Interval Regression Analysis Research Articles

INTERVAL MODEL FOR ASSESSING THE PURITY OF NUCLEAR STRUCTURAL METALS BY MICROHARDNESS

The article considers the possibilities of evaluating the purity of Zr-1%Nb zirconium alloy samples – the main structural material of the thermal neutron reactors active zones with a water coolant – according to the microhardness of the metal. The correctness of the application of interval regression analysis is shown, if there is uncertainty, incompleteness of information, measurement errors in the experimental data for determining the oxygen content in metal samples and its microhardness. The method of estimating parameters of interval linear regression is presented.

Establishing cost-effectiveness threshold in China: a community survey of willingness to pay for a healthy life year

IntroductionThe willingness to pay per quality-adjusted life year gained (WTP/Q) is commonly used to determine whether an intervention is cost-effective in health technology assessment. This study aimed to evaluate the...

Open defecation among adults having household toilets and factors associated with it: An analytical cross-sectional study from rural Bihar, India

BackgroundBihar is one of the focus states under Swachh Bharat Mission (SBM) in India. A study was conducted to estimate the prevalence and to determine the factors associated with the practice of open defecation among adults having household toilets, in rural Patna, Bihar. MethodsAn analytical cluster cross-sectional study was conducted for a duration of one year among 609 participants using cluster sampling in rural block of Patna. The prevalence was calculated with 95 % confidence interval and binary logistic regression analysis was done to determine factors associated with open defecation. ResultsOut of 609, 391(64.2 %, 95 % CI: 60–68 %) were practising open defecation despite having a household toilet. Male gender (AOR, 1.684; 95 % CI, 1.1–2.4), scheduled caste community (AOR, 2.168; 95 % CI, 1.3–3.4), family gross monthly income Rs. <7770 (AOR, 2.838; 95 % CI, 1.6–4.8), age of initiating toilet uses at age >35 years (AOR,1.453; 95%CI, 1.0–2.0), absence of government supply as water source (AOR: 2.106, 95 % CI: 1.088–3.410) were the independent factors associated with practice of open defecation. ConclusionsNearly two-third of adults were practising OD despite having a household toilet. Male gender, schedule caste community, family gross monthly income Rs. <7770, age of initiating toilet uses at age >35 years, lack of government supply as water source were the factors associated with the practice ofOD.

Consumers’ Preferences and Willingness to Pay (WTP) for Traceable Liquid Milk: A Survey in Dhaka, Bangladesh

ABSTRACT Consumers’ concerns about food safety have recently escalated in many developing nations as a result of repeated food safety incidents. Many countries, including Bangladesh, are trying to introduce more stringent food safety control measures such as food traceability. However, not much is known about the preferences of Bangladeshi consumers for food traceability, including whether they are willing to pay for traceable foods. This study attempts to fill this gap by evaluating factors that may influence consumers’ preferences and WTP for traceable liquid milk. Based on survey data obtained from 384 consumers in Dhaka in 2021, our results indicate that consumers are ready to pay almost 12% price premium for traceable liquid milk than for non-traceable liquid milk. Interval regression analysis reveals that international third-party certification, branding, price, information on contaminants, income, and milk consumption are important factors in determining consumers’ WTP for traceable liquid milk.

Abstract P2-03-11: Differential Long-Term Benefit from Adjuvant Tamoxifen Therapy in Estrogen Receptor (ER)-Positive/Human Epidermal Growth Factor Receptor 2 (HER2)-Negative Premenopausal and Postmenopausal Breast Cancer Patients

