Generalized Linear Models to Identify the Impact of Road Geometric Design Features on Crash Frequency in Rural Roads

2021 ◽  
Author(s):  
Moataz Bellah Ben Khedher ◽  
Dukgeun Yun
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Geometric Design ◽  
Design Features ◽  
Crash Frequency ◽  
Rural Roads ◽  
The Impact

Changes in blood culture methodology have an impact on time trends of bacteraemia: a 26-year regional study

2010 ◽  
Vol 139 (5) ◽  
pp. 772-776 ◽  
Author(s):  
M. SØGAARD ◽  
M. C. ENGEBJERG ◽  
S. LUNDBYE-CHRISTENSEN ◽  
H. C. SCHØNHEYDER
Keyword(s):  
Blood Culture ◽  
Generalized Linear Models ◽  
Time Trends ◽  
Time Trend ◽  
Linear Models ◽  
Population Ageing ◽  
Invasive Procedures ◽  
Regional Study ◽  
The Impact ◽  
Bacterial Groups

SUMMARYThe incidence of bacteraemia has increased considerably during the last decades. This may be related to population ageing, increased use of invasive procedures, and increased ascertainment of bacteraemia. Generalized additive and generalized linear models were used to analyse the impact of four successive improvements in blood culture methodology on the recovery of prevalent blood culture isolates while simultaneously controlling for underlying time trend and seasonal variation. Between 1981 and 2006, 20 091 bacteraemias comprising 22 800 blood culture isolates were diagnosed. The changes in methodology increased the recovery of some bacterial groups; the greatest impact was observed for Enterobacteriaceae, pneumococci andStaphylococcus aureuswhereas recovery of β-haemolytic streptococci,Pseudomonas aeruginosa, other Gram-negative aerobes, and fungi was not affected. Changes in blood culture methodology should be taken into account when assessing time trends of bacteraemia.

scholarly journals Bayesian Correction for Misclassification in Multilevel Count Data Models

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Tyler Nelson ◽  
Joon Jin Song ◽  
Yoo-Mi Chin ◽  
James D. Stamey
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Positive Impact ◽  
Real Data ◽  
Count Data Models ◽  
Number Of Children ◽  
Standard Linear ◽  
Interval Estimators ◽  
Fully Bayesian ◽  
The Impact

Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.

Crash Frequency Analysis with Generalized Additive Models

2008 ◽  
Vol 2061 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Yuanchang Xie ◽  
Yunlong Zhang
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Generalized Additive Model ◽  
Negative Binomial ◽  
Generalized Additive Models ◽  
Additive Model ◽  
Additive Models ◽  
Crash Frequency ◽  
Data Set ◽  
Explanatory Variables

Recent crash frequency studies have been based primarily on generalized linear models, in which a linear relationship is usually assumed between the logarithm of expected crash frequency and other explanatory variables. For some explanatory variables, such a linear assumption may be invalid. It is therefore worthwhile to investigate other forms of relationships. This paper introduces generalized additive models to model crash frequency. Generalized additive models use smooth functions of each explanatory variable and are very flexible in modeling nonlinear relationships. On the basis of an intersection crash frequency data set collected in Toronto, Canada, a negative binomial generalized additive model is compared with two negative binomial generalized linear models. The comparison results show that the negative binomial generalized additive model performs best for both the Akaike information criterion and the fitting and predicting performance.

scholarly journals Patients learning to read their doctors’ notes: the importance of reminders

2016 ◽  
Vol 23 (5) ◽  
pp. 951-955 ◽  
Author(s):  
John N Mafi ◽  
Roanne Mejilla ◽  
Henry Feldman ◽  
Long Ngo ◽  
Tom Delbanco ◽  
...  
Keyword(s):  
Generalized Linear Models ◽  
Natural Experiment ◽  
Linear Models ◽  
Medical Center ◽  
Similar Frequency ◽  
Learning To Read ◽  
Doctor Communication ◽  
The Impact ◽  
Trial Participants ◽  
Gain Access

