The duration of export trade relations and its influential factors in China's wooden floor

PurposeThis article will select 25 years of subdivided data to perform Kaplan–Meier survival analysis on the export trade relations of Chinese wooden flooring, use discrete-time cloglog models to analyze influencing factors, use logit and probit models to test the robustness, and try to systematically reveal the duration of China's wood flooring export trade and its influencing factors.Design/methodology/approachThis study used Kaplan–Meier survival function estimation method. In the survival analysis, survival function and hazard rate function are often used to characterize the distribution of survival time.FindingsThe continuous average export time of China's wooden flooring is relatively long, about 14 years. China's wooden flooring has a negative time dependency. After the export trade exceeds the threshold value of 15 years, the failure rate of trade greatly decreases, which has a “threshold effect.” Gravity model variables have a significant impact on the duration of China's wooden floor export.Originality/valueStudying the duration of forest products trade is of great significance for clearing deep-level trade relations and promoting sustainable development of forest products trade.

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Survival analysis

Epidemiology with R ◽

10.1093/oso/9780198841326.003.0009 ◽

2020 ◽

pp. 181-218

Author(s):

Bendix Carstensen

Keyword(s):

Survival Analysis ◽

Competing Risks ◽

Cox Model ◽

Survival Function ◽

Event Analysis ◽

Time To Event ◽

Poisson Models ◽

Kaplan Meier ◽

Analysis Survival ◽

Event Rates

This chapter describes survival analysis. Survival analysis concerns data where the outcome is a length of time, namely the time from inclusion in the study (such as diagnosis of some disease) till death or some other event — hence the term 'time to event analysis', which is also used. There are two primary targets normally addressed in survival analysis: survival probabilities and event rates. The chapter then looks at the life table estimator of survival function and the Kaplan–Meier estimator of survival. It also considers the Cox model and its relationship with Poisson models, as well as the Fine–Gray approach to competing risks.

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Survival analysis of renal patients underwent transplantation in Kyrgyz Republic and various countries by 10 years follow-up

Heart Vessels and Transplantation ◽

10.24969/hvt.2019.168 ◽

2019 ◽

Vol 3 (Issue 4) ◽

pp. 243

Author(s):

Zhanybek Gaibyldaev ◽

Zhamalbek Ashimov ◽

Damirbek Abibillaev ◽

Fuat Kocyigit

Keyword(s):

Survival Analysis ◽

Heart Surgery ◽

Cox Regression ◽

Statistical Significance ◽

Survival Function ◽

Strong Impact ◽

Kyrgyz Republic ◽

Cox Regression Analysis ◽

Kaplan Meier

In our study we conducted survival analysis of 204 patients visited Scientific-Research Institute of Heart Surgery and Organs transplantation and who underwent renal transplantation in Kyrgyzstan and other Eurasian countries between 2005 and 2016 years (age range: 9-71 years, mean: 38.21 (12.74) years, median: 34.0 (0.89) years; gender: 142 male (69.6%)). During follow-up period, mortality event was observed in 16 (7.84%) patients. Survival function probabilities of patients and rational risk factors of survival functions were evaluated by Kaplan-Meier and Cox regression analyses, respectively. According to Kaplan-Meier results survival probabilities calculated for 1st year: 0.96 (0.014), for 3rd year: 0.94 (0.018), for 5th year: 0.86 (0.04), for 7th year: 0.75 (0.10). Among age groups 28-39 age ranges prevailed by 11 patients. Nevertheless, that difference did not show statistical significance: p˃0.322. The intensity of transplantation also analyzed according to years, which revealed increasing in numbers of operations by time. For instance, when in 2006 only two cases were registered in our center, but numbers of transplanted patients reached up to 48 in 2015. The association of mortality states and years of transplantation found significantly by Kaplan-Meier test (Breslow p˂0.001). The survival analysis was compared according to countries and revealed significant results (Breslow p˂0.05). From other factors influencing mortality, sex did not show strong impact on survival by Kaplan-Meier analysis, but significant association was found by Cox regression analysis.

