Assessment of factors that affect the bankruptcy of an organization

Analysis of factors that influence the company's bankruptcy is one of the main tasks for companies that want to assess their financial situation and prevent possible bankruptcy in a timely manner. This article analyzes the factors that affect the company's bankruptcy. A logistic regression model was constructed based on the indicators of both bankrupt and financially stable companies. During the development of the model, significant factors were identified for predicting the bankruptcy of the organization. The results will be useful both for future bankruptcy researchers and for those companies that want to assess their financial situation.

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Developing a Multi-variate Logistic Regression Model to Analyze Accident Scenarios: Case of Electrical Contractors

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17134852 ◽

2020 ◽

Vol 17 (13) ◽

pp. 4852

Author(s):

Pouya Gholizadeh ◽

Behzad Esmaeili

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Odds Ratio ◽

Logistic Regression Model ◽

The Body ◽

Occupational Accidents ◽

Multivariate Logistic Regression Model ◽

Ratio Analysis ◽

Accident Scenarios ◽

Significant Factors

The ability to identify factors that influence serious injuries and fatalities would help construction firms triage hazardous situations and direct their resources towards more effective interventions. Therefore, this study used odds ratio analysis and logistic regression modeling on historical accident data to investigate the contributing factors impacting occupational accidents among small electrical contracting enterprises. After conducting a thorough content analysis to ensure the reliability of reports, the authors adopted a purposeful variable selection approach to determine the most significant factors that can explain the fatality rates in different scenarios. Thereafter, this study performed an odds ratio analysis among significant factors to determine which factors increase the likelihood of fatality. For example, it was found that having a fatal accident is 4.4 times more likely when the source is a “vehicle” than when it is a “tool, instrument, or equipment”. After validating the consistency of the model, 105 accident scenarios were developed and assessed using the model. The findings revealed which severe accident scenarios happen commonly to people in this trade, with nine scenarios having fatality rates of 50% or more. The highest fatality rates occurred in “fencing, installing lights, signs, etc.” tasks in “alteration and rehabilitation” projects where the source of injury was “parts and materials”. The proposed analysis/modeling approach can be applied among all specialty contracting companies to identify and prioritize more hazardous situations within specific trades. The proposed model-development process also contributes to the body of knowledge around accident analysis by providing a framework for analyzing accident reports through a multivariate logistic regression model.

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Revised Injury Severity Classification II (RISC II) is a predictor of mortality in REBOA-managed severe trauma patients

PLoS ONE ◽

10.1371/journal.pone.0246127 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0246127

Author(s):

Peter Hibert-Carius ◽

David T. McGreevy ◽

Fikri M. Abu-Zidan ◽

Tal M. Hörer ◽

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Predictive Value ◽

Logistic Regression Model ◽

Injury Severity ◽

Univariate Analysis ◽

Severe Trauma ◽

Trauma Patients ◽

Revised Injury Severity Classification ◽

Significant Factors

The evidence supporting the use of Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) in severely injured patients is still debatable. Using the ABOTrauma Registry, we aimed to define factors affecting mortality in trauma REBOA patients. Data from the ABOTrauma Registry collected between 2014 and 2020 from 22 centers in 13 countries globally were analysed. Of 189 patients, 93 died (49%) and 96 survived (51%). The demographic, clinical, REBOA criteria, and laboratory variables of these two groups were compared using non-parametric methods. Significant factors were then entered into a backward logistic regression model. The univariate analysis showed numerous significant factors that predicted death including mechanism of injury, ongoing cardiopulmonary resuscitation, GCS, dilated pupils, systolic blood pressure, SPO2, ISS, serum lactate level and Revised Injury Severity Classification (RISCII). RISCII was the only significant factor in the backward logistic regression model (p < 0.0001). The odds of survival increased by 4% for each increase of 1% in the RISCII. The best RISCII that predicted 30-day survival in the REBOA treated patients was 53.7%, having a sensitivity of 82.3%, specificity of 64.5%, positive predictive value of 70.5%, negative predictive value of 77.9%, and usefulness index of 0.385. Although there are multiple significant factors shown in the univariate analysis, the only factor that predicted 30-day mortality in REBOA trauma patients in a logistic regression model was RISCII. Our results clearly demonstrate that single variables may not do well in predicting mortality in severe trauma patients and that a complex score such as the RISC II is needed. Although a complex score may be useful for benchmarking, its clinical utility can be hindered by its complexity.

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Assessment of factors that affect the company's investment attractiveness

Scientific notes of the Russian academy of entrepreneurship ◽

10.24182/2073-6258-2020-19-2-32-40 ◽

2020 ◽

Vol 19 (2) ◽

pp. 32-40

Author(s):

Irina Vinnikova

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Financial Position ◽

Significant Factors

Analysis of factors that influence investment attractiveness is one of the main tasks for companies that want to assess their financial position and be attractive to investors. This article analyzes the factors that affect the investment attractiveness of the company. A logistic regression model was constructed based on the indicators of both investment-attractive and unattractive companies. During the development of the model, significant factors were identified, and tests were performed on the significance of the resulting model. The results will be useful both for future investors in the organization, and for those companies that want to evaluate their investment attractiveness.

