scholarly journals MODEL DAN PELUANG TERJADINYA HUJAN BERDASARKAN KELEMBABAN MENGGUNAKAN REGRESI LOGISTIK BINER DI KABUPATEN MANOKWARI

2020 ◽  
Vol 16 (1) ◽  
pp. 34-37
Author(s):  
Inayatul Farach Ardianty ◽  
Indah Ratih Anggriyani
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Regression Estimation ◽  
Response Variable ◽  
Nominal Scale ◽  
Explanatory Variables ◽  
Logit Transformation ◽  
Scale Response ◽  
The Relationship ◽  
Categorical Scale

Manokwari Regrency has a tropical climate. This results in significant rainfall. One factor that stimulates rain is humidity. By using binary logistic regression, the model an chance of rainfall based on humidity can be determined. Logistic regression analysis is used to determine the relationship between categorical  scale response variables and numeric or categoric scale explanatory variables. If response variable used is nominal scale with  two possoble value (0 and 1), then it is called binary logistic regression. Estimation of the model  is done by logit  transformation. The model produce in this  study is g(x) = -23.443 + 0.289  humidity. The accuracy of the model is 70.4 percent and the probability of rain for humidity lowering one unit will be reduced to 0.74.

Ordinal logistic regression analysis of flight task ratings

2006 ◽  
Vol 110 (1109) ◽  
pp. 447-456
Author(s):  
R. Bradley ◽  
W. M. Maclaren
Keyword(s):  
Logistic Regression ◽  
Ordinal Logistic Regression ◽  
Practical Significance ◽  
Response Variable ◽  
Explanatory Variables ◽  
Ordinal Logistic Regression Analysis ◽  
Categorical Response ◽  
The Relationship ◽  
Ordered Categorical ◽  
Categorical Scale

Abstract The relationship between a pilot workload rating for a simulated flight task in the proximity of an offshore platform helideck and three experimental factors – wind speed, wind direction and pilot is investigated. The statistical method employed is ordinal logistic regression, which allows the specifying and fitting of regression relationships between ordered categorical response variables and explanatory variables. The response variable in this context is a pilot’s rating of the workload induced by certain flight tasks, measured on an ordered categorical scale 1 to 10. Estimates of the effects of the explanatory variables are given and their practical significance discussed.

scholarly journals Binary logistic regression to estimate household income efficiency. (south Darfur rural areas-Sudan)

2016 ◽  
Vol 4 (1) ◽  
pp. 31
Author(s):  
Sofian A. A. Saad ◽  
Amin Adam ◽  
Afra H. Abdelateef
Keyword(s):  
Logistic Regression ◽  
Rural Areas ◽  
Household Income ◽  
Household Head ◽  
Binary Logistic Regression ◽  
Statistical Technique ◽  
Household Expenditure ◽  
Response Variable ◽  
Explanatory Variables ◽  
Main Factors

<p>The main objective behind this study is to find out the main factors that affects the efficiency of household income in Darfur rejoin. The statistical technique of the binary logistic regression has been used to test if there is a significant effect of fife binary explanatory variables against the response variable (income efficiency); sample of size 136 household head is gathered from the relevant population. The outcomes of the study showed that; there is a significant effect of the level of household expenditure on the efficiency of income, beside the size of household also has significant effect on the response variable, the remaining explanatory variables showed no significant effects, those are (household head education level, size of household head own agricultural and numbers of students at school).</p>

scholarly journals Pemodelan Faktor-Faktor yang Mempengaruhi Jenis Kanker Payudara Menggunakan Regresi Logistik Biner (Kasus : Pasien Penderita Kanker Payudara di RSUP Dr. Wahidin Sudirohusodo tahun 2016).

