scholarly journals Comprehensive Evaluation of a Sparse Dataset, Assessment and Selection of Competing Models

Signals ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 157-169
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Goodness Of Fit ◽  
Negative Binomial ◽  
Comprehensive Evaluation ◽  
Binary Logistic Regression ◽  
Parameter Estimates ◽  
Hurdle Model ◽  
Factors Affecting ◽  
Equivalent Property ◽  
The Right ◽  
The Impact

With tremendous associated economic and social costs of crashes, researchers have been trying not only to identify the factors affecting crashes, but also to estimate those coefficients in the most accurate ways. Estimating model coefficients without accounting for a correct distribution would result in biased and erroneous results. This risk especially holds true when modeling skewed equivalent property damage only (EPDO) crashes with a preponderance of zeroes. The distribution of EPDO is known for not being modeled with known distributions such as Poisson or negative binomial distributions. This issue is highlighted in particular for a mountainous state like Wyoming that has very low traffic levels and a severely high crash rate. In addition, we included barriers in the model that did not experience any crashes but did suffer from being under-designed by geometric architects, thereby adding to the number of zero count observations. Various models with different distributional characteristics were considered and compared in this study. Comparisons were not just made across models in terms of their goodness of fit, but the estimated coefficients were also compared to see the impact of considering the wrong distributional assumptions on model parameter estimates. As the objectives of this study are to implement the identified results for optimization purposes and locate hazardous locations that could host future crashes, the results highlight accurate model estimations and the consequences of a failure to account for the right distributions. After conducting different goodness-of-fit measures, a hurdle model was proposed in this study to accommodate observations with zero crashes, and to account for a sparse distribution of EPDO crashes in the state of Wyoming. For the hurdle model, binary logistic regression was used to account for observations with zero crashes, while the negative binomial method was considered for non-zero observations. The findings of this study have direct implications on the allocation of limited funds for policymakers in Wyoming, as optimization could be conducted on the geometric characteristics of traffic barriers in future studies.

Structural Model of Service Quality Factors Affecting Loyalty Sustainability

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Eman Al-erqi ◽  
◽  
Mohd Lizam Mohd Diah ◽  
Najmaddin Abo Mosali ◽  
◽  
...  
Keyword(s):  
International Students ◽  
Service Quality ◽  
Goodness Of Fit ◽  
Structural Model ◽  
Quality Factors ◽  
Factors Affecting ◽  
Measurement Models ◽  
Confirmatory Factor ◽  
The University ◽  
The Impact

This study seeks to address the impact of service quality affecting international student's satisfaction towards loyalty tothe Universiti Tun Hussein Onn Malaysia(UTHM). The aim of thestudy is to develop relationship between service quality factor and loyalty to the university from the international students’ perspectives. The study adopted quantitative approach where data was collected through questionnaire survey and analysed statistically. A total of 246 responses were received and found to be valid. The model was developed and analysed using AMOS-SEM software. Confirmatory factor analysis (CFA) function of the software was to assessed the measurement models and found that all the models achieved goodness of fit. Then path analysis function was used to assessed structural model and found that service qualityfactors have a significant effect on the students’ satisfaction and thus affecting the loyaltyto the university. Hopefully the outcome form this study will benefit the university in providing services especially to the international students.

scholarly journals On hypergeometric generalized negative binomial distribution

2002 ◽  
Vol 29 (12) ◽  
pp. 727-736 ◽  
Author(s):  
M. E. Ghitany ◽  
S. A. Al-Awadhi ◽  
S. L. Kalla
Keyword(s):  
Recurrence Relation ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Field Data ◽  
Goodness Of Fit ◽  
Negative Binomial ◽  
Generalized Negative Binomial Distribution ◽  
The Right ◽  
Three Term Recurrence Relation

It is shown that the hypergeometric generalized negative binomial distribution has moments of all positive orders, is overdispersed, skewed to the right, and leptokurtic. Also, a three-term recurrence relation for computing probabilities from the considered distribution is given. Application of the distribution to entomological field data is given and its goodness-of-fit is demonstrated.

scholarly journals Maximum Product of Spacing Parameter Estimation of Gompertz Rayleigh Distribution and Application to Rainfall Datasets

2021 ◽  
pp. 41-59
Author(s):  
Hussein Ahmad Abdulsalam ◽  
Sule Omeiza Bashiru ◽  
Alhaji Modu Isa ◽  
Yunusa Adavi Ojirobe
Keyword(s):  
Goodness Of Fit ◽  
Negative Binomial ◽  
Likelihood Estimation ◽  
Statistical Properties ◽  
Rainfall Data ◽  
Parameter Estimates ◽  
Data Sets ◽  
Unknown Parameters ◽  
Exponentiated Weibull ◽  
Integrated Hazard

