scholarly journals ANALISIS JUMLAH KASUS MALARIA DI WILAYAH SUMATERA MENGGUNAKAN GEOGRAPHICALLY WEIGHTED ZERO-INFLATED POISSON REGRESSION (GWZIPR)

2020 ◽  
Vol 4 (4) ◽  
pp. 638-648
Author(s):  
Rahmat Kevin Praditia ◽  
Dian Agustina ◽  
Dyah Setyo Rini
Keyword(s):  
Poisson Regression ◽  
Predictor Variable ◽  
Regression Method ◽  
Health Centers ◽  
Logit Models ◽  
Factors Affecting ◽  
Spatial Factor ◽  
Distribution Mapping ◽  
Geographical Locations ◽  
Better Than

A method that can be used if there is a spatial factor and if overdispersion happens in a count data is Geographically Weighted Zero-Inflated Poisson Regression (GWZIPR). This research aimed to analyze the number of malaria cases in every regency/city of Sumatra Land using the GWZIPR method and distribution mapping of factors affecting the number of malaria cases in Sumatra Land. Data involved in this research was the number of malaria cases as the response variable and the predictor variable as a percentage of households that have access to proper sanitation, a percentage of households that have access to proper water resources, and a percentage of the number of public health centers. The results were for each area which had distinctive models based on significant variables. The distribution mapping of factors affecting the number of malaria cases in every regency/city was commonly divided into three groups based on significant variables on ln and logit models. The mapping did not shape a spreading pattern or each regency/city in that group because the geographical locations were close to each other. GWZIPR method in this research was better than the ZIP Regression method because it produced the least AIC value.

scholarly journals PENERAPAN REGRESI GENERALIZED POISSON UNTUK MENGATASI FENOMENA OVERDISPERSI PADA KASUS REGRESI POISSON

2013 ◽  
Vol 2 (2) ◽  
pp. 49
Author(s):  
I PUTU YUDANTA EKA PUTRA ◽  
I PUTU EKA NILA KENCANA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Poisson Regression ◽  
Discrete Data ◽  
Mean Value ◽  
Regression Method ◽  
Response Variable ◽  
Generalized Poisson ◽  
The Mean ◽  
Generalized Poisson Regression ◽  
Better Than

The Poisson regression is generally used to analyze the response variable that is a discrete data. Poisson regression has assumption which must be met, that is condition equidispersion. But in fact this assumption is often violated, that is the value of the variance is greater or less than the mean value. The condition when value of the variance is greater than the mean value is called overdispersion. One method that can be used for overdispersion data is Generalized Poisson regression. In this research, it was found that the Generalized Poisson regression method was better than Poisson regression method.

scholarly journals SURG-22. CUSHING’S DISEASE: A DIFFICULT TO TREAT NEURO-ONCOLOGICAL CONDITION

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi244-vi244
Author(s):  
Santanu Bora ◽  
Ashish Suri
Keyword(s):  
Cortisol Level ◽  
Remission Rate ◽  
Univariate Analysis ◽  
Clinical Manifestations ◽  
Plasma Cortisol Level ◽  
Cushing Disease ◽  
Factors Affecting ◽  
Microscopic Surgery ◽  
Acth Secreting ◽  
Better Than