2019 ◽  
Vol 1 (3) ◽  
pp. 40
Author(s):  
Titi Kurnianti HR ◽  
Muhammad Nadjib Bustan ◽  
R. Ruliana
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Statistical Analysis ◽  
Binary Logistic Regression ◽  
Breast Cancer Patients ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Independent Variables ◽  
Continuous Scale ◽  
Categorical Scale

Abstrak Regresi logistik adalah suatu metode analisis statistik yang diterapkan untuk memodelkan variabel dependen yang memiliki dua kategori atau lebih dengan satu atau lebih variabel independen. Regresi Logistik biner merupakan suatu analisis statistika yang digunakan untuk menganalisis hubungan antara satu atau lebih peubah bebas dengan peubah respon yang bersifat biner atau  dichotomous. Peubah bebas pada regresi logistik dapat berupa peubah skala kategorik maupun peubah yang skala kontinu sedangkan peubah respon berupa peubah berskala kategorik. Regresi Logistik Biner dapat diterapkan pada kasus kesehatan, khususnya pada penelitian ini yaitu mengenai kanker payudara. Sesuai uraian diatas maka penulis bermaksud untuk mengkaji dan melakukan penelitian  tentang Pemodelan Faktor-Faktor yang Mempengaruhi Jenis Kanker Payudara Menggunakan Regresi Logistik Biner (Kasus : Pasien Penderita Kanker Payudara di Rumah Sakit Umum Pusat Dr. Wahidin Sudirohusodo). Dari hasil analisis didapatkan bahwa peubah penjelas yang berpengaruh nyata terhadap jenis keganasan kanker terhadap pasien penderita kanker payudara adalah peubah Kemoterapi (X2) dan peubah Metastase (X5) yang masing-masing memiliki nilai odds rasio sebesar 0,17 dan 6,16.  Kata kunci : Kanker Payudara, Regresi Logistik, Regresi Logistik Biner. Abstract Logistic regression is a method of statistical analysis that is applied to model the dependent variable which has two or more categories with one or more independent variables. Binary Logistic Regression is a statistical analysis that is used to analyze the relationship between one or more independent variables with variable binary or dichotomous responses. The free variables in logistic regression can be either categorical scale or continuous scale variables while the response variables are categorical scale variables. Binary Logistic Regression can be applied to health cases, especially in this study, namely breast cancer. In accordance with the description above, the author intends to study and conduct research on Modeling Factors Affecting Types of Breast Cancer Using Binary Logistic Regression (Case: Patients with Breast Cancer Patients at Dr. Wahidin Sudirohusodo Central General Hospital). From the results of the analysis it was found that the explanatory variables that significantly affected the type of cancer malignancy in patients with breast cancer were Chemotherapy variables (X2) and Metastase variables (X5), each of which had odds ratio values of 0.17 and 6.16. Keywords: Breast Cancer, Logistic Regression, Binary Logistic Regression.

Abstract 3734: Presurgical fMRI and Morbidity Outcomes in Patients with Vascular Lesions

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Andrew C Radtke ◽  
Joshua Pankratz ◽  
Ryan Holdsworth ◽  
Dovile Baniulis ◽  
Nicole Kornder ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Preoperative Planning ◽  
Binary Logistic Regression ◽  
Vascular Lesion ◽  
Vascular Lesions ◽  
Motor Deficits ◽  
Binary Logistic Regression Analysis ◽  
Language Mapping ◽  
Motor Mapping ◽  
The Relationship

Background fMRI is being increasingly used as an adjunct imaging technique for preoperative planning for patients with various brain lesions. The proximity of the lesion to eloquent cortex is a major factor in guiding surgical planning. Our group has previously reported significant association between the distance between brain tumor periphery and area of fMRI activation (Lesion-Activation Distance; LAD) and morbidity and mortality outcomes. This study investigated the relationship between vascular lesion LAD and morbidity. Methods This study was a retrospective analysis of data from patients with vascular lesions [arteriovenous malformations (AVMs) (n=49), and cavernomas (n=57)], who had received fMRI as part of their preoperative planning. The preoperative fMRI included motor mapping (n=87) and/or language mapping (n=102). The fMRI paradigms were chosen based on observed preoperative weakness (aphasia, paresis) and anticipated functional areas of the brain that may be affected by treatment. Results Multiple logistic regression analyses showed that a model that combines Age and Language LAD was a significant predictor of postoperative deficits (p= 0.04). Broca’s LAD(1-2 cm) X Age was a significant predictor of postoperative deficits (change in odds ratio (OR) =0.82, CI:0.68-0.98). The relationship between Brocas’s LAD and postoperative aphasia and Broca’s LAD and pre and postoperative aphasia trended towards significance (p = .08 and p =.07 respectively). Wernicke’s LAD, independently or combined with Age, was not a significant predictor of postoperative deficits. Binary logistic regression analysis for SMC LAD and postop deficits did not reach significance (p =.10). There were no significant differences in postoperative language or motor deficits as a function of gender or handedness. Conclusions These results suggest that both age and the proximity of a vascular lesion to language LAD are factors that can help predict postoperative outcomes, especially for Broca’s LAD. The lack of similar results when investigating the relationship between Wernicke’s LAD and postoperative deficits suggests potential brain reorganization and/or robustness of this brain region. These results have implications for the potential use of fMRI as a presurgical tool for language mapping in patients with vascular lesions.