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Drowning of Under 18 Children in Bangladesh: Analysis of Risk Factors Using MICS 2006 Data

Dhaka University Journal of Science ◽

10.3329/dujs.v64i1.28519 ◽

2016 ◽

Vol 64 (1) ◽

pp. 21-24

Author(s):

Farzana Chowdhury ◽

Jahida Gulshan

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Model ◽

Cause Of Death ◽

Logistic Regression Model ◽

Wealth Index ◽

Bivariate Analysis ◽

Prone Area ◽

Flood Prone Area ◽

Significant Factors

In Bangladesh, drowning is the single leading cause of death among children aged 1 to 17 years. With a view of measuring the drowning of under 18 children in Bangladesh, this paper attempts to analyze different factors responsible for drowning by using the MICS 2006 data. Bivariate analysis is employed to examine the factors related to drowning and logistic regression model is used to determine the contribution of different significant factors to drowning. This study found that divisions, residing in flood prone area or riverbank and wealth index have significant association with drowning. Children residing in flood prone area and riverbank have greater risk of drowning as compared to their counterparts.Dhaka Univ. J. Sci. 64(1): 21-24, 2016 (January)

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Diuretic Enhanced Ultrasonography in the Diagnosis of Pyeloureteral Obstruction

Medicina ◽

10.3390/medicina55100670 ◽

2019 ◽

Vol 55 (10) ◽

pp. 670 ◽

Cited By ~ 1

Author(s):

Kazlauskas ◽

Cekuolis ◽

Bilius ◽

Anglickis ◽

Verkauskas

Keyword(s):

Logistic Regression ◽

Renal Function ◽

Regression Model ◽

Renal Pelvis ◽

Logistic Regression Model ◽

Ultrasound Measurement ◽

Additional Investigation ◽

Differential Renal Function ◽

Adjusted Dose ◽

Significant Factors

Background and Objectives: To determine the value of diuretic ultrasonography for the diagnosis of obstructive hydronephrosis. Materials and Methods: Diuretic enhanced ultrasonography was used routinely as a part of examination of patients with hydronephrosis in our Department. There were 72 patients (42 males, 30 females; aged 2 months to 17 years; median age 7.07 years) with a sonoscopic diagnosis of hydronephrosis included from January 2006 until October 2011. The anteroposterior diameter (AD) of renal pelvis was measured sonoscopically before and at sixty minutes after furosemide injection. A weight-adjusted dose of 1 mg/kg of furosemide was administered intravenously. Results: Patients were operated on if pyeloureteral obstruction was suspected because of low or deteriorating differential renal function, increasing hydronephrosis or symptoms thereof. Hydronephrosis was unilateral in 61 (84.7%) and bilateral in 11 (15.3%) patients. The median AD of pelvis before furosemide injection was 22 mm in operated and 17 mm in non-operated patients (p = 0.005). Sixty minutes after furosemide injection, the AD of pelvis in operated patients was 35.5 mm and 25.8 mm in non-operated—25.8 mm (p < 0.001). Logistic regression model demonstrated that significant factors for surgery were: AD 60 minutes after furosemide infection and ultrasonographic parenchymal sclerosis. Conclusion: Ultrasound measurement of the AD of renal pelvis 1 hour after the injection of furosemide used as an additional investigation can help in predicting obstructive hydronephrosis.

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Determinants of Satisfaction and Proper Management of Aged Population in Chapai Nawabgonj District in Bangladesh: Multivariate Approach

Asian Journal of Humanity Art and Literature ◽

10.18034/ajhal.v8i1.538 ◽

2021 ◽

Vol 8 (1) ◽

pp. 9-18

Author(s):

Md. Shamsuzzaman

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Elderly People ◽

Low Income ◽

Living Arrangements ◽

Logistic Regression Model ◽

The Elderly ◽

Aged Population ◽

Proper Management ◽

Significant Factors

Improving the ability of the satisfaction and proper management to reach the aged population is important for health and essential to mitigate the income erosion consequences of ill health in Bangladesh. This study examined the satisfaction and proper management of the elderly of some identified disadvantages of aged populations; including the effect of poverty-focused nongovernmental development interventions. The objective of the study is to determine the more influential factors that are affecting the health status and living arrangements of the elderly. The data were collected by direct interview method from Chapai-Nawabgonj District, Bangladesh. The chi-square test and logistic regression model were used to fulfill the objective of this study. The results of this study reveal that among literate the majority percent aged population has at least primary education and slightly over half of them have secondary level education. The majority of the elderly people are low income, economically dependent, living with married children. Also, they are unhealthy to suffer from different kinds of illnesses like Lame, Gastric, Blood pressure, Paralysis, Diabetics, etc. A large number of people is taking treatment from M.B.B.S, and a small portion of people are taking treatment from Homeopathic and Ayurvedic physician. Despite their suffering, most of them do not get the proper care. Television, Newspaper, monthly income-expenditure, family member, and educational status are associated with the satisfaction of elderly people. The logistic regression model exposed that serious operation and proper management are the most major significant factors effects satisfaction. It also exposed that mental torture, a different shelter for the elderly are major significant factors effects proper management. The paper concludes by emphasizing the importance of enhancing local capacities to determine whether self-treatment is indicated, to investigate socio-economic background, or in cases where satisfaction and proper management is sought, to judge provider competence and evaluate whether basic needs are justified. The provision of pharmaceutical training to the full spectrum of satisfied providers is also recommended.

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