Abstract BACKGROUND Cushing disease (CD) comprises a spectrum of clinical manifestations secondary to hypercortisolism due to ACTH-secreting pituitary adenoma. Transsphenoidal adenomectomy remains the standard treatment. Because of the significant rate of recurrence or persistence of CD, it is of interest to determine factors that may correlate with long-term outcomes following surgical intervention. OBJECTIVE The objective of our study is to determine the remission rate after surgery with special emphasis on factors affecting remission. METHODS Data of all patients undergoing surgery for CD from 2009 to 2017 was analyzed retrospectively. Transphenoidal resection was the preferred treatment with a recent trend in favor of endonasal endoscopic skull base approach. Post-operative cortisol level of < 2 μg/dL was taken as remission and value between 2 and 5 μg/dL as possible remission. RESULTS 104 patients operated primarily for CD were included for analysis. 47 patients underwent microscopic surgery, 55 endoscopic surgery and two were operated trans-cranially. Remission was achieved in 76.47% of patients. In univariate analysis, factors significantly associated with remission were (1) type of surgery (p=0.01); endoscopy (88.23% remission) better than microscopy (56.6% remission) (2) postoperative day-1 morning cortisol (p=0.004) and; (3) postoperative day-1 morning ACTH (p=0.015). In multivariate analysis, however only postoperative day-1 cortisol was found to be significant as predictor of remission (p=0.02). CONCLUSION Postoperative plasma cortisol level is a strong independent predictor of remission and value less than 10.7µgm/dl can be taken as cut off for predicting remission. Remission provided by endoscopy appears to be significantly better than microscopic approach.

scholarly journals Investigating the status of marital burnout and related factors in married women referred to health centers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mahbobeh Nejatian ◽  
Ali Alami ◽  
Vahideh Momeniyan ◽  
Ali Delshad Noghabi ◽  
Alireza Jafari
Keyword(s):  
Marital Satisfaction ◽  
Significant Relationship ◽  
Married Couples ◽  
Married Women ◽  
Health Centers ◽  
Related Factors ◽  
Factors Affecting ◽  
The Status ◽  
Multistage Sampling ◽  
Emotional Burnout

Abstract Background Marital burnout is an important issue in marriage and many factors play an important role in this phenomenon. The aim of this study was to determine the status of marital burnout and the factors affecting married women who were referred to health centers because of it. Methods In this study, 936 women were selected by multistage sampling and data collection was performed using questionnaires of demographic and couple burnout. Data analysis was performed using SPSS software version 24. Results The mean (± SD) of marital burnout, in this study, was 55.46 (± 18.03) (out of 147 score). There was a significant relationship between the level of women's education with total marital burnout, and the subscales of somatic and emotional burnout (P < 0.05). A significant relationship was also observed between mandatory marriage and total marital burnout, as well as subscales of somatic, emotional, and psychological burnout (P < 0.05). A significant relationship was detected and observed between women's participation in training courses of communication skills and total marital burnout, inclusive of the subscales regarding psychological burnout (P < 0.05). The results of linear regression showed a significant relationship between mandatory in marriage, marital satisfaction, marriage duration, and husband's level of education with women's marital burnout. The variables were finally able to predict 12% of marital burnout variance. It should be noted that marital satisfaction had a higher effect on predicting marital burnout (P < 0.001). Conclusions Marital satisfaction was one of the effective factors in predicting marital burnout, so it can be concluded that it is necessary to pay more attention to this issue. Educational programs and examining the factors that enhance marital satisfaction are needed to prevent and reduce marital burnout in married couples.

scholarly journals ANALYSIS OF FACTORS AFFECTING THE PRICE FLUCTUATION OF CAYENNE PEPPER IN MALANG REGENCY

2021 ◽  
Vol 5 (1) ◽  
pp. 19-26
Author(s):  
Nurul Laili ◽  
Sri Hindarti ◽  
Dwi Susilowati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Research Method ◽  
Commodity Prices ◽  
Secondary Data ◽  
Regression Method ◽  
Linear Regression Method ◽  
Factors Affecting ◽  
Independent Variables ◽  
Multiple Linear Regression Method

 This study aims to 1) Analyze the pattern of changes in commodity prices for spanish pepper in Malang District. 2) Analyzing the factors that influence fluctuations in the price of spanish pepper in Malang District. The research method used is quantitative method that uses secondary data in the form of time series obtained from several related agencies, namely the Central Statistics Agency of Malang District, Department of Industry and Trade, and Department of food crops, horticulture, and plantation in Malang District. Analysis of the data used is multiple linear regression with the dependent variable is the price at the consumer level from 2009-2018, while the independent variables use the data of the price of spanish pepper at the producer level, the amount of production, and the amount of consumption from 2009-2018. The study found that: 1) The development of the price of spanish pepper had a trend that tended to increase during the last 10 years. 2) From the results of data processing using multiple linear regression method with Eviews 9.0 application, it is found that the factor that significantly influences changes in the price of spanish pepper is the price at the producer level, while the amount of production of spanish pepper and the number of requests does not significantly affect the change in spanish pepper prices in Malang District. 