Abstract Objective To examine whether patients invited to review their clinicians’ notes continue to access them and to assess the impact of reminders on whether patients continued to view notes. Materials and methods We followed OpenNotes trial participants for 2 years at Beth Israel Deaconess Medical Center (BIDMC) and Geisinger Health System (GHS). Electronic invitations alerting patients to signed notes stopped at GHS after year 1, creating a natural experiment to assess the impact of reminders. We used generalized linear models to measure whether notes were viewed within 30 days of availability. Results We identified 14 360 patients (49 271 visits); mean age 52.2; 57.8% female. In year 1, patients viewed 57.5% of their notes, and their interest in viewing notes persisted over time. In year 2, BIDMC patients viewed notes with similar frequency. In contrast, GHS patients viewed notes far less frequently, a change starting when invitations ceased (RR 0.29 [0.26–0.32]) and persisting to the end of the study (RR 0.20 [0.17–0.23]). A subanalysis of BIDMC patients revealed that black and other/multiracial patients also continued to view notes, although they were overall less likely to view notes compared with whites (RR 0.75 [0.67–0.83] and 0.93 [0.89–0.98], respectively). Discussion As millions of patients nationwide increasingly gain access to clinicians’ notes, explicit email invitations to review notes may be important for fostering patient engagement and patient-doctor communication. Conclusion Note viewing persists when accompanied by email alerts, but may decline substantially in their absence. Non-white patients at BIDMC viewed notes less frequently than whites, although their interest also persisted.

Effect of Different Dentifrices, Bleaching with 35% Hydrogen Peroxide, and Red Wine on Surface Color and Roughness of Bovine Enamel

2020 ◽  
Vol 02 ◽  
Author(s):  
RM Garcia ◽  
WF Vieira-Junior ◽  
JD Theobaldo ◽  
NIP Pini ◽  
GM Ambrosano ◽  
...  
Keyword(s):  
Hydrogen Peroxide ◽  
Generalized Linear Models ◽  
Repeated Measures ◽  
Red Wine ◽  
Linear Models ◽  
Artificial Saliva ◽  
Surface Color ◽  
Dental Bleaching ◽  
Surface Alteration ◽  
Bovine Enamel

Objective: To evaluate color and roughness of bovine enamel exposed to dentifrices, dental bleaching with 35% hydrogen peroxide (HP), and erosion/staining by red wine. Methods: Bovine enamel blocks were exposed to: artificial saliva (control), Oral-B Pro-Health (stannous fluoride with sodium fluoride, SF), Sensodyne Repair & Protect (bioactive glass, BG), Colgate Pro-Relief (arginine and calcium carbonate, AR), or Chitodent (chitosan, CHI). After toothpaste exposure, half (n=12) of the samples were bleached (35% HP), and the other half were not (n=12). The color (CIE L*a* b*, ΔE), surface roughness (Ra), and scanning electron microscopy were evaluated. Color and roughness were assessed at baseline, post-dentifrice and/or -dental bleaching, and after red wine. The data were subjected to analysis of variance (ANOVA) (ΔE) for repeated measures (Ra), followed by Tukey ́s test. The L*, a*, and b* values were analyzed by generalized linear models (a=0.05). Results: The HP promoted an increase in Ra values; however, the SF, BG, and AR did not enable this alteration. After red wine, all groups apart from SF (unbleached) showed increases in Ra values; SF and AR promoted decreases in L* values; AR demonstrated higher ΔE values, differing from the control; and CHI decreased the L* variation in the unbleached group. Conclusion: Dentifrices did not interfere with bleaching efficacy of 35% HP. However, dentifrices acted as a preventive agent against surface alteration from dental bleaching (BG, SF, and AR) or red wine (SF). Dentifrices can decrease (CHI) or increase (AR and SF) staining by red wine.

Economic burden of readmission due to postoperative cerebrospinal fluid leak in Chinese patients

2020 ◽  
Vol 9 (16) ◽  
pp. 1105-1115
Author(s):  
Shuqing Wu ◽  
Xin Cui ◽  
Shaoyu Zhang ◽  
Wenqi Tian ◽  
Jiazhen Liu ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Generalized Linear Models ◽  
Economic Burden ◽  
Linear Models ◽  
Chinese Patients ◽  
Cerebrospinal Fluid Leakage ◽  
Index Hospitalization ◽  
Real World Data ◽  
Factors Associated ◽  
Hospitalization Cost

Aim: This real-world data study investigated the economic burden and associated factors of readmissions for cerebrospinal fluid leakage (CSFL) post-cranial, transsphenoidal, or spinal index surgeries. Methods: Costs of CSFL readmissions and index hospitalizations during 2014–2018 were collected. Readmission cost was measured as absolute cost and as percentage of index hospitalization cost. Factors associated with readmission cost were explored using generalized linear models. Results: Readmission cost averaged US$2407–6106, 35–94% of index hospitalization cost. Pharmacy costs were the leading contributor. Generalized linear models showed transsphenoidal index surgery and surgical treatment for CSFL were associated with higher readmission costs. Conclusion: CSFL readmissions are a significant economic burden in China. Factors associated with higher readmission cost should be monitored.

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