Abstract Background: Tamoxifen is a standard endocrine therapy for both pre- and postmenopausal ER-positive breast cancer patients. Patients with ER-positive disease have a long-term risk of distant recurrence, thus, long-term follow-up studies are essential to understand true treatment benefit. Clinically used tumor characteristics are prognostic 5-10 years after primary diagnosis, however, whether these characteristics are predictive of long-term tamoxifen benefit is largely unexplored. Therefore, we aimed to determine the long-term tamoxifen therapy benefit by the clinically used tumor characteristics in pre- vs postmenopausal patients in the Stockholm tamoxifen (STO)-trials with 20-years complete follow-up. Methods: Secondary analysis of 1242 ER-positive/HER2-negative patients from the STO-trials, randomized to at least 2 years of 40 mg tamoxifen vs no endocrine therapy (control). Premenopausal lymph node-positive patients were allocated to chemotherapy as standard of care and postmenopausal high-risk patients were further randomized to chemotherapy vs radiotherapy. Tumor immunohistochemical analysis was recently conducted. Complete 20-year follow-up was obtained from Swedish high-quality registries. Long-term distant recurrence-free interval (DRFI) was assessed by multivariable Cox proportional hazard regression and time-varying analysis using flexible parametric modelling. Results: Premenopausal patients showed significantly improved long-term DRFI from tamoxifen vs control if they were lymph node-negative (Hazard Ratio [HR]=0.46; 95% CI, 0.24-0.87), PR-positive (HR=0.61; 95% CI, 0.41-0.91), or of genomic low risk (HR=0.47; 95% CI, 0.26-0.85), see Table. In postmenopausal patients, significantly improved long-term DRFI from tamoxifen vs control was seen for all good prognosis tumor characteristics, i.e. small tumor size (pT≤20mm: HR=0.55; 95% CI, 0.39-0.77), tumor grade 1-2 (HR=0.55; 95% CI, 0.41-0.73), lymph node-negative (HR=0.44; 95% CI, 0.30-0.64), PR-positive (HR=0.60; 95% CI, 0.44-0.80), Ki-67-low (&amp;lt; 15%: HR=0.51; 95% CI, 0.38-0.68), and genomic low risk (HR=0.53; 95% CI, 0.37-0.74), see Table. Also, postmenopausal patients with large tumor size (pT&amp;gt;20mm: HR=0.64; 95% CI, 0.44-0.94) and PR-negative tumors (HR=0.51; 95% CI, 0.32-0.81) showed significant long-term tamoxifen benefit. Time-varying analysis in premenopausal patients indicated that tamoxifen therapy benefit diminished over time. Significant tamoxifen benefit until year 5, 10, and 15 after primary diagnosis was observed for PR-positive, lymph node-negative, and genomic low-risk patients, respectively. Postmenopausal patients had a significant long-term tamoxifen benefit if they had tumors of small or large tumor size, tumor grade 1-2, lymph node-negative status, PR-positive status, low Ki-67 levels, or genomic low risk. Conclusions: This study suggests a differential long-term tamoxifen therapy benefit in pre- vs postmenopausal patients. Clinically defined low-risk postmenopausal patients have long-term tamoxifen benefit, whereas the benefit is absent or diminish over time for premenopausal patients. Improved long-term prognostic and endocrine therapy predictive markers in premenopausal breast cancer patients with poor prognosis and long life-expectancy is needed, which could involve molecular tools. Long-term tamoxifen benefit in premenopausal and postmenopausal breast cancer patients by the clinically used tumor characteristics. Table Multivariable Cox proportional hazard regression analysis of 20-year distant recurrence-free interval (DRFI) for patients with ER-positive/HER2-negative tumors, comparing patients randomized to tamoxifen vs patients randomized to no endocrine therapy (control). Adjusted for age, randomization year, tumor size, tumor grade, lymph node status, PR status, Ki-67 status, chemotherapy, radiotherapy, and type of surgery. Citation Format: Annelie Johansson, Huma Dar, Anna Nordenskjöld, Gizeh Perez-Tenorio, Christina Yau, Christopher C. Benz, Laura J. Esserman, Laura Van’t Veer, Bo Nordenskjöld, Olle Stål, Tommy Fornander, Linda S. Lindström. Differential Long-Term Benefit from Adjuvant Tamoxifen Therapy in Estrogen Receptor (ER)-Positive/Human Epidermal Growth Factor Receptor 2 (HER2)-Negative Premenopausal and Postmenopausal Breast Cancer Patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-03-11.

Public Willingness to Pay for Green Lifestyle in China: A Contingent Valuation Method Based on Integrated Model.

