Detection of Conditional Dependence Between Multiple Variables Using Multiinformation

2021 ◽  
pp. 677-690
Author(s):  
Jan Mielniczuk ◽  
Paweł Teisseyre
Keyword(s):  
Conditional Dependence ◽  
Multiple Variables

Abusive Men's Use of Children to Control Their Partners and Ex-Partners

2007 ◽  
Vol 12 (1) ◽  
pp. 54-61 ◽  
Author(s):  
Marisa L. Beeble ◽  
Deborah Bybee ◽  
Cris M. Sullivan
Keyword(s):  
United States ◽  
Intimate Partner Violence ◽  
Partner Violence ◽  
Emotional Abuse ◽  
The United States ◽  
Intimate Partner ◽  
Anecdotal Evidence ◽  
Multiple Variables ◽  
The Relationship

While research has found that millions of children in the United States are exposed to their mothers being battered, and that many are themselves abused as well, little is known about the ways in which children are used by abusers to manipulate or harm their mothers. Anecdotal evidence suggests that perpetrators use children in a variety of ways to control and harm women; however, no studies to date have empirically examined the extent of this occurring. Therefore, the current study examined the extent to which survivors of abuse experienced this, as well as the conditions under which it occurred. Interviews were conducted with 156 women who had experienced recent intimate partner violence. Each of these women had at least one child between the ages of 5 and 12. Most women (88%) reported that their assailants had used their children against them in varying ways. Multiple variables were found to be related to this occurring, including the relationship between the assailant and the children, the extent of physical and emotional abuse used by the abuser against the woman, and the assailant's court-ordered visitation status. Findings point toward the complex situational conditions by which assailants use the children of their partners or ex-partners to continue the abuse, and the need for a great deal more research in this area.

Product Brand Loyalty and Purchase Decision

2020 ◽  
Vol 3 (3) ◽  
pp. 76-87
Author(s):  
Muhammad Naeem ◽  
Abdul Sami
Keyword(s):  
Brand Loyalty ◽  
Quantitative Research ◽  
Research Study ◽  
Positive Association ◽  
Perceived Quality ◽  
Purchase Decision ◽  
Cross Sectional ◽  
Business World ◽  
Multiple Variables ◽  
The Relationship

The present study was an examination of the relationship between product brand loyalty and purchase decision of automotive customers. The study focused on comparative analysis of two famous brands of automobile i-e Honda City and Toyota Corolla Xli and the various effects of product brand loyalty on purchase decision of automotive customers. A cross sectional quantitative research design was employed in the research study. In today’s competitive business world, now most of the marketers and manufacturers of various brands have encountered with multiple variables through which they can not only influence the purchase decision of their customers but also secure their buying preferences. The variables that are used and relevant to this study are product brand loyalty, perceived quality, price, and purchase decision. During examination of the relationship between these variables, study investigated that there is a positive association between product brand loyalty, product perceived quality, price and purchase decision.

Acute Colonic Diverticulitis: Diagnostic Evidence, Demographic and Clinical Features in ree Practice Settings

2014 ◽  
Vol 23 (4) ◽  
pp. 379-386 ◽  
Author(s):  
Rajan Iyer ◽  
George F. Longstreth ◽  
Li-Hao Chu ◽  
Wansu Chen ◽  
Linnette Yen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Emergency Department ◽  
Clinical Features ◽  
Clinical Characteristics ◽  
Past History ◽  
Colonic Diverticulitis ◽  
Co Morbidity ◽  
Objective Evidence ◽  
Multiple Variables ◽  
Acute Colonic Diverticulitis

Background & Aims: Diverticulitis is often diagnosed in outpatients, yet little evidence exists on diagnostic evidence and demographic/clinical features in various practice settings. We assessed variation in clinical characteristics and diagnostic evidence in inpatients, outpatients, and emergency department cases and effects of demographic and clinical variables on presentation features.Methods: In a retrospective cohort study of 1749 patients in an integrated health care system, we compared presenting features and computed tomography findings by practice setting and assessed independent effects of demographic and clinical factors on presenting features.Results: Inpatients were older and more often underweight/normal weight and lacked a diverticulitis past history and had more comorbidities than other patients. Outpatients were most often Hispanic/Latino. The classical triad (abdominal pain, fever, leukocytosis) occurred in 78 (38.6%) inpatients, 29 (5.2%) outpatients and 34 (10.7%) emergency department cases. Computed tomography was performed on 196 (94.4%) inpatients, 110 (9.2%) outpatients and 296 (87.6%) emergency department cases and was diagnostic in 153 (78.6%) inpatients, 62 (56.4%) outpatients and 243 (82.1%) emergency department cases. Multiple variables affected presenting features. Notably, female sex had lower odds for the presence of the triad features (odds ratio [95% CI], 0.65 [0.45-0.94], P<0.05) and increased odds of vomiting (1.78 [1.26-2.53], P<0.01). Patients in age group 56 to 65 and 66 or older had decreased odds of fever (0.67 [0.46-0.98], P<0.05) and 0.46 [0.26-0.81], P<0.01), respectively, while ≥1 co-morbidity increased the odds of observing the triad (1.88 [1.26-2.81], P<0.01).Conclusion: There was little objective evidence for physician-diagnosed diverticulitis in most outpatients. Demographic and clinical characteristics vary among settings and independently affect presenting features.Abbreviations: AD: acute colonic diverticulitis; BMI: body mass index; CT: computed tomography; ED: emergency department; IBS: irritable bowel syndrome; ICD-9-CM: International Classification of Diseases, 9th Revision, Clinical Modification; IP: inpatient; KPSC: Kaiser Permanente Southern California; OP: outpatient.