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A Study on Survival Scenario of COVID-19 patients in India: An Application of Survival Analysis on patient demographics

10.1101/2020.08.01.20162115 ◽

2020 ◽

Author(s):

Sampurna Kundu ◽

Kirti ◽

Debarghya Mandal

Keyword(s):

Survival Analysis ◽

Disease Transmission ◽

Survival Function ◽

Survival Rates ◽

Age Groups ◽

Central India ◽

Kaplan Meier ◽

First Case ◽

The Government ◽

And Gender

The study of transmission dynamics of COVID-19, have depicted the rate, patterns and predictions of the pandemic cases. In order to combat the disease transmission in India, the Government had declared lockdown on the 25th of March. Even after a strict lockdown nationwide, the cases are increasing and have crossed 4.5 lakh positive cases. A positive point to be noted amongst all that the recovered cases are slowly exceeding the active cases. The survival of the patients, taking death as the event that varies over age groups and gender wise is noteworthy. This study aims in carrying out a survival analysis to establish the variability in survivorship among age groups and sex, at different levels, that is, national, state and district level. The open database of COVID-19 tracker (covid19india.org) of India has been utilized to fulfill the objectives of the study. The study period has been taken from the beginning of the first case which was on 30th Jan 2020 till 30th June. Due to the amount of under-reporting of data and dropping missing columns a total of 26,815 sample patients were considered. The entry point of each patient is different and event of interest is death in the study. Kaplan Meier survival estimation, Cox proportional hazard model and multilevel survival model has been used to perform survival analysis. Kaplan Meier survival function, shows that the probability of survival has been declining during the study period of five months. A significant variability has been observed in the age groups, as evident from all the survival estimates, with increasing age the risk of dying from COVID-19 increases. When Western and Central India show ever decreasing survival rate in the framed time period then Eastern , North Eastern and Southern India shows a slightly better picture in terms of survival. Maharashtra, Gujarat, Delhi, Rajasthan and West bengal showed alrmingly poor survival as well. This study has depicted a grave scenario of gradation of ever decreasing survival rates in various regions and shows the variability by age and gender.

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Survival analysis of supply chain financial risk

The Journal of Risk Finance ◽

10.1108/jrf-11-2015-0112 ◽

2016 ◽

Vol 17 (2) ◽

pp. 130-151 ◽

Cited By ~ 2

Author(s):

Scott Dellana ◽

David West

Keyword(s):

Supply Chain ◽

Survival Analysis ◽

Financial Risk ◽

Proportional Hazards ◽

Risk Mitigation ◽

Survival Function ◽

Cox Proportional Hazards ◽

Multiple Discriminant Analysis ◽

Content Type ◽

Simple Decision Rule

Purpose The purpose of this paper is to apply survival analysis, using Cox proportional hazards regression (CPHR), to the problem of predicting if and when supply chain (SC) customers or suppliers might file a petition for bankruptcy so that proactive steps may be taken to avoid a SC disruption. Design/methodology/approach CPHR is first compared to multiple discriminant analysis (MDA) and logistic regression (LR) to assess its suitability and accuracy to SC applications using three years of financial quarterly data for 69 non-bankrupt and 74 bankrupt organizations. A k-means clustering approach is then applied to the survival curves of all 143 organizations to explore heuristics for predicting the timing of bankruptcy petitions. Findings CPHR makes bankruptcy predictions at least as accurately as MDA and LR. The survival function also provides valuable information on when bankruptcy might occur. This information allows SC members to be prioritized into three groups: financially healthy companies of no immediate risk, companies with imminent risk of bankruptcy and companies with intermediate levels of risk that need monitoring. Originality/value The current paper proposes a new analytical approach to scanning and assessing the financial risk of SC members (suppliers or customers). Traditional models are able to predict if but not when a financial failure will occur. Lacking this information, it is impossible for SC managers to prioritize risk mitigation activities. A simple decision rule is developed to guide SC managers in setting these priorities.

