Refining logistic regression models for wildlife habitat suitability modeling—A case study with muntjak and goral in the Central Himalayas, India

2011 ◽  
Vol 222 (8) ◽  
pp. 1354-1366 ◽  
Author(s):  
Aditya Singh ◽  
S.P.S. Kushwaha
Keyword(s):  
Logistic Regression ◽  
Habitat Suitability ◽  
Regression Models ◽  
Wildlife Habitat ◽  
Central Himalayas ◽  
Habitat Suitability Modeling ◽  
Logistic Regression Models

Statistical simulation of ocean current patterns using autoregressive logistic regression models: A case study in the Gulf of Mexico

2019 ◽  
Vol 136 ◽  
pp. 1-12 ◽  
Author(s):  
Helios Chiri ◽  
Ana Julia Abascal ◽  
Sonia Castanedo ◽  
José Antonio A. Antolínez ◽  
Yonggang Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Gulf Of Mexico ◽  
Regression Models ◽  
Statistical Simulation ◽  
Ocean Current ◽  
Logistic Regression Models

Using logistic regression for persona segmentation in tourism: A case study

2020 ◽  
Vol 48 (4) ◽  
pp. 1-16
Author(s):  
Rui Kang
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Tourism Industry ◽  
Opinion Leaders ◽  
Service Users ◽  
User Characteristics ◽  
Logistic Regression Models ◽  
Integrated Method ◽  
Tourism Motivation

I introduced a method for persona segmentation in the tourism industry to identify representative subgroups with different motivations or goals. Data from 496 key opinion leaders of groups representing 7,965 travel service users were analyzed with a logistic regression model of user characteristics and tourism motivation. I found that logistic regression is an integrated method of persona segmentation that balances precision and accuracy, and yields replicable and valid results. Three subgroups for persona segmentation based on logistic regression models are proposed.

The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

2019 ◽  
pp. 1-5
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Skin Necrosis ◽  
Regression Models ◽  
Multivariable Analysis ◽  
P Value ◽  
Flap Necrosis ◽  
Single Institution ◽  
Logistic Regression Models ◽  
The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

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