Gompertz Rayleigh (GomR) distribution was introduced in an earlier study with few statistical properties derived and parameters estimated using only the most common traditional method, Maximum Likelihood Estimation (MLE). This paper aimed at deriving more statistical properties of the GomR distribution, estimating the three unknown parameters via a competitive method, Maximum Product of Spacing (MPS) and evaluating goodness of fit using rainfall data sets from Nigeria, Malaysia and Argentina. Properties of statistical distributions including distribution of smallest and largest order statistics, cumulative or integrated hazard function, odds function, rth non-central moments, moment generating function, mean, variance and entropy measures for GomR distribution were explicitly derived. The fitted data sets reveal the flexibility of GomR distribution over other distributions been compared with. Simulation study was used to evaluate the consistency, accuracy and unbiasedness of the GomR distribution parameter estimates obtained from the method of MPS. The study found that GomR distribution could not provide a better fit for Argentine rainfall data but it was the best distribution for the rainfall data sets from Nigeria and Malaysia in comparison with the distributions; Generalized Weibull Rayleigh (GWR), Exponentiated Weibull Rayleigh (EWR), Type (II) Topp Leone Generalized Inverse Rayleigh (TIITLGIR), Kumarawamy Exponential Inverse Raylrigh (KEIR), Negative Binomial Marshall-Olkin Rayleigh (NBMOR) and Exponentiated Weibull (EW). Furthermore, the estimates from MPSE were consistent as the sample size increases but not as efficient as those from MLE.

scholarly journals Geographical factors in access: investigating the impact of distance on the use of primary care extended hours, an administrative data study.

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Jen Murphy ◽  
William Whittaker ◽  
Mark Elliot ◽  
Rathi Ravindrarajah
Keyword(s):  
Primary Care ◽  
Negative Binomial ◽  
Unmet Need ◽  
Negative Binomial Regression ◽  
City Region ◽  
Hub Location ◽  
Barriers To Access ◽  
Access To Primary Care ◽  
The Right ◽  
The Impact

IntroductionNHS national targets mandate extended opening hours of doctors’ surgeries as a mechanism for increasing access to primary care, based on the assumption that unmet need is caused by a lack of appointments at the right time. Research has shown that other factors impact access and it may not simply be availability that limits an individual’s ability to access healthcare. Aims and Objectives To determine whether distance, familiarity and deprivation impact on the uptake of extended hours GP services that use a hub practice model. MethodsWe linked an appointments dataset to publicly available population datasets. With that linked dataset, we used negative binomial regression to model count data relating to uses of the extended hours service in one care commissioning group in the Greater Manchester city region. The dataset included 32,693 appointments across 4 hubs serving 37 practices. ResultsFamiliarity and distance are important in predicting the number of uses of the extended hours service at a GP practice level. For a theoretical pair of practices collocated at the hub location, the model predicts a use rate of 101.2 for the non hub compared with 283.7 for the hub, a 180% uplift. For a pair of non-hub practices, one located the mean distance from the hub, the other located one mile further away, the model predicts 64.8 uses for the nearer practice, and 46.5 uses for the far practice, a 28% penalty. ConclusionThe results indicate geographical inequity in the extended hours service. There may be many patients with unmet need for whom the extension of hours via a hub model does not address barriers to access. Providers should consider whether or not this type of model actually works to facilitate access. This is particularly of importance in the context of closing health inequality gaps.

scholarly journals Australian state influenza notifications and school closures in 2019

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 1899
Author(s):  
Anna Mae Scott ◽  
Mina Bakhit ◽  
Justin Clark ◽  
Melanie Vermeulen ◽  
Mark Jones ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Negative Binomial ◽  
School Closure ◽  
School Closures ◽  
Chi Square ◽  
Exact Test ◽  
Australian State ◽  
Chi Square Test ◽  
The Impact ◽  
Vacation Period

Background: The impact of school holidays on influenza rates has been sparsely documented in Australia. In 2019, the early winter influenza season coincided with mid-year school breaks, enabling us the unusual opportunity to examine how influenza incidence changed during school closure dates. Methods: The weekly influenza data from five Australian state and one territory health departments for the period of week 19 (mid-May) to week 35 (early September) 2019 were compared to each state’s public school closure dates. We used segmented regression to model the weekly counts and a negative binomial distribution to account for overdispersion due to autocorrelation. The models’ goodness-of-fit was assessed by plots of observed versus expected counts, plots of residuals versus predicted values, and Pearson’s Chi-square test. The main exposure was the July two-week school vacation period, using a lag of one week. The effect is estimated as a percent change in incidence level, and in slope. We also dichotomized the change in weekly counts into decreases versus increases (or no change). The proportion of decreases were then compared for each of three periods (pre-vacation, vacation, post-vacation) using Fishers exact test. Results: School holidays were associated with significant declines in influenza incidence. The models showed acceptable goodness-of-fit. The numbers and percentages of decreases in weekly influenza counts from the previous week for all states combined were: 19 (33%) pre-vacation; 11 (92%) decreases during the vacation; and 19 (59%) decreases post-vacation (P=0.0002). The first decline during school holidays is seen in the school aged (5-19 years) population, with the declines in the adult and infant populations being smaller and following a week later. Conclusions: Given the significant and rapid reductions in incidence, these results have important public health implications. Closure or extension of holiday periods could be an emergency option for state governments.