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Survival Analysis Based on Average Response Time of Maritime Search and Rescue (SAR) Incidents in 2019 Using Kaplan-Meier Method and Log-Rank Test

Enthusiastic : International Journal of Applied Statistics and Data Science ◽

10.20885/enthusiastic.vol1.iss1.art2 ◽

2021 ◽

Vol 1 (01) ◽

pp. 7-12

Author(s):

Muhammad Hasan Sidiq Kurniawan ◽

Duhania Oktasya Mahara

Keyword(s):

Survival Analysis ◽

Response Time ◽

Survival Function ◽

Search And Rescue ◽

High Rate ◽

Rank Test ◽

Average Response ◽

Average Response Time ◽

Log Rank Test ◽

Kaplan Meier

Indonesia is the largest archipelagic country in the world (based on area and population), which makes it as one of countries with the most significant maritime activities. Therefore, there has been a high rate of maritime accidents in Indonesia. The National Search and Rescue Agency (BASARNAS) as a non-ministerial government agency with the primary task of Search and Rescue (SAR) operation deals with several types of accidents, including maritime accidents. Response time as the time to receive news about the accidents until the SAR unit comes to the rescue is very crucial in this matter. Average response time is stipulated based on BASARNAS’s regulations to estimate information about the survival probability of the victims. This research concerns with the survival analysis using Kaplan-Meier Method and Log-Rank Test. The researchers categorized maritime accidents into three categories: ‘Low’, ‘Medium’, and ‘High’. This classification aims to find out whether the survival function of each category has the same or different function and to investigate whether there are differences from the given responses or not. The survival analysis with Kaplan-Meier method revealed that the three categories had different survival functions. The survival analysis was followed by a Log-Rank Test. The final result shows that there is no difference in the responses given by the three categories when maritime accidents occur. Received February 10, 2021Revised March 29, 2021Accepted March 29, 2021

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Identifying the influencing factors on the quality of China’s forestry exports

Forestry Economics Review ◽

10.1108/fer-04-2019-0011 ◽

2019 ◽

Vol 1 (1) ◽

pp. 2-16

Author(s):

Baodong Cheng ◽

Sitong Liu ◽

Lichun Xiong ◽

Fengting Wang ◽

Guangyuan Qin ◽

...

Keyword(s):

Influencing Factors ◽

Raw Materials ◽

Forest Products ◽

Developed Countries ◽

Negative Influence ◽

Asia Pacific ◽

Content Type ◽

Positive Effects ◽

Export Quality

Purpose China is not only the biggest importing country of the raw materials of forest products, but also the biggest exporting country of intermediate and final forest products. The paper aims to discuss these issues. Design/methodology/approach The authors use the Khandelwal (2010) method and trade data from 2000 to 2014 of bilateral forest products between China and ten main developed countries to evaluate the quality of China’s forestry imports and exports. Subsequently, the influencing factors of product quality are analyzed. Findings The results show that the current export quality of plywood and fiberboard is decreasing, and the export quality of particleboard and paper products is on the rise. A further study finds that several factors have the positive effects on the quality of forestry exports, including gross domestic product of the importing country, forestry export value of the importing country as well as the number of forestry higher education graduates of the exporting country. Moreover, the study also finds that the status of an Asia-Pacific Economic Cooperation member has a negative effect on the quality of forestry exports, while the distance cost has a negative influence on fiberboard, paper and paperboard. Practical implications The study suggests that China needs to strengthen the research and development investment on forest products, and improve the quality of forest products to promote the trade development of forestry exports. Originality/value The existing literature has not shown much research regarding the quality of China’s forestry exports through econometric analysis. Therefore, the research results provide new perspective about the influencing factors on China’s forestry trade activities.

