Predictor Importance in Logistic Regression: An Extension of Dominance Analysis

2006 ◽  
Author(s):  
Nicole M. Traxel ◽  
Razia Azen
2009 ◽  
Vol 34 (3) ◽  
pp. 319-347 ◽  
Author(s):  
Razia Azen ◽  
Nicole Traxel

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R2 analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A simulation study, using both simple random sampling from a known population and bootstrap sampling from a single (parent) random sample, was performed to evaluate the bias, sampling distribution, and confidence intervals of quantitative dominance measures as well as the reproducibility of qualitative dominance measures. Results indicated that the bootstrap procedure is feasible and can be used in applied research to generalize logistic regression dominance analysis results to the population of interest. The procedures for determining and interpreting the general dominance of predictors in a logistic regression context are illustrated with an empirical example.


Author(s):  
Praveen V. Mummaneni ◽  
Mohamad Bydon ◽  
John J. Knightly ◽  
Mohammed Ali Alvi ◽  
Yagiz U. Yolcu ◽  
...  

OBJECTIVE Optimizing patient discharge after surgery has been shown to impact patient recovery and hospital/physician workflow and to reduce healthcare costs. In the current study, the authors sought to identify risk factors for nonroutine discharge after surgery for cervical myelopathy by using a national spine registry. METHODS The Quality Outcomes Database cervical module was queried for patients who had undergone surgery for cervical myelopathy between 2016 and 2018. Nonroutine discharge was defined as discharge to postacute care (rehabilitation), nonacute care, or another acute care hospital. A multivariable logistic regression predictive model was created using an array of demographic, clinical, operative, and patient-reported outcome characteristics. RESULTS Of the 1114 patients identified, 11.2% (n = 125) had a nonroutine discharge. On univariate analysis, patients with a nonroutine discharge were more likely to be older (age ≥ 65 years, 70.4% vs 35.8%, p < 0.001), African American (24.8% vs 13.9%, p = 0.007), and on Medicare (75.2% vs 35.1%, p < 0.001). Among the patients younger than 65 years of age, those who had a nonroutine discharge were more likely to be unemployed (70.3% vs 36.9%, p < 0.001). Overall, patients with a nonroutine discharge were more likely to present with a motor deficit (73.6% vs 58.7%, p = 0.001) and more likely to have nonindependent ambulation (50.4% vs 14.0%, p < 0.001) at presentation. On multivariable logistic regression, factors associated with higher odds of a nonroutine discharge included African American race (vs White, OR 2.76, 95% CI 1.38–5.51, p = 0.004), Medicare coverage (vs private insurance, OR 2.14, 95% CI 1.00–4.65, p = 0.04), nonindependent ambulation at presentation (OR 2.17, 95% CI 1.17–4.02, p = 0.01), baseline modified Japanese Orthopaedic Association severe myelopathy score (0–11 vs moderate 12–14, OR 2, 95% CI 1.07–3.73, p = 0.01), and posterior surgical approach (OR 11.6, 95% CI 2.12–48, p = 0.004). Factors associated with lower odds of a nonroutine discharge included fewer operated levels (1 vs 2–3 levels, OR 0.3, 95% CI 0.1–0.96, p = 0.009) and a higher quality of life at baseline (EQ-5D score, OR 0.43, 95% CI 0.25–0.73, p = 0.001). On predictor importance analysis, baseline quality of life (EQ-5D score) was identified as the most important predictor (Wald χ2 = 9.8, p = 0.001) of a nonroutine discharge; however, after grouping variables into distinct categories, socioeconomic and demographic characteristics (age, race, gender, insurance status, employment status) were identified as the most significant drivers of nonroutine discharge (28.4% of total predictor importance). CONCLUSIONS The study results indicate that socioeconomic and demographic characteristics including age, race, gender, insurance, and employment may be the most significant drivers of a nonroutine discharge after surgery for cervical myelopathy.


Author(s):  
Michael Brusco

Logistic regression is one of the most fundamental tools in predictive analytics. Graduate business analytics students are often familiarized with implementation of logistic regression using Python, R, SPSS, or other software packages. However, an understanding of the underlying maximum likelihood model and the mechanics of estimation are often lacking. This paper describes two Excel workbooks that can be used to enhance conceptual understanding of logistic regression in several respects: (i) by providing a clear formulation and solution of the maximum likelihood estimation problem; (ii) by showing the process for testing the significance of logistic regression coefficients; (iii) by demonstrating different methods for model selection to avoid overfitting, specifically, all possible subsets ordinary least squares regression and l1-regularized logistic regression (lasso); and (iv) by illustrating the measurement of relative predictor importance using all possible subsets.