scholarly journals Loyalitas Konsumen Terhadap Konsumsi Kopi Tubruk di Meulaboh

2017 ◽  
Vol 2 (2) ◽  
pp. 147-155
Author(s):  
Dina Fida ◽  
Ismayani Ismayani ◽  
Fajri Jakfar
Keyword(s):  
Logistic Regression ◽  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Binary Logistic Regression ◽  
Validity And Reliability ◽  
Chi Square ◽  
Plantation Species ◽  
Long Time ◽  
Coffee Powder ◽  
The Relationship

Abstrak.Kopi adalah salah satu jenis tanaman perkebunan yang sudah lama dibudidayakan dan memiliki nilai ekonomi yang dapat menghasilkan keuntungan. Kopi tubruk merupakan kopi tradisional yang umumnya lebih keras karena bubuk kopi murni yang langsung diseduh dengan air  mendidih, teksturnya lebih kasar, lebih banyak mengandung ampas, aroma kopi yang lebih menyengat, serta tingkat kekentalan yang bisa disesuaikan dengan lidah penikmatnya. Loyalitas konsumen pada umumnya merupakan suatu sikap konsumen yang loyal terhadap pilihan dan penggunaan produk dalam waktu yang lama dan untuk masa yang akan datang, Sedangkan kepuasan konsumen ialah perasaan senang atau kecewa seseorang yang berasal dari perbandingan antara kesannya terhadap kinerja (hasil) sesuatu produk dengan harapannya. Pada penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi loyalitas konsumen terhadap minuman kopi tubruk di Meulaboh, Mengetahui hubungan antara tingkat kepuasan konsumen dengan loyalitas konsumen terhadap konsumsi kopi tubruk di Meulaboh.Adapun metode yang digunakan adalah Uji Validitas dan Reliabilitas,Regresi Logistik Biner dan Chi Square.Hasil Regresi Biner Logistik menunjukkan bahwa citarasa, harga, kualitas pelayanan dan lokasi merupakan faktor yang mempengaruhi loyalitas konsumen terhadap minuman kopi tubruk.Hasil Uji Chi-Square menunjukkan bahwa adanya hubungan yang signifikan antara kepuasan konsumen dengan loyalitas konsumen terhadap minuman kopi tubruk di Meulaboh.Consumer Loyality To The Consumption Of Coffee Brewed In MeulabohAbstract.Coffee is one of the plantation species has long been cultivated and have a mutually beneficial economic value.The brewed coffee is a traditional coffee are generally harder for pure coffee powder that instantly brewed with boiling water, rough texture, contains more dregs, pungent coffee aroma, as well as the level of consistency that can be adapted to the tongue of the audience.Consumer loyalty is generally a loyal consumer attitudes towards choice and use of the product for a long time and for the future.While customer satisfaction is feeling happy or disappointed someone who comes from a comparison between her impression of the performance (yield) of a product with expectations.In this study aims to determine the factors that influence consumer loyalty to the coffee beverage brewed in Meulaboh.Determine the relationship between the level of customer satisfaction and customer loyalty towards the consumption of instant coffee in Meulaboh.The methods used are validity and reliability, Binary Logistic Regression and Chi Square.Binary logistic regression results show that the simultaneous testing of the factors that influence loyalty is taste, price, service quality, and location. While testing only partially furnished variables that influence loyalty.Chi-Square test results indicate that there is a significant relationship between customer satisfaction and customer loyalty so that customer satisfaction is influenced flavors that suit the tastes of consumers. 

scholarly journals Relationship Between Unbound Bilirubin Levels and Acute Bilirubin Encephalopathy in Exchange Transfusion Neonates

