scholarly journals Application of Multinomial Regression Model to Identify Parameters Impacting Traffic Barrier Crash Severity

2019 ◽  
Vol 13 (1) ◽  
pp. 57-64
Author(s):  
Mahdi Rezapour ◽  
Amirarsalan Mehrara Molan ◽  
Khaled Ksaibati
Keyword(s):  
Regression Model ◽  
Multinomial Logistic Regression ◽  
Crash Severity ◽  
Multinomial Regression ◽  
Interstate Highways ◽  
The Road ◽  
Run Off ◽  
Multinomial Regression Model ◽  
Proportional Odds Assumption ◽  
And Performance

Background: Run Off The Road (ROTR) crashes are some of the most severe crashes that could occur on roadways. The main countermeasure that can be taken to address this type of crashe is traffic barrier installation. Although ROTR crashes can be mitigated significantly by traffic barriers, still traffic barrier crashes resulted in considerable amount of severe crashes. Besides, the types of traffic barriers, driver actions and performance play an important role in the severity of these crashes. Methods: This study was conducted by incorporating only traffic barrier crashes in Wyoming. Based on the literature review there are unique contributory factors in different crash types. Therefore, in addition to focusing on traffic barrier crashes, crashes were divided into two different highway classes: interstate and non-interstate highways. Results: The result of proportional odds assumption was an indication that multinomial logistic regression model is appropriate for both non-interstate and interstates crashes involved with traffic barriers. The results indicated that road surface conditions, age, driver restraint and negotiating a curve were some of the factors that impact the severity of traffic barrier crashes on non-interstate highways. On the other hand, the results of interstate barrier crashes indicated that besides types of barriers, driver condition, citation record, speed limit compliance were some of the factors that impacted the interstate traffic barrier crash severity. Conclusion: The results of this study would provide the policymakers with the directions to take appropriate countermeasures to alleviate the severity of traffic barrier crashes.

Predictive markers of nonalcoholic fatty liver disease in lean patients. A multinomial regression model and a 2k factorial analysis

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Emma Purón-González ◽  
Arnulfo González-Cantú ◽  
Edgar Ulises Coronado-Alejandro ◽  
Oswaldo Enrique Sánchez-Dávila ◽  
Héctor Cobos-Aguilar ◽  
...  
Keyword(s):  
Liver Disease ◽  
Fatty Liver ◽  
Regression Model ◽  
Nonalcoholic Fatty Liver Disease ◽  
Fatty Liver Disease ◽  
Predictive Markers ◽  
Factorial Analysis ◽  
Multinomial Regression ◽  
Nonalcoholic Fatty Liver ◽  
Multinomial Regression Model

scholarly journals Fever and hypothermia represent two populations of sepsis patients and are associated with outside temperature

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Daniel O. Thomas-Rüddel ◽  
Peter Hoffmann ◽  
Daniel Schwarzkopf ◽  
Christian Scheer ◽  
Friedhelm Bach ◽  
...  
Keyword(s):  
Regression Model ◽  
Secondary Analysis ◽  
Temperature Response ◽  
Thermal Response ◽  
Binary Logistic Regression ◽  
High Fever ◽  
Multinomial Regression ◽  
Binary Logistic Regression Model ◽  
Multinomial Regression Model ◽  
Fever Response

Abstract Background Fever and hypothermia have been observed in septic patients. Their influence on prognosis is subject to ongoing debates. Methods We did a secondary analysis of a large clinical dataset from a quality improvement trial. A binary logistic regression model was calculated to assess the association of the thermal response with outcome and a multinomial regression model to assess factors associated with fever or hypothermia. Results With 6542 analyzable cases we observed a bimodal temperature response characterized by fever or hypothermia, normothermia was rare. Hypothermia and high fever were both associated with higher lactate values. Hypothermia was associated with higher mortality, but this association was reduced after adjustment for other risk factors. Age, community-acquired sepsis, lower BMI and lower outside temperatures were associated with hypothermia while bacteremia and higher procalcitonin values were associated with high fever. Conclusions Septic patients show either a hypothermic or a fever response. Whether hypothermia is a maladaptive response, as indicated by the higher mortality in hypothermic patients, or an adaptive response in patients with limited metabolic reserves under colder environmental conditions, remains an open question. Trial registration The original trial whose dataset was analyzed was registered at ClinicalTrials.gov (NCT01187134) on August 23, 2010, the first patient was included on July 1, 2011.

scholarly journals Analysis of relative abundances with zeros on environmental gradients: a multinomial regression model

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5643 ◽  
Author(s):  
Fiona Chong ◽  
Matthew Spencer
Keyword(s):  
Data Analysis ◽  
Regression Model ◽  
Compositional Data ◽  
Environmental Gradients ◽  
Compositional Data Analysis ◽  
Multinomial Regression ◽  
Point Count ◽  
Compositional Approach ◽  
Multinomial Regression Model ◽  
Relative Abundances

Ecologists often analyze relative abundances, which are an example of compositional data. However, they have made surprisingly little use of recent advances in the field of compositional data analysis. Compositions form a vector space in which addition and scalar multiplication are replaced by operations known as perturbation and powering. This algebraic structure makes it easy to understand how relative abundances change along environmental gradients. We illustrate this with an analysis of changes in hard-substrate marine communities along a depth gradient. We fit a quadratic multivariate regression model with multinomial observations to point count data obtained from video transects. As well as being an appropriate observation model in this case, the multinomial deals with the problem of zeros, which often makes compositional data analysis difficult. We show how the algebra of compositions can be used to understand patterns in dissimilarity. We use the calculus of simplex-valued functions to estimate rates of change, and to summarize the structure of the community over a vertical slice. We discuss the benefits of the compositional approach in the interpretation and visualization of relative abundance data.