The purpose of this study was to note how people recognize the green lifestyle and how much extra money they are willing to pay for it. An integrated model based on the theory of planned behavior was constructed, and data on the willingness to pay (WTP) for green lifestyles of 1377 respondents in five cities in East China were measured and calculated using the double-bounded dichotomous choice contingent valuation method (DBDC) combined with interval regression analysis. The results showed that the respondents were willing to pay an extra 81.8 yuan, 52.5 yuan, 38.9 yuan, 53.2 yuan, and 37.2 yuan per month for green food, clothing, travel, housing, and waste recycling, respectively. Attitude and moral norms were the strongest predictors of WTP for green clothing, travel, housing, and waste recycling. Perceived behavior control, environmental awareness, personal habits, subjective knowledge, gender, income, and education can affect a few kinds of green lifestyle's WTP.

Quick Sequential Organ Failure Assessment Score, Lactate, and Neutrophil-Lymphocyte Ratio Help in Diagnosis and Mortality Prediction during Golden Hour of Sepsis in Emergency Department.

Sepsis is a life-threatening condition with a very narrow golden period in which confirmatory diagnosis may change the outcome dramatically. No confirmatory biomarker is available till date for early diagnosis of sepsis. This study aimed to evaluate the combined and independent role of quick sequential organ failure assessment (qSOFA) score, lactate, and neutrophil-lymphocyte ratio (NLR) in diagnosis and mortality prediction in early sepsis. This was a hospital-based, single-center, prospective cohort study conducted in a tertiary care institute, Karnataka, India. Three hundred adult sepsis patients were recruited during 10-month period, and demographic data, qSOFA score, lactate, NLR, and culture samples were collected in ED within 1 h of admission. Outcome groups (survivor and nonsurvivor) were statistically analyzed with relative frequencies (%), median, mean ± standard deviation with 95% confidence interval (CI), univariate, bivariate, and multivariate logistic regression analysis, and Receiver -operating characteristic curve (ROC) curve to test the predictive ability of initial levels of three biomarkers. Sepsis was more prevalent among middle-aged male patients. Male gender (odds ratio [OR], 6.9; 95% CI: 1.61-30.1), qSOFA (OR, 154; 95% CI: 15-1565), and lactate (OR, 1.36; 95% CI: 22-833) show 97% (area under the curve) predictive accuracy of the model for sepsis on bivariate and multivariate logistic regression analysis. A significant rise in NLR was a poor outcome indicator on univariate analysis (P = 0.773). All three biomarkers are good outcome predictors whereas qSOFA and lactate have diagnostic significance in early sepsis. These markers can be used for patient triaging, minimizing culture report dependence for treatment and ultimately the outcome.

Factors Associated with The Incidence of Coronary Heart Disease in The Mashad: A Cohort Study

Introduction: Coronary heart disease (CHD) is the leading cause of morbidity and mortality globally, and specially in Iran. An accurate assessment of the incidence of coronary heart disease (CHD) is very important for public health. In current study we aimed to investigate the incidence of CHD and importance of several classical modifiable and un-modifiable risk factors for CHD among an urban population in eastern Iran after 6 years follow-up.&#x0D; Methods: The population of MASHAD cohort study were followed up for 6 years, every 3 years initially by phone and those who reported symptoms of cardiovascular disease (CVD) were asked to attend for a cardiac examination. An estimate of the incidence of CHD was determined with 95% confidence interval (95% CI) and multiple logistic regression analysis was performed to assess the association of several baseline characteristics with the incidence of a CHD event. Evaluation of goodness-of-fit was undertaken using ROC analysis. CHD cases were divided into four different categories: stable angina, unstable angina pectoris, myocardial infarction and sudden cardiac death.&#x0D; Results: In the six years of follow-up of the Mashhad study participants, the incidence density of CHD events in men and women in 1000 person-year with 95% confidence intervals were 19.20 (8.10-30.30) and 11.60 (7.30-15.90), respectively. The areas under ROC curve (AUC), based on multiple logistic regression model of CHD outcome, was determined to be 0.783.&#x0D; Conclusion: Our findings indicated that the incidence rate of coronary heart diseases in MASHAD cohort study increases with age, and our final model was able to predict approximately 78% of CHD events in this Iranian population.