2021 ◽  
Author(s):  
Yiyi Ding ◽  
Shuo Wang ◽  
Rui Guo ◽  
Aizhen Zhang ◽  
Yufang Zhu
Keyword(s):  
Logistic Regression ◽  
Blood Glucose ◽  
Odds Ratio ◽  
Exchange Transfusion ◽  
Binary Logistic Regression ◽  
P Value ◽  
Bilirubin Encephalopathy ◽  
Unbound Bilirubin ◽  
Independent Variable ◽  
The Relationship

Abstract BACKGROUND: Evidence regarding the relationship between unbound bilirubin levels and acute bilirubin encephalopathy was limited. Therefore, this study set out to investigate whether the unbound bilirubin level was independently related to acute bilirubin encephalopathy in children who underwent exchange transfusion after adjusting for other covariates. METHODS: A total of 46 neonates who underwent exchange transfusion were involved in The First People's Hospital Of Changde City in China from 2016-1-1 to 2018-12-31. The target independent variable and the dependent variable were unbound bilirubin levels measured at baseline and acute bilirubin encephalopathy respectively. Covariates involved in this study included sex, age, birth weight, blood glucose, red blood cell, hemolysis, receive phototherapy before exchange transfusion. RESULTS: The average gestational age of 46 selected participants was 38.6 ± 1.3 weeks old, the average age was 146.5 ± 86.9 hours old, 52.17% of them were male. Result of fully-adjusted binary logistic regression showed unbound bilirubin levels were positively associated with risk of acute bilirubin encephalopathy after adjusting confounders (Odds ratio = 1.41, 95% confidence intervals 1.05-1.91, P value <0.05). CONCLUSION: Unbound bilirubin levels are associated with neonatal acute bilirubin encephalopathy. The mechanism of unbound bilirubin levels leading to neonatal acute bilirubin encephalopathy needs to be further explored.

scholarly journals A Nonsymmetric Logit Model and Grouped Predictand Category Development

2014 ◽  
Vol 142 (8) ◽  
pp. 2991-3002 ◽  
Author(s):  
Bob Glahn
Keyword(s):  
Logistic Regression ◽  
Logit Model ◽  
Functional Form ◽  
Single Equation ◽  
Regression Estimation ◽  
Weather Event ◽  
Probability Estimates ◽  
The Relationship ◽  
Single Predictor ◽  
Category Development

Abstract Logistic regression is an alternative to regression estimation of event probabilities (REEP) and other techniques for estimating weather event probabilities based on NWP output or other predictors. Logistic regression has the advantage over REEP in that the probability estimates are constrained between zero and unity, whereas REEP can “overshoot” these values. It may be a detriment in some applications that the curves developed, one for each of several predictand categories (events), are symmetric. This paper shows how the logit curve can easily be made nonsymmetric as a function of a predictor, and thereby possibly achieve a better fit to the data. As with REEP, the probabilities estimated by logistic regression for each of several categories of a variable may not be consistent. For instance, the probability of snow &gt; 2 in. may exceed the probability of snow &gt; 1 in. Such inconsistencies can be avoided by developing a single equation involving all predictand categories and including another predictor that is a function of the predictand. This effectively, for a single predictor, produces parallel curves separated along the predictor axis but imposes restrictions on the equations and probabilities produced from them. The relationship between the predictor(s) and the predictand must be considered in determining the functional form. With only one predictor, defining the function is relatively straightforward. However, with multiple predictors, the process is more problematic. This paper demonstrates an alternative to imposing a functional form by using binary predictors. This formulation also achieves the goal of producing consistent forecasts and generalizes more readily to multiple predictors.

scholarly journals PEMODELAN DAYA TAHAN BELAJAR MAHASISWA PENDIDIKAN TINGGI JARAK JAUH DENGAN PENDEKATAN REGRESI LOGISTIK BINER (STUDI KASUS: MAHASISWA FAKULTAS EKONOMI JURUSAN MANAJEMEN)

2011 ◽  
Vol 12 (2) ◽  
pp. 57-67
Author(s):  
Dewi Juliah Ratnaningsih
Keyword(s):  
Logistic Regression ◽  
Binary Data ◽  
Study Time ◽  
Statistical Data Analysis ◽  
Grade Point ◽  
First Semester ◽  
Explanatory Variables ◽  
The Relationship ◽  
Length Of Study