When Victims Refuse and Prosecutors Decline: Examining Exceptional Clearance in Sexual Assault Cases

2019 ◽  
Vol 65 (4) ◽  
pp. 474-498 ◽  
Author(s):  
Tara N. Richards ◽  
Marie Skubak Tillyer ◽  
Emily M. Wright
Keyword(s):  
Sexual Assault ◽  
Regression Model ◽  
Similar Pattern ◽  
Reporting System ◽  
Future Research ◽  
Sexual Offense ◽  
Male Victims ◽  
Multinomial Regression ◽  
Multinomial Regression Model ◽  
Sexual Assault Case

This study examines the predictors of sexual assault case clearance, with a focus on arrest and two types of exceptional clearance: victim refusal to cooperate and prosecutorial declination to prosecute. Using National Incident Based Reporting System (NIBRS) data on crime incidents that contain a sexual offense ( N = 21,977), we estimated a multinomial regression model to examine the predictors of different clearance types for cases of sexual assault. Results indicated that the likelihood of victim refusal decreases in cases perpetrated by strangers, involving victim injury, occurring in public, and involving multiple offenses. A similar pattern of findings was observed for the decision to decline to prosecute a case. In addition, prosecutors are more likely to decline to prosecute cases with male victims and older victims. We discuss the implications of our findings and directions for future research.

Consensus molecular subtypes and RAS status as biomarker of treatment intensity with fluoropyrimidine, bevacizumab, and irinotecan in metastatic colorectal cancer (XELAVIRI, AIO KRK 0110).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3552-3552
Author(s):  
Arndt Stahler ◽  
Volker Heinemann ◽  
Veronika Schuster ◽  
Annabel Helga Sophie Alig ◽  
Laura Elisabeth Fischer ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regression Model ◽  
Metastatic Colorectal Cancer ◽  
Cox Regression ◽  
Molecular Subtypes ◽  
Progression Free Survival ◽  
Phase Iii ◽  
Prognostic Impact ◽  
Multinomial Regression ◽  
Multinomial Regression Model

3552 Background: Prognostic biomarkers beside RAS/BRAF status are necessary to identify metastatic colorectal cancer (mCRC) patients who benefit from combined (COMB) versus sequential (SEQ) treatment with fluoropyrimidine, bevacizumab and irinotecan (randomized phase III XELAVIRI trial). Methods: mRNA was extracted from formalin-fixed paraffin embedded (FFPE) tumor tissue of 337 patients, gene expression was measured by the Nanostring PanCancer Progression Panel. Consensus molecular subtypes (CMS) classification was re-derived using a multinomial regression model. Data of Guinney et al. (Nat. Med. 2015. 21:1350-6) and FIRE-3 served as training and validation set. RAS/BRAF MUT were assessed by pyrosequencing. Median overall (OS) and progression free survival (PFS), hazard ratios (HR) and 95% confidence interval (CI) were estimated by Kaplan-Meier method and univariate Cox regression. Results: The multinomial regression model employed in the present analysis correctly predicted CMS labels in 98.3 % of the original Guinney- and 100.0 % of FIRE-3 population. In XELAVIRI, CMS subgroups were predicted as follows: CMS1: n = 62 (18.4 %); CMS2: n = 174 (51.6 %); CMS3: n = 9 (2.7 %); CMS4: n = 92 (27.3 %). A general prognostic impact of CMS was not observed when all patients were analysed. In RAS/BRAF WT mCRC patients, substantial benefit of COMB versus SEQ treatment was shown for OS and PFS in CMS2 and CMS4, but not in CMS1. Conversely, OS was significantly longer for COMB treatment in patients with RAS MUT and CMS1 mCRC, while SEQ treatment was not inferior in RAS MUT and CMS2 or CMS4 subgroups (see TABLE). Additional data for overall response rates, early tumor shrinkage and sidedness might be presented at the meeting. Conclusions: This retrospective analysis of XELAVIRI suggests that CMS may serve as biomarker that predicts response to initially combined versus less intensive sequential chemotherapy in patients with RAS/BRAF WT mCRC.[Table: see text]

scholarly journals An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
W. Duncan Wadsworth ◽  
Raffaele Argiento ◽  
Michele Guindani ◽  
Jessica Galloway-Pena ◽  
Samuel A. Shelburne ◽  
...  
Keyword(s):  
Regression Model ◽  
Multinomial Regression ◽  
Multinomial Regression Model ◽  
Microbiome Data
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