scholarly journals Factors affecting under-five mortality in Ethiopia: a multi-level negative binomial model

2019 ◽  
Author(s):  
Bisrat Misganew Geremew ◽  
Kassahun Alemu Gelaye ◽  
Alemakef Wagnew Melesse ◽  
Temesgen Yihunie Akalu ◽  
Adhanom Gebreegziabher Baraki
Keyword(s):  
Birth Interval ◽  
Goodness Of Fit ◽  
Negative Binomial ◽  
Addis Ababa ◽  
Household Head ◽  
Multiple Birth ◽  
Negative Binomial Regression Model ◽  
Factors Affecting ◽  
Under Five ◽  
Significant Factors

Abstract Introduction: Under-five mortality is a key indicator of countries’ developmental status. Even though remarkable declines in under-five mortality rates, nearly 5.6 million children still die annually worldwide before their fifth birthday. The 2016 Ethiopian Demographic and Health Survey (EDHS) report revealed that 67 children per 1,000 live births died before the fifth birthday. This study was aimed at determining factors affecting under-five mortality in Ethiopia using EDHS, 2016.Methods: The data was retrieved from the EDHS 2016. A total weighted number of 11,023 under-five children were included in this study. Descriptive statistics were done and reported using tables, graphs, and texts. The multilevel negative binomial regression model was fitted to identify significant factors of under-five mortality. Adjusted Incidence rate (AIRR) with a 95% confidence interval (CI) and p-value <0.05 in the multivariable model were reported. The goodness of fit was checked using the deviance test.Results: Mother attained higher education (AIRR=0.25, 95% CI: 0.10-0.66); female-headed household (AIRR=1.32, 95%CI:1.05-1.66); age of household head (AIRR=1.07, 95%CI: 1.03,1.11); preceding birth interval ≥48 months (AIRR=0.51, 95%CI: 0.42-0.61); child’s had history of diarrhea (AIRR=1.23, 95% CI:1.08-1.41); multiple birth type (AIRR=1.80, 95% CI:1.34-2.42); mothers delivered in health facility (IRR=0.86, 95% CI:0.73,0.94), residents of Addis Ababa (AIRR=0.52, 95%CI: 0.28-0.98), and Amhara region (AIRR=1.43, 95%CI: 1.09, 1.88) were statistically significant factors to under-five mortality in Ethiopia.Conclusion: In this study, under-five mortality remains a public health problem in Ethiopia. Mothers education level, women delivered at health institution, preceding birth interval 24-35 and ≥48, and residents of Addis Ababa have reduced the incidence of under-five mortality. On the other hand, being a female household head, age of mother at first giving birth, being employment, having multiple births and having childhood diarrhea was associated with a higher incidence of under-five mortality. This finding suggests that enhancing opportunities to female education, addressing regional disparities, and encouraging mothers to deliver at health institutions will help to combat the burden of under-five mortality. Keywords: Under-five mortality, negative binomial, multilevel analysis, Ethiopia

scholarly journals Impact of factors on fair value accounting: empirical study in Vietnam

2020 ◽  
Vol 17 (3) ◽  
pp. 10-26
Author(s):  
Bui Thi Ngoc
Keyword(s):  
Quantitative Research ◽  
Positive Impact ◽  
Accounting Standards ◽  
Binary Logistic Regression ◽  
Fair Value ◽  
Analytical Framework ◽  
Fair Value Accounting ◽  
Quantitative Research Methods ◽  
Factors Affecting ◽  
The Impact

Due to the ongoing process of globalization, enterprises need to provide financial statements in accordance with international practices, in which information about assets and liabilities should be presented at fair values rather than at original prices. Fair value is supported by the International Accounting Standards Board and the Financial Accounting Standards Board. The purpose of this study is to evaluate the adoption of fair value accounting in Vietnam and the impact of factors on the adoption of fair value. The paper used the analytical framework of previous studies to identify factors affecting the adoption of fair value. Additionally, this study applied quantitative research methods and collected data by sending questionnaires to 127 accountants and directors of listed companies. Particularly, binary logistic regression was conducted to investigate the extent of the impact of each factor on the adoption of fair value. The results have shown that human resources have the strongest and positive impact on the adoption of fair value, and this is followed by the benefits of fair value. Difficulties and markets negatively affect the use of fair value. Furthermore, the control variables that affect the use of fair value are sector, size and length of operation with different levels of impact. The accuracy rate of the overall predictive model is 85.8%. The findings provide guidance of the application of fair value accounting in companies and give recommendations to policy makers in establishing a legal accounting framework in Vietnam.