Students’ persistence is the ability of students to survive in carrying out the study. In Universitas Terbuka (UT), there are no real dropped out student, but there are considered as non-active or non persistence students. Length of study time among UT’s students can be divided into binary data categories, which are valued as persistence (1) and non persistence (0). Logistic regression analysis is one type of statistical data analysis to be used for binary data. The purposes of writing this article are to identify the factors which influence the length of study time among students of the Department of Management, Faculty of Economics in UT, and to determine appropriate model in order to explain the relationship between the response variables (length of study time) with explanatory variables using logistic regression. The method used in this research is a case study with a number of samples as 2,936 college students. The result of the study shows that the factors influence the length of study time with alpha levels 0.05 are: age, the number of the courses taken, the employment status of the student, the participation in tutorials, the first semester achievement index, and the cumulative grade point.

scholarly journals ANALISIS KURVA ROC PADA MODEL LOGIT DALAM PEMODELAN DETERMINAN LANSIA BEKERJA DI KAWASAN TIMUR INDONESIA

2020 ◽  
Vol 4 (1) ◽  
pp. 116-135
Author(s):  
Muhammad Rizqi Fachrian Nur ◽  
Siskarossa Ika Oktora
Keyword(s):  
Logistic Regression ◽  
Health Insurance ◽  
Elderly Population ◽  
Descriptive Analysis ◽  
Binary Logistic Regression ◽  
The Elderly ◽  
Family Status ◽  
Explanatory Variables ◽  
The Status ◽  
Elementary School Education

Binary logistic regression is used for probability modeling or to predict binary response variables (Success / Failure) from one or more explanatory variables that are continuous or categorical. In carrying out this analysis, there are several ways to test the suitability of the resulting model, and one of them is the area under the ROC curve. The application of the analysis method in this study is the determinant of the elderly population to work. The population of the elderly in Indonesia is increasing every year. Many views that the elderly depend on other residents, especially in terms of the economy. However, if seen from the percentage of elderly working in Indonesia, it is increasing, including the elderly in KTI. The purpose of this study is to determine the characteristics of the elderly in KTI, know the factors that influence the decision of the elderly population to work in KTI and find out the tendency of variables that affect the decision of the elderly to work in KTI. The data used are raw data from Badan Pusat Statistik (BPS) was Survei Sosial Ekonomi Nasional (Susenas) Kor March 2018. This study using descriptive analysis methods and binary logistic regression. The results are that the variables that significantly influence the decisions of the elderly to work are residence, gender, age, education, family status, marital status, health complaints, and health insurance. Elderly who has characteristics residing in rural, male sex, classified as young elderly (60-69 years old), has the highest level of elementary school education, has the status of KRT in his family, is married, has no complaints health, and not having health insurance will have a greater tendency to decide to work.  

scholarly journals Global and local corporate social responsibility: a study of foreign entry mode choice in Spanish quoted firms

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Francisco José Mas-Ruiz ◽  
Carla Rodriguez-Sanchez ◽  
Franco Manuel Sancho-Esper ◽  
Esther de Quevedo-Puente
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Ad Hoc ◽  
Entry Mode ◽  
Binary Logistic Regression ◽  
Content Type ◽  
Explanatory Variables ◽  
Foreign Entry ◽  
Corporate Social ◽  
The Relationship

PurposeThis study examines the relationships between the foreign entry mode (FEM) used by a company, its global corporate social responsibility (CSR) and the host country's local CSR environment in Spanish quoted firms. Additionally, it seeks to explore the moderating role of the host country's CSR in the relationship between firm's global CSR and FEM.Design/methodology/approachTo test the proposed hypotheses, binary logistic regression is used with a sample of 418 foreign direct investment (FDI) operations between 2002 and 2008. This period is chosen with the aim of knowing what happened after the boom in Spanish investments abroad in the 1990s and the uncertainty of the early 2000s.FindingsThe results reveal firm patterns of behaviour regarding the FEM of companies and the two types of CSR according to the proposed hypotheses. Furthermore, it is found that the host country's local CSR may not only have a direct influence on the FEM decision but may also moderate the relationship between the firm's global CSR and firm's entry mode in a host country.Originality/valueThis is one of the first studies to propose as explanatory variables of FEM two types of CSR (firm's global CSR and host country's local CSR). This has been possible by the creation of an ad-hoc database with data from different information sources of FDI (Instituto Español de Comercio Exterior) and CSR [Eikon™ and AccountAbility National Corporate Responsibility Index (NCRI)].

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