scholarly journals Factors affecting net interest margin of joint-stock commercial banks in Vietnam

2017 ◽  
Vol 24 (01) ◽  
pp. 92-103
Author(s):  
An Pham Hoang ◽  
Loan Vo Thi Kim
Keyword(s):  
Commercial Banks ◽  
Secondary Data ◽  
Regression Method ◽  
Factors Affecting ◽  
Managerial Efficiency ◽  
Net Interest Margin ◽  
Panel Data Regression ◽  
Data Regression ◽  
Negative Effect ◽  
Interest Margin

This study analyzes factors affecting net interest margin of joint-stock commercial banks in Vietnam. The paper uses the secondary data of 26 banks with 182 observations for the period of 2008–2014 and applies the panel data regression method. The empirical results indicate that lending scale, credit risk, capitalization, and in-terest rate have positive impacts on net interest margin. In contrast, managerial efficiency has a negative effect on net interest margin. However, bank size and loan to deposit ratio are statistically insig-nificant to net interest margin.

Application of Machine Learning in Predicting Crude Oil Production Volume

2021 ◽  
Author(s):  
Okechukwu Prince Innocent
Keyword(s):  
Machine Learning ◽  
Crude Oil ◽  
Predictor Variable ◽  
Oil Production ◽  
Water Volume ◽  
Production Volume ◽  
Affecting Factors ◽  
Factors Affecting ◽  
Crude Oil Production ◽  
The Relationship

Abstract The production of oil is of great and immense significance as a source of energy worldwide. The major factors affecting the production volume of oil is classified into two groups namely the geological and the human factor. Each group comprises of factors affecting oilfield production volume. The challenge in this project is to find the variable for the crude oil production volume in an oilfield because there are numerous factors affecting the crude oil production volume in an oilfield. The objective of this paper is to provide a more accurate and efficient solution on how to predict the oil production volume. Furthermore, Machine Learning algorithm called Multiple Linear Regression was developed using Python programming Language to predict the production volume of oil in an oilfield. The model was developed and fitted to train and test the factors that affect and influence the oil production volume. After a several studies have been made, the affecting factors were provided from the oilfield which would be trained and tested in order to model the relationship between predictor variable and response variable which are the significant affecting factors and the oil production volume respectively. The predictor variables are the startup number of wells, the recovery percent of previous year, the injected water volume of previous year and the oil moisture content of previous year. The predictor variable is the oil production volume. Moreover, the model was found to possess greater utility in predicting the production volume of oil as it yielded an oil production volume output with an accuracy of 98 percent. The relationship between oil production volume and the affecting factors was observed and drawn to a perfect conclusion. This model can be of immense value in the oil and gas industry if implemented because of its ability to predict oilfield output more accurately. It is an invaluable and very efficient model for the oilfield manager and oil production manager.

A Framework to Analyze Variation of the Satisfaction of Patients for Outpatient Needs

2016 ◽  
pp. 227-241
Author(s):  
Arnab Jana ◽  
Noboru Harata
Keyword(s):  
Daily Activity ◽  
Positive Impact ◽  
Activity Analysis ◽  
Health Centers ◽  
Enabling Factors ◽  
Factors Affecting ◽  
Seeking Behavior ◽  
Care Activity ◽  
Healthcare Seeking Behavior ◽  
Health Care Activity