Nephron ◽  
2021 ◽  
pp. 1-9
Author(s):  
Yong Pey See ◽  
Barnaby Edward Young ◽  
Li Wei Ang ◽  
Xi Yan Ooi ◽  
Chi Peng Chan ◽  
...  

<b><i>Introduction:</i></b> Acute kidney injury (AKI) in coronavirus infection disease (COVID-19) is associated with disease severity. We aimed to evaluate risk factors associated with AKI beyond COVID-19 severity. <b><i>Methods:</i></b> A retrospective observational study of COVID-19 patients admitted to a tertiary hospital in Singapore. Logistic regression was used to evaluate associations between risk factors and AKI (based on Kidney Disease Improving Global Outcomes criteria). Dominance analysis was performed to evaluate the relative importance of individual factors. <b><i>Results:</i></b> Seven hundred seven patients were included. Median age was 46 years (interquartile range [IQR]: 29–57) and 57% were male with few comorbidities (93%, Charlson Comorbidity Index [CCI] &#x3c;1). AKI occurred in 57 patients (8.1%); 39 were in AKI stage 1 (68%), 9 in stage 2 (16%), and 9 in stage 3 (16%). Older age (adjusted odds ratio [aOR] 1.04; 95% confidence interval [CI]: 1.01–1.07), baseline use of angiotensin-converting enzyme inhibitor (ACE-I) or angiotensin receptor blocker (ARB) (aOR 2.86; 95% CI: 1.20–6.83), exposure to vancomycin (aOR 5.84; 95% CI: 2.10–16.19), use of nonsteroidal anti-inflammatory drugs (NSAIDs) (aOR 3.04; 95% CI: 1.15–8.05), and severe COVID-19 with hypoxia (aOR 13.94; 95% CI: 6.07–31.98) were associated with AKI in the multivariable logistic regression model. The 3 highest ranked predictors were severe COVID-19 with hypoxia, vancomycin exposure, and age, accounting for 79.6% of the predicted variance (41.6, 23.1, and 14.9%, respectively) on dominance analysis. <b><i>Conclusion:</i></b> Severe COVID-19 is independently associated with increased risk of AKI beyond premorbid conditions and age. Appropriate avoidance of vancomycin and NSAIDs are potentially modifiable means to prevent AKI in patients with COVID-19.


2021 ◽  
pp. 1-10
Author(s):  
Emilia Schwertner ◽  
Renata Zelic ◽  
Juraj Secnik ◽  
Björn Johansson ◽  
Bengt Winblad ◽  
...  

Background: In Sweden, 2,296,000 firearms were legally owned by private persons in 2017 and there were 150,000 persons living with a dementia diagnosis. A proportion of these persons owning a firearm may pose safety concerns. Objective: The aim was to describe firearm ownership in persons with dementia in Sweden and examine which characteristics are explaining physicians’ decision to report a person to the police as unsuitable to possess a firearm. Methods: This was a registry-based observational study. 65,717 persons with dementia registered in the Swedish Dementia Registry were included in the study. Logistic regression was used to evaluate which of the persons’ characteristics were most important in predicting the likelihood of being reported as unsuitable to possess a firearm. Relative importance of predictors was quantified using standardized coefficients (SC) and dominance analysis (DA). Results: Out of 53,384 persons with dementia, 1,823 owned a firearm and 419 were reported to the police as unsuitable owners. Firearm owners were predominantly younger, males, living alone, and without assistance of homecare. The most important predictors of being reported to the police were: living with another person (SC = 0.23), frontotemporal dementia (SC = 0.18), antipsychotics prescription (SC = 0.18), being diagnosed in a memory/cognitive clinic (SC = –0.27), female gender (SC = 0.18), mild (SC = –0.25) and moderate (SC = –0.21) dementia, and hypnotics prescription (SC = 0.17). Conclusion: Firearm owners with dementia were mostly younger males who were still living more independent lives. The decision to remove a weapon was not solely based on a diagnosis of dementia but a combination of factors was considered.


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