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Platform ecological circle for cold chain logistics enterprises: the value co-creation analysis

Industrial Management & Data Systems ◽

10.1108/imds-10-2019-0531 ◽

2020 ◽

Vol 120 (4) ◽

pp. 675-691 ◽

Cited By ~ 2

Author(s):

Benhong Peng ◽

Yuanyuan Wang ◽

Sardar Zahid ◽

Guo Wei ◽

Ehsan Elahi

Keyword(s):

Influencing Factors ◽

Resource Sharing ◽

Structural Equation ◽

Dynamic Capabilities ◽

Positive Influence ◽

Cold Chain ◽

Enterprise Performance ◽

Logistics Industry ◽

Content Type ◽

Logistics Enterprises

Purpose The purpose of this paper is to propose a framework of value co-creation in platform ecological circle for cold chain logistics enterprises to guide the transformation and development of cold chain logistics industry. Design/methodology/approach This paper establishes a conceptual framework for the research on the platform ecological circle in cold chain logistics, utilizes a structural equation model to investigate the influencing factors of the value co-creation of the platform ecological circle in the cold chain logistics enterprises and elaborates the internal relations between different influencing factors regarding the value co-creation and enterprises’ performance. Findings Results show that resource sharing in logistics platform ecological circle can stimulate the interaction among enterprises and this produces a positive influence on their dynamic capabilities, which, in turn, affects the they to work together to plan, implement and solve problems, so as to achieve the goal of improving enterprise performance. Practical implications The shared resources and value co-creation activities in the platform ecological circle are very important for the transformation and development of cold chain logistics enterprises. Therefore, enterprises should promote value co-creation through realizing resource sharing and creating a win-win cooperation mechanism. Originality/value This paper targets at incorporating the resource sharing in platform ecological circle for cold chain logistics enterprises, explores from an empirical perspective the role of the resource sharing in cold chain logistics enterprises in enhancing the dynamic capabilities of enterprises, thereby encouraging the value co-creation behavior, and ultimately boosts enterprise performance and stimulates business development.

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A85 THE CLINICAL IMPACT OF COVID-19 DELAYS ON PLASTIC BILIARY STENT REMOVAL IN NOVA SCOTIA

Journal of the Canadian Association of Gastroenterology ◽

10.1093/jcag/gwab002.083 ◽

2021 ◽

Vol 4 (Supplement_1) ◽

pp. 54-56

Author(s):

D R Lim ◽

M Tsai ◽

S E Gruchy ◽

J Jones ◽

G Williams ◽

...

Keyword(s):

Survival Analysis ◽

Nova Scotia ◽

Stent Placement ◽

Biliary Stent ◽

Biliary Stents ◽

Stent Occlusion ◽

Stent Removal ◽

Kaplan Meier ◽

And Migration

Abstract Background The COVID-2019 pandemic continues to restrict access to endoscopy, resulting in delays or cancellation of non-urgent endoscopic procedures. A delay in the removal or exchange of plastic biliary stents may lead to stent occlusion with consensus recommendation of stent removal or exchange at three-month intervals [1–4]. We postulated that delayed plastic biliary stent removal (DPBSR) would increase complication rates. Aims We aim to report our single-centre experience with complications arising from DPBSR. Methods This was a retrospective, single-center, observational cohort study. All subjects who had ERCP-guided plastic biliary stent placement in Halifax, Nova Scotia between Dec 2019 and June 2020 were included in the study. DPBSR was defined as stent removal >=90 days from insertion. Four endpoints were assigned to patients: 1. Stent removed endoscopically, 2. Died with stent in-situ (measured from stent placement to documented date of death/last clinical encounter before death), 3. Pending removal (subjects clinically well, no liver enzyme elevation, not expired, endpoint 1 Nov 2020), and 4. Complication requiring urgent reintervention. Kaplan-Meier survival analysis was used to represent duration of stent patency (Fig.1). Results 102 (47.2%) had plastic biliary stents placed between 2/12/2019 and 29/6/2020. 49 (48%) were female, and the median age was 68 (R 16–91). Median follow-up was 167.5 days, 60 (58.8%) subjects had stent removal, 12 (11.8%) died before replacement, 21 (20.6%) were awaiting stent removal with no complications (median 230d, R 30–332), 9 (8.8%) had complications requiring urgent ERCP. Based on death reports, no deaths were related to stent-related complications. 72(70.6%) of patients had stents in-situ for >= 90 days. In this population, median time to removal was 211.5d (R 91-441d). 3 (4.2%) subjects had stent-related complications requiring urgent ERCP, mean time to complication was 218.3d (R 94–441). Stent removal >=90 days was not associated with complications such as occlusion, cholangitis, and migration (p=1.0). Days of stent in-situ was not associated with occlusion, cholangitis, and migration (p=0.57). Sex (p=0.275), cholecystectomy (p=1.0), cholangiocarcinoma (p=1.0), cholangitis (p=0.68) or pancreatitis (p=1.0) six weeks prior to ERCP, benign vs. malignant etiology (p=1.0) were not significantly associated with stent-related complications. Conclusions Plastic biliary stent longevity may have been previously underestimated. The findings of this study agree with CAG framework recommendations [5] that stent removal be prioritized as elective (P3). Limitations include small sample size that could affect Kaplan-Meier survival analysis. Despite prolonged indwelling stent time as a result of COVID-19, we did not observe an increased incidence of stent occlusion or other complications. Funding Agencies None