This study explored outpatient healthcare seeking behavior in India and estimated predisposing and enabling factors that influenced the satisfaction derived from the health care activity. The study assumed that if these gaps are fulfilled in the local facilities, this might invigorate lesser popular public providers within the neighborhood. The study was conducted in the state of West Bengal India. A multilevel framework was developed to incorporate factors affecting the satisfaction of the healthcare activity. Analysis revealed dependency on regional facilities and extensive traveling. Excessive traveling affected satisfaction negatively whereas in cases where respondent availed services from local primary health centers had positive impact on satisfaction. On the route to daily activity, ability to visit referred facility and visit to facility with modern amenities often triggered satisfaction. Segmented policy designed to fulfill these preferences might be indispensable to enhance local sufficiency.

A Framework to Analyze Variation of the Satisfaction of Patients for Outpatient Needs

2015 ◽  
Vol 4 (1) ◽  
pp. 21-35
Author(s):  
Arnab Jana
Keyword(s):  
West Bengal ◽  
Positive Impact ◽  
Health Centers ◽  
Enabling Factors ◽  
Factors Affecting ◽  
Primary Health ◽  
Seeking Behavior ◽  
Care Activity ◽  
Healthcare Seeking Behavior ◽  
Health Care Activity

This study explored outpatient healthcare seeking behavior in India and estimated predisposing and enabling factors that influenced the satisfaction derived from the health care activity. The study assumed that if these gaps are fulfilled in the local facilities, this might invigorate lesser popular public providers within the neighborhood. The study was conducted in the state of West Bengal India. A multilevel framework was developed to incorporate factors affecting the satisfaction of the healthcare activity. Analysis revealed dependency on regional facilities and extensive traveling. Excessive traveling affected satisfaction negatively whereas in cases where respondent availed services from local primary health centers had positive impact on satisfaction. On the route to daily activity, ability to visit referred facility and visit to facility with modern amenities often triggered satisfaction. Segmented policy designed to fulfill these preferences might be indispensable to enhance local sufficiency.

Factors Affecting the Toxicity of Glyphosate Applied in the Recirculating Sprayer to Johnsongrass (Sorghum halepense)and Soybeans (Glycine max)

Weed Science ◽  
1980 ◽  
Vol 28 (1) ◽  
pp. 59-63 ◽  
Author(s):  
C. G. McWhorter ◽  
J. R. Williford
Keyword(s):  
Glycine Max ◽  
Field Experiments ◽  
Sorghum Halepense ◽  
Soybean Yield ◽  
Factors Affecting ◽  
Over The Top ◽  
Uniform Droplet ◽  
Better Than

Field experiments were conducted to determine optimum nozzle settings for applying glyphosate [N-(phosphonomethyl)glycine] in the recirculating sprayer for postemergence control of johnsongrass [Sorghum halepense(L.) Pers.] in soybeans [Glycine max(L.) Merr.]. Herbicide sprays were directed across the row to johnsongrass growing taller than soybeans in July and August. Herbicide not sprayed on johnsongrass was trapped and reused. Glyphosate at 0.56, 1.12, and 2.24 kg/ha applied with commercially available 25° spray nozzles provided johnsongrass control and soybean yields equal to those following applications with specialized uniform droplet nozzles. Glyphosate at 1.7 kg/ha applied in the recirculating sprayer using only one nozzle per row provided control of johnsongrass equal to or better than that from applications made with two, three, or four nozzles per row. Soybean yield following application of glyphosate at 1.7 kg/ha with one nozzle per row was equal to yields obtained following its application with two, three, or four nozzles per row, with or without surfactant at 0.1% in spray solutions. Soybean yield was higher with four nozzles per row than with one nozzle per row when 0.5% surfactant was included in spray solutions. Soybean injury was lower and yield was higher when glyphosate was applied in the recirculating sprayer rather than over-the-top with a conventional sprayer. Glyphosate at 1.12 kg/ha applied in the recirculating sprayer caused more injury to ‘Hill’ and ‘Bragg’ than to ‘Forrest’ or ‘Tracy’ soybeans.

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