scholarly journals “P3”: an adaptive modeling tool for post-COVID-19 restart of surgical services

JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Divya Joshi ◽  
Ali Jalali ◽  
Todd Whipple ◽  
Mohamed Rehman ◽  
Luis M Ahumada
Keyword(s):  
Data Warehouse ◽  
Predictive Analytics ◽  
Surgical Patient ◽  
Protective Equipment ◽  
Operating Room Personnel ◽  
Surgical Services ◽  
Multiple Variable ◽  
Multiple Variables ◽  
Using Data ◽  
User Friendly

Abstract Objective To develop a predictive analytics tool that would help evaluate different scenarios and multiple variables for clearance of surgical patient backlog during the COVID-19 pandemic. Materials and Methods Using data from 27 866 cases (May 1 2018–May 1 2020) stored in the Johns Hopkins All Children’s data warehouse and inputs from 30 operations-based variables, we built mathematical models for (1) time to clear the case backlog (2), utilization of personal protective equipment (PPE), and (3) assessment of overtime needs. Results The tool enabled us to predict desired variables, including number of days to clear the patient backlog, PPE needed, staff/overtime needed, and cost for different backlog reduction scenarios. Conclusions Predictive analytics, machine learning, and multiple variable inputs coupled with nimble scenario-creation and a user-friendly visualization helped us to determine the most effective deployment of operating room personnel. Operating rooms worldwide can use this tool to overcome patient backlog safely.

scholarly journals The Correlation amongst Salty Taste Preference and Overactive Bladder Symptoms in Female Individuals

2021 ◽  
Vol 18 (2) ◽  
pp. 518
Author(s):  
Jin-Won Noh ◽  
Kyoung-Beom Kim ◽  
Jae Heon Kim ◽  
Young Dae Kwon
Keyword(s):  
Dietary Habits ◽  
Sodium Intake ◽  
Taste Preference ◽  
Close Correlation ◽  
Design Data ◽  
Cross Sectional ◽  
Salty Taste ◽  
Multiple Variables ◽  
Storage Symptom ◽  
And Storage

Sodium intake could have an indirect effect on storage symptoms as it is an established fact that it has a correlation to hypertension (HTN). However, clinical support for the correlation of sodium intake to STORAGE symptom remains scarce. Therefore, the present work sought to determine how sodium intake and OAB symptom seriousness were correlated in female individuals based on a cross-sectional research design. Data from 115,578 respondents chosen from 228,921 individuals enrolled in the Korean Community Health Survey (KCHS) were subjected to cross-sectional analysis. The correlation amongst sodium intake and STORAGE symptom was assessed on the basis of estimates of the incidence rate ratio (IRR) with 95% confidence interval (CI). Furthermore, joint correspondence analysis (JCA) was conducted to investigate how a predilection for salty taste was associated with several factors, including STORAGE symptom, socio-economic factors, comorbidities, and dietary habits. By comparison to respondents indicating a neutral predilection for salty taste, those who indicated a predilection for bland and salty taste were 7.1% (IRR = 1.071, p < 0.001, 95% CI = 1.045–1.097) and 20.5% (IRR = 1.205, p < 0.001, 95% CI = 1.177–1.234) more probable to experience severe STORAGE symptom, within an adjusted model with multiple variables. JCA confirmed the existence of a correlation between predilection for salty taste and STORAGE symptom. A close correlation was established to exist between predilection for salty taste and lower urinary tract symptoms (LUTS), such as voiding and storage symptoms and nocturia. Moreover, sodium intake was found to be a risk factor for LUTS seriousness in both excessive and deficient amount.