scholarly journals Behavioral Differences Towards Internal and External Factors in Making the Bid/No Bid Decision

2019 ◽  
Vol 5 (5) ◽  
pp. 1189-1196
Author(s):  
Abdulrahman Bageis ◽  
Ibrahim I. Falqi ◽  
Abdullah Alshehri ◽  
Saleh Alsulamy ◽  
Tariq A. Alsahli
Keyword(s):  
Quantitative Research ◽  
Subjective Evaluation ◽  
External Factors ◽  
Business Success ◽  
Behavioral Differences ◽  
Start Time ◽  
Factors Affecting ◽  
The Right ◽  
Internal And External Factors ◽  
The Impact

Decision-making and subjective evaluation are two important aspects that characterizes the involvement of an organization in tender process. Moreover, selection of the right project to bid for is a principal feature of business success. The study aims to investigate the behavioral differences of Saudi construction contractors toward internal and external factors based on the process of modelling the bidding decisions. A quantitative research design is used to investigate the behavioral differences of 97 contractors recruited from construction industry of Saudi Arabia. A questionnaire was distributed among the respondents that would help in identifying the significant level of factors affecting the bid or no bid decision. The impact of internal and external factors on the bidding decisions was evaluated using one-way ANOVA analysis. The results have shown a significant and positive effect of internal and external factors on the bid or no bid decision; including job start time, work capital requirement, availability of qualified human resources, bidding methods, bidding document price, project supervision procedure and etc. The study has helped in establishing a better understanding toward the behavioral differences of contractors with respect to the bidding decisions.

scholarly journals Use of Direct Marketing Strategies by Farmers and Their Impact on Farm Business Income

2011 ◽  
Vol 40 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Hiroki Uematsu ◽  
Ashok K. Mishra
Keyword(s):  
Negative Binomial ◽  
Direct Marketing ◽  
Marketing Strategies ◽  
Farmers Markets ◽  
Farm Income ◽  
Factors Affecting ◽  
Quantile Regression Model ◽  
Farm Business ◽  
On Farm ◽  
The Impact

Direct marketing strategies increasingly have been recognized as a viable business option in U.S. agriculture as they allow producers to receive a better price by selling products directly to consumers. The objective of this study is twofold. Using a national survey, we first estimated a zero-inflated negative binomial model to identify factors affecting the total number of direct marketing strategies adopted by farmers. Then we estimated a quantile regression model to assess the impact of the intensity of adoption of direct marketing strategies on gross cash farm income. The results show that the intensity of adoption has no significant impact on gross cash farm income and that participation in farmers markets is negatively correlated with gross cash farm income at all five quantiles estimated.

scholarly journals Australian state influenza notifications and school holiday closures in 2019

F1000Research ◽  
2021 ◽  
Vol 8 ◽  
pp. 1899
Author(s):  
Anna Mae Scott ◽  
Mina Bakhit ◽  
Justin Clark ◽  
Melanie Vermeulen ◽  
Mark Jones ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Negative Binomial ◽  
State Governments ◽  
Health Departments ◽  
Chi Square ◽  
Australian State ◽  
Show Evidence ◽  
Chi Square Test ◽  
Predicted Values ◽  
The Impact

Background: The impact of school holidays on influenza rates has been sparsely documented in Australia. In 2019, the early winter influenza season coincided with mid-year school breaks, enabling us the unusual opportunity to examine how influenza incidence changed during school holiday closure dates. Methods: The weekly influenza data from five Australian state and one territory health departments for the period of week 19 (mid-May) to week 39 (early October) 2019 were compared to each state’s public-school holiday closure dates. We used segmented regression to model the weekly counts and a negative binomial distribution to account for overdispersion due to autocorrelation. The models’ goodness-of-fit was assessed by plots of observed versus expected counts, plots of residuals versus predicted values, and Pearson’s Chi-square test. The main exposure was the July two-week school holiday period, using a lag of one week. The effect is estimated as a percent change in incidence level, and in slope. Results: School holidays were associated with significant declines in influenza incidence in three states and one territory by between 41% and 65%. Two states did not show evidence of declines although one of those states had already passed its peak by the time of the school holidays. The models showed acceptable goodness-of-fit. The first decline during school holidays is seen in the school aged (5-19 years) population, with the declines in the adult and infant populations being smaller and following a week later. Conclusions: Given the significant and rapid reductions in incidence, these results have important public health implications. Closure or extension of holiday periods could be an emergency option for state governments.

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