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Survival Analysis of Geriatric Patients with Low Digestive Hemorrhage Attending an Emergency Department

Gerontology ◽

10.1159/000513245 ◽

2021 ◽

pp. 1-6

Author(s):

Ana Fernandez-Suárez ◽

Oriol Yuguero Torres

Keyword(s):

Emergency Department ◽

Survival Analysis ◽

Retrospective Study ◽

Survival Rate ◽

Life Expectancy ◽

Antiplatelet Therapy ◽

Geriatric Patients ◽

Digestive Hemorrhage ◽

Kaplan Meier ◽

Number Of Individuals

Background: The increase in life expectancy and low mortality have doubled the number of individuals older than 65 in the last 30 years. Methods: We conducted a retrospective study of 101 patients older than 80 years of age treated by low digestive hemorrhage (LDH) in an emergency department during 2018. Sociodemographic variables were evaluated, as well as comorbidity and survival at 18 months. Survival was assessed by a Kaplan-Meier test. Results: 52.5% of the subjects were women. The average comorbidity of the sample was 1.97. The survival rate per year was 60%. The finding on colonoscopy shows no association with mortality. However, those patients on anticoagulant/antiplatelet therapy have a higher survival rate. Conclusion: Survival per year is high, so urgent colonoscopy for an LDH should be performed after evaluating the patient’s stability and functional status in a scheduled and outpatient manner.

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Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods

Risks ◽

10.3390/risks9070121 ◽

2021 ◽

Vol 9 (7) ◽

pp. 121

Author(s):

Beata Bieszk-Stolorz ◽

Krzysztof Dmytrów

Keyword(s):

Survival Analysis ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Stock Exchange ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

Stock Exchanges ◽

Analysis Methods ◽

Hazards Model ◽

Kaplan Meier

The aim of our research was to compare the intensity of decline and then increase in the value of basic stock indices during the SARS-CoV-2 coronavirus pandemic in 2020. The survival analysis methods used to assess the risk of decline and chance of rise of the indices were: Kaplan–Meier estimator, logit model, and the Cox proportional hazards model. We observed the highest intensity of decline in the European stock exchanges, followed by the American and Asian plus Australian ones (after the fourth and eighth week since the peak). The highest risk of decline was in America, then in Europe, followed by Asia and Australia. The lowest risk was in Africa. The intensity of increase was the highest in the fourth and eleventh week since the minimal value had been reached. The highest odds of increase were in the American stock exchanges, followed by the European and Asian (including Australia and Oceania), and the lowest in the African ones. The odds and intensity of increase in the stock exchange indices varied from continent to continent. The increase was faster than the initial decline.

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