scholarly journals Modeling the Conditional Dependence between Discrete and Continuous Random Variables with Applications in Insurance

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 45
Author(s):  
Emilio Gómez-Déniz ◽  
Enrique Calderín-Ojeda
Keyword(s):  
Structural Model ◽  
Medical Expenditure Panel Survey ◽  
Health Care Use ◽  
Medical Expenditure ◽  
Panel Survey ◽  
Conditional Distributions ◽  
Conditional Dependence ◽  
Outpatient Visits ◽  
Conditional Expectations ◽  
The U.S

We jointly model amount of expenditure for outpatient visits and number of outpatient visits by considering both dependence and simultaneity by proposing a bivariate structural model that describes both variables, specified in terms of their conditional distributions. For that reason, we assume that the conditional expectation of expenditure for outpatient visits with respect to the number of outpatient visits and also, the number of outpatient visits expectation with respect to the expenditure for outpatient visits is related by taking a linear relationship for these conditional expectations. Furthermore, one of the conditional distributions obtained in our study is used to derive Bayesian premiums which take into account both the number of claims and the size of the correspondent claims. Our proposal is illustrated with a numerical example based on data of health care use taken from Medical Expenditure Panel Survey (MEPS), conducted by the U.S. Agency of Health Research and Quality.

scholarly journals Comparison of Prediction Models for Mortality Related to Injuries from Road Traffic Accidents after Correcting for Undersampling

2021 ◽  
Vol 18 (11) ◽  
pp. 5604
Author(s):  
Yookyung Boo ◽  
Youngjin Choi
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
National Level ◽  
Brier Score ◽  
Support Vector ◽  
Main Diagnosis ◽  
Road Traffic Accidents ◽  
Multiple Variables ◽  
Type Of Injury ◽  
Kernel Model

In this study, four models—logistic regression (LR), random forest (RF), linear support vector machine (SVM), and radial basis function (RBF)-SVM—were compared for their accuracy in determining mortality caused by road traffic injuries. They were tested using five years of national-level data from the Korea Disease Control and Prevention Agency’s (KDCA) National Hospital Discharge In-Depth Survey (2013 through to 2017). Model performance was measured for accuracy, precision, recall, F1 score, and Brier score metrics using classification analysis that included characteristics of patients, accidents, injuries, and illnesses. Due to the number of variables and differing units, the rates of survival and mortality related to road traffic accidents were imbalanced, so the data was corrected and standardized before the classification models’ performances were compared. Using the importance analysis, the main diagnosis, the type of injury, the site of the injury, the type of injury, the operation status, the type of accident, the role at the time of the accident, and the sex were selected as the analysis factors. The biggest contributing factor was the role in the accident, which is the driver, and the major sites of the injuries were head injuries and deep injuries. Using selected factors, comparisons of the classification performance of each model indicated RBF-SVM and RF models were superior to the others. Of the SVM models, the RBF kernel model was superior to the linear kernel model; it can be inferred that the performance of the high-dimensional transformed RBF model is superior when the dimension is complex because of the use of multiple variables. The findings suggest there are limitations to analyses involving imbalanced, multidimensional original data, such as data on road traffic mortality. Thus, analyses must be performed after imbalances are corrected.

scholarly journals Proposed Framework for Comparison of Continuous Probabilistic Genotyping Systems amongst Different Laboratories

2021 ◽  
Vol 1 (1) ◽  
pp. 33-45
Author(s):  
Dennis McNevin ◽  
Kirsty Wright ◽  
Mark Barash ◽  
Sara Gomes ◽  
Allan Jamieson ◽  
...  
Keyword(s):  
Numerical Methods ◽  
Analytical Solutions ◽  
Peak Height ◽  
Dna Profiling ◽  
Likelihood Ratios ◽  
Dna Mixtures ◽  
Individual Laboratory ◽  
Multiple Variables

Continuous probabilistic genotyping (PG) systems are becoming the default method for calculating likelihood ratios (LRs) for competing propositions about DNA mixtures. Calculation of the LR relies on numerical methods and simultaneous probabilistic simulations of multiple variables rather than on analytical solutions alone. Some also require modelling of individual laboratory processes that give rise to electropherogram artefacts and peak height variance. For these reasons, it has been argued that any LR produced by continuous PG is unique and cannot be compared with another. We challenge this assumption and demonstrate that there are a set of conditions defining specific DNA mixtures which can produce an aspirational LR and thereby provide a measure of reproducibility for DNA profiling systems incorporating PG. Such DNA mixtures could serve as the basis for inter-laboratory comparisons, even when different STR amplification kits are employed. We propose a procedure for an inter-laboratory comparison consistent with these conditions.

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