fixed effects and a categorical trial variable as a random effect. We will adjust analysis for important prognostic characteristics. To investigate whether intervention effects vary by predefined subgroups of patients, we will test interaction terms in the statistical model. Furthermore, we will develop a risk-prediction model for venous thromboembolism, with a focus on control patients of randomised trials. Ethics and dissemination: Aside from maintaining participant anonymity, there are no major ethical concerns. This will be the first individual participantdata meta-analysis addressing heparin use among patients with cancer and will directly influence recommendations in clinical practice guidelines. Major cancer guideline development organisations will use eventual results to inform their guideline recommendations. Several knowledge users will disseminate results through presentations at clinical rounds as well as national and international conferences. We will prepare an evidence brief and facilitate dialogue to engage policymakers and stakeholders in acting on findings.noneSchünemann, Holger J; Ventresca, Matthew; Crowther, Mark; Briel, Matthias; Zhou, Qi; Garcia, David; Lyman, Gary; Noble, Simon; Macbeth, Fergus; Griffiths, Gareth; Di Nisio, Marcello; Iorio, Alfonso; Beyene, Joseph; Mbuagbaw, Lawrance; Neumann, Ignacio; Es, Nick Van; Brouwers, Melissa; Brozek, Jan; Guyatt, Gordon; Levine, Mark; Moll, Stephan; Santesso, Nancy; Streiff, Michael; Baldeh, Tejan; Florez, Ivan; Alma, Ozlem Gurunlu; Solh, Ziad; Ageno, Walter; Marcucci, Maura; Bozas, George; Zulian, Gilbert; Maraveyas, Anthony; Lebeau, Bernard; Buller, Harry; Evans, Jessica; Mcbane, Robert; Bleker, Suzanne; Pelzer, Uwe; Akl, Elie ASchünemann, Holger J; Ventresca, Matthew; Crowther, Mark; Briel, Matthias; Zhou, Qi; Garcia, David; Lyman, Gary; Noble, Simon; Macbeth, Fergus; Griffiths, Gareth; Di Nisio, Marcello; Iorio, Alfonso; Beyene, Joseph; Mbuagbaw, Lawrance; Neumann, Ignacio; Es, Nick Van; Brouwers, Melissa; Brozek, Jan; Guyatt, Gordon; Levine, Mark; Moll, Stephan; Santesso, Nancy; Streiff, Michael; Baldeh, Tejan; Florez, Ivan; Alma, Ozlem Gurunlu; Solh, Ziad; Ageno, Walter; Marcucci, Maura; Bozas, George; Zulian, Gilbert; Maraveyas, Anthony; Lebeau, Bernard; Buller, Harry; Evans, Jessica; Mcbane, Robert; Bleker, Suzanne; Pelzer, Uwe; Akl, Elie A

The Khorana score for prediction of venous thromboembolism in cancer patients: An individual patient data meta-analysis

Oncology guidelines suggest using the Khorana score to select ambulatory cancer patients receiving chemotherapy for primary venous thromboembolism (VTE) prevention, but its performance in different cancers remains uncertain