Nonlinear interval regression analysis with neural networks and grey prediction for energy demand forecasting

Nonlinear interval regression analysis with neural networks and grey prediction for energy demand forecasting

Knowledge, attitude, and practice of Bangladeshi residents during COVID-19 pandemic.

Bangladeshi government has adopted some special steps to control the quick spread of the COVID-19 pandemic situation. However, the residents' knowledge, attitudes, and practices towards the disease directly impact the success of the controlling measures taken by the state. This article explores knowledge (K) about preventions, attitude (A) to the disease, and practices (P) of preventing the COVID-19 infection risks of different age groups residing in Bangladesh. Quantitative data were collected online using a KAP questionnaire from 932 participants. Also, statistical t and F tests have been used and analyzed and p-value, 95% Confidence Interval, Odd Ratio (OR), KAP scores, and multiple logistic regression analysis, are presented in this research. Results show the population is generally aware of the symptoms and social distancing. They are concerned about re-spreading and positive about staying home. The most significant findings of the study reveal that the old age group (age 50 or over) is the most alert group, male population are the most vulnerable with less care, people living outside Dhaka take less care and fewer preventive measures against the deadly virus, the young age group (age 18-25) is most optimistic while the female respondent group is best prepared among all the participants.

A credibility-based interval multi-objective crop area planning model for agricultural and ecological management

This study presents a credibility-based interval multi-objective crop area planning model for agricultural and ecological management under uncertainty. The model is developed through the integrations of interval multi-objective programming and fuzzy credibility-constrained programming by considering economic and ecological benefits of the study system, and dealing with interval and fuzzy uncertainties. It focuses on crop area optimization with the interval objective function of maximizing the system benefits, maximizing the watershed area, and fractional interval objective function of maximizing the land productivity (i.e., system benefits per unit area). Additionally, the relationship between watershed area and ecological discharge is expressed as interval linear function, which is estimated by using interval regression analysis method. Then, the model is applied to a case study in Minqin County in the lower reaches of Shiyang River Basin for crop area optimization in view of the increasing shortage of water resources and the competition between agricultural and ecological water use. Optimal solutions for different scenarios can be generated based on fuzzy credibility constraints when the predefined credibility levels are set as 0.6, 0.7 and 0.8, 0.9, respectively. The results show that the crop area optimization model can better balance the regional agricultural and ecological benefits while ensuring grain production and promoting water saving. Moreover, a higher level of credibility corresponds to a lower system benefit but a larger watershed area. When credibility level is raised from 0.6 to 0.9, the upper bounds of system benefits are decreased from 13.87×108 Yuan to 13.81×108 Yuan whereas the watershed area is increased from 41.01 km2 to 42.12 km2. These various optimal results can help decision makers weigh system benefits and constraint-violation risks. Therefore, the results of the model can provide decision-making basis for the crop area optimization and provide valuable basis for the sustainable development in Minqin County and similar study areas.

An interval regression analysis of Japanese consumer’s preference for cosmetic argan oil

An interval regression analysis of Japanese consumer’s preference for cosmetic argan oil

Interval regression analysis of the Japanese consumer’s preference for cosmetic argan oil

Interval regression analysis of the Japanese consumer’s preference for cosmetic argan oil

Demand forecasting of green metal materials using non-equidistant grey prediction with robust nonlinear interval regression analysis.

The main advantages of magnesium alloys are that they are lightweight, easy to recycle, and have high vibration absorption. These unique characteristics make magnesium alloys important green metal materials for manufacturing, especially for the automotive and 3C products industries. The developing trends of these related industries can be recognized by forecasting the demand for magnesium alloys. This study develops grey prediction power models to forecast the demand for such a promising green metal material. Grey prediction is an appropriate technique because available data regarding the demand for magnesium alloys are not in line with any statistical assumptions. In particular, because outliers might cause a deterioration of forecasting performance, a robust nonlinear interval regression analysis with neural networks is applied to detect outliers by estimating data intervals. Then, a power model is applied to the newly generated non-equidistant data sequence without outliers. Residual modification is further considered here to improve the forecasting performance of the power model. The forecasting abilities of the proposed grey residual modification models are verified using actual magnesium alloy demand data. The experimental results for ex-post testing show that the mean absolute percentage errors of the proposed models that can work on non-equidistant data were minimal among all considered models.

Integrating Nonlinear Interval Regression Analysis with a Remnant Grey Prediction Model for Energy Demand Forecasting

ABSTRACT Energy demand forecasting is increasingly important for developing national energy policies. This study aims to apply the first order gray model with one variable (GM(1,1)) without following any statistical assumptions to energy demand forecasting. To boost the forecasting accuracy of GM(1,1), a problem arising from collected samples that are often derived from an uncertain assessment should be addressed. One way to deal with these uncertain and imprecise observations is by using nonlinear interval regression analysis with neural networks to generate upper and lower limits for individual samples. As a result, a nonlinear interval gray prediction model is constructed by applying the sequences of upper and lower limits to construct GM(1,1) with residual modification separately. By examining the forecasting performance of a nonlinear interval model by the best non-fuzzy performance values, the empirical results obtained based on real energy demand data show that the proposed models perform well compared with other interval gray prediction models. This study has shown the high applicability of the proposed model to energy demand forecasting.

Risk factors for polyetheretherketone cage subsidence following minimally invasive transforaminal lumbar interbody fusion.

Interbody cage subsidence is a postoperative complication leading to poor outcomes after minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF). This study aimed to identify risk factors of cage subsidence in lumbar spinal diseases after MIS-TLIF using polyetheretherketone (PEEK) cage. In this retrospective cohort study, plain radiographs and three-dimensional computed tomography (3D-CT) performed 12months after MIS-TLIF were evaluated, and the risk of cage subsidence was calculated with odds ratio (OR), confidence interval (CI), and logistic regression analysis. A total of 114 patients (mean age, 65years) and 135 levels were included in this study: 80 (59.3%) with and 55 (40.7%) without cage subsidence. Multifidus atrophy showed the strongest association with PEEK cage subsidence (p < 0.001). Compared to those with normal mass, the odds of PEEK cage subsidence were 76.0 (95% CI: 3.9-1472.9) for severe atrophy. The factors significantly associated with cage subsistence were posterior cage position (OR = 4.2; p = 0.005), cage height ≥ 12mm (OR = 7.6; p = 0.008), use of an autograft mixed with demineralized bone matrix (DBM) (OR = 5.8; p = 0.002), body mass index (BMI) > 27.5kg/m2 (OR = 4.2; p = 0.03), and titanium-coated PEEK (Ti-PEEK) cage-type (OR = 38.4, p = 0.02). In MIS-TLIF with a PEEK cage, the factors associated with an increased risk of cage subsidence were higher BMI, increased severity of multifidus muscle atrophy, Ti-coated PEEK cage-type, cage height ≥ 12mm, use of DBM mixed autograft, and posterior cage position.

134 Estimating the capacity of horse owners to absorb the surplus of wild horses

In FY2019, the Bureau of Land Management (BLM) adopted or sold 8,548 wild horses and burros, but the remaining population still exceeded the appropriate management level by over 61,000 animals. In early 2019, BLM's acting head indicated that a key step in controlling the overpopulation of wild horses on federal lands is increasing private adoptions. Assuming that current or former horse owners represent the most feasible outlet, this paper explored the capacity of this population to absorb the surplus. We pursued this objective by utilizing social media to distribute a nationwide online survey of current and former horse owners. First, we asked whether respondents had adopted (or considered adopting) a wild horse before, whether they might consider it in the future, or whether they would never consider it. We then inquired about reasons for and barriers to adopting. All respondents except those in the last group were asked to report their willingness-to-pay (WTP) for wild horses with different levels of handling and training using a stated preference approach called the payment card method. With 2,247 complete responses, 2,041 respondents (90.8%) reported having adopted, considered adopting, or would consider adopting a wild horse in the future. The most commonly identified reason for having adopted previously was to provide a wild horse with a better life (n = 311, 63.7%), while the primary barrier to adopting was having appropriate facilities (n = 558, 52.2%). Interval regression analysis was utilized to estimate WTP for wild horses with 3 different levels of training: entirely unhandled, trained with basic ground manners, and started under saddle. Across the 3 models, preliminary results suggest that WTP for wild horses is consistently influenced by whether the respondent has adopted previously (+), years of experience with horses (+), age (-), and income (+) ( P < 0.05). Moreover, training before adoption positively influences WTP. For the average respondent, our results suggest that respondents are willing to pay an average of $282.03 more for a horse that has received training for basic ground manners and $539.21 more for a horse that has been started under saddle as compared with a completely unhandled horse. Within our sample, results indicate an overall positive perception of the private adoption of wild horses; if the main barriers to adoption can be overcome (lack of appropriate facilities and time/expertise to safely train an undomesticated horse), our results suggest general feasibility of the BLM's plan to solve, or at least significantly alleviate, the overpopulation of wild horses through private placement.

Farmers' willingness to pay for foot and mouth disease vaccine in different cattle production systems in Amhara region of Ethiopia.

Although foot and mouth disease (FMD) is endemic in Ethiopia, use of vaccines to control the disease has been practiced sparingly. This is due to perceived high cost of good quality FMD vaccine, and consequently limited availability of the vaccine in the market. This study was conducted to assess farmers' willingness to pay (WTP) for a quality FMD vaccine and identify factors that could potentially influence their WTP in Amhara region of Ethiopia. A total of 398 farmers from four districts that represent the mixed crop-livestock and market oriented production systems were enrolled for the study. The WTP was estimated using contingent valuation method with a double-bound dichotomous choice bid design. Interval regression analysis was used to estimate mean WTP and identify factors that influence it. The results showed that the mean WTP of all farmers was Ethiopian Birr (ETB) 58.23 (95% CI: 56.20-60.26)/annual dose. It was ETB 75.23 (95% CI: 72. 97-74.49) for market oriented farmers and ETB 42.6 (95%CI: 41.24-43.96) for mixed crop livestock farmers. Willingness to pay for the vaccine was significantly higher for farmers in market oriented system than in mixed crop livestock system. It was also significantly higher for farmers whose main livelihood is livestock than those whose main livelihood is other than livestock, and for farmers who keep exotic breed cattle and their crosses than those who keep only local cattle breeds. Willingness to pay significantly increased with increase in FMD impact perception and vaccine knowledge scores of farmers. The high mean WTP estimates showed that farmers are enthusiastic about using the FMD vaccine. Market-oriented farmers with higher willingness to pay may be more likely to pay full cost if official FMD vaccination is planned in the country than mixed crop livestock farmers. Animal health extension about livestock diseases impact and vaccines has a potential to increase farmers' uptake of vaccines for disease control.

Interval regression models of a machine-building enterprise

The article discusses methods of interval regression analysis and their application in modeling. The object of the study was the reporting of the engineering company LLC Spetsstroymash (in a sixteen-year period). The results obtained are compared with traditional regression analogs such as the least squares method and the least modulus method.

Interval Grey Prediction Models with Forecast Combination for Energy Demand Forecasting

Time series data for decision problems such as energy demand forecasting are often derived from uncertain assessments, and do not meet any statistical assumptions. The interval grey number becomes an appropriate representation for an uncertain and imprecise observation. In order to obtain nonlinear interval grey numbers with better forecasting accuracy, this study proposes a combined model by fusing interval grey numbers estimated by neural networks (NNs) and the grey prediction models. The proposed model first uses interval regression analysis using NNs to estimate interval grey numbers for a real valued sequence; and then a grey residual modification model is constructed using the upper and lower wrapping sequences obtained by NNs. It turns out that two different kinds of interval grey numbers can be estimated by nonlinear interval regression analysis. Forecasting accuracy on real data sequences was then examined by the best non-fuzzy performance values of the combined model. The proposed combined model performed well compared with the other interval grey prediction models considered.