A note on the construction of locally - and -optimal designs for the binary logistic model with several explanatory variables

2012 ◽  
Vol 82 (5) ◽  
pp. 865-870 ◽  
Author(s):  
M. Gaëtan Kabera ◽  
Linda M. Haines ◽  
Principal Ndlovu
Keyword(s):  
Logistic Model ◽  
Optimal Designs ◽  
Explanatory Variables ◽  
Binary Logistic Model

Factors Affecting Shift from Paddy to Maize Cultivation in Punjab

2021 ◽  
pp. 170-175
Keyword(s):  
Decision Maker ◽  
Logistic Model ◽  
Primary Data ◽  
Wheat Crop ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Maize Cultivation ◽  
Block Level ◽  
Price Instability ◽  
Binary Logistic Model

Maize is one of the most suitable replacements of paddy in Punjab. The primary data for 2015-16 of paddy, maize, and wheat crop from five Punjab districts (Hoshiarpur, Jalandhar, Rupnagar, SAS Nagar and SBS Nagar) was collected from 300 sample farm households. The binary logistic model was constructed, and among the six most relevant explanatory variables availability of hired labour was found to be negative and significant statistically, whereas the educational level of decision maker was statistically nonsignificant. The participation in block-level camp/Kisan Mela/lecture attended by the decision maker was positive and significant statistically, and water availability on the diversified farm was negative and significant. Like the assured market and experience of the decision maker, the other variables were positive but non-significant. The farmers' non-diversification was found to be price instability, the menace of animals, lack of awareness regarding government programmes, non-availability of mechanisation for dehusking of the kernels.

scholarly journals Logistic Regression to Evaluate the Marketability of Pepper Cultivars

Agronomy ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 125 ◽  
Author(s):  
Manuel Díaz-Pérez ◽  
Ángel Carreño-Ortega ◽  
José-Antonio Salinas-Andújar ◽  
Ángel-Jesús Callejón-Ferre
Keyword(s):  
Logistic Regression ◽  
Relative Humidity ◽  
Fruit Quality ◽  
Logistic Model ◽  
Sweet Pepper ◽  
Continuous Variables ◽  
Statistical Tool ◽  
Explanatory Variables ◽  
Fruit Samples ◽  
Binary Logistic Model

The goal of this paper is to show that logistic regression is an analytical method of interest to evaluate the marketability of different pepper (Capsicum annuum L.) cultivars. Two studies were conducted on “Italian sweet” pepper cultivars. Fruit samples were introduced in storage chambers and kept at 9 °C and 85–95% relative humidity during the study period. The fruits were evaluated individually and periodically by measuring the deterioration of fruit quality (rot, ageing, etc.). In this study, categorical explanatory variables (rot, etc.) and continuous explanatory variables (days of storage) were integrated and combined to determine the probability of marketability of the fruit. The results show that the binary logistic model is a useful statistical tool to analyse together both categorical and continuous variables in the study of the marketability of pepper cultivars.

scholarly journals Testing parallelism for the four-parameter logistic model with D-optimal design

2020 ◽  
Vol 15 (3) ◽  
pp. 273-284
Author(s):  
Lin Ying ◽  
Hyun Seung Won
Keyword(s):  
Optimal Design ◽  
Logistic Model ◽  
Test Preparation ◽  
Test Sample ◽  
Optimal Designs ◽  
Model Parameters ◽  
Reference Standard ◽  
Response Curves ◽  
Classical Design ◽  
Intersection Union Test

In order to determine the potency of the test preparation relative to the standard preparation, it is often important to test parallelism between a pair of dose-response curves of reference standard and test sample. Optimal designs are known to be more powerful in testing parallelism as compared to classical designs. In this study, D-optimal design was implemented to study the parallelism and compare+ its performance with a classical design. We modified D-optimal design to test the parallelism in the four-parameter logistic (4PL) model using Intersection-Union Test (IUT). IUT method is appropriate when the null hypothesis is expressed as a union of sets, and by using this method complicated tests involving several parameters are easily constructed. Since D-optimal design minimizes the variances of model parameters, it can bring more power to the IUT test. A simulation study will be presented to compare the empirical properties of the two different designs.

Optimal designs for the power logistic model

2004 ◽  
Vol 74 (11) ◽  
pp. 779-791 ◽  
Author(s):  
Joy King ◽  
Weng Kee Wong
Keyword(s):  
Logistic Model ◽  
Optimal Designs

scholarly journals The Construction of Locally D-Optimal Designs by Canonical Forms to an Extension for the Logistic Model

2014 ◽  
Vol 05 (05) ◽  
pp. 824-831
Author(s):  
Irene García Camacha Gutiérrez ◽  
Raúl Martín Martín
Keyword(s):  
Logistic Model ◽  
Optimal Designs ◽  
Canonical Forms

scholarly journals Fraud Risk Factors of Fraud Triangle and the Likelihood of Fraud Occurrence: Evidence from Malaysia

2014 ◽  
Vol 6 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Shabnam Fazli Aghghaleh ◽  
Zakiah Muhammaddun Mohamed .
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Logistic Model ◽  
Audit Committee ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Fraud Risk ◽  
Available Information ◽  
Binary Logistic Model

The current research studies the usefulness of Cressey’s fraud risk factor framework adopted from SAS No. 99 to prevent fraud from occurring. In accordance with Cressey’s theory, pressure, opportunity and rationalization are existing when fraud occurs. The study suggests variables as proxy measures for pressure and opportunity, and test these variables using publicly available information relating to a set of fraud firms and a sample of no-fraud firms. Two pressure proxies and two opportunity proxies are identified and suggested to be significantly related to financial statement fraud. We find that leverage and sale to account receivable are positively related to the likelihood of fraud. Audit committee size and board of directors’ size are also linked to decrease the level of financial statement fraud. A binary logistic model based on examples of fraud risk factors of fraud triangle model measures the likelihood of financial statement fraud and can assist experts.

scholarly journals Disabled People in Brazil: Risk Question

2018 ◽  
Author(s):  
Paulo de Oliveira
Keyword(s):  
Logistic Model ◽  
Risk Index ◽  
Poverty Rate ◽  
Decent Work ◽  
Visual Disability ◽  
Explanatory Variables ◽  
Number Of Children ◽  
Ordinal Response ◽  
Education Levels ◽  
Production Form

Throughout the world, disabilities people have worse health prospects, lower education levels, lower economic participation, and higher poverty rate in comparative terms to people without disabilities. For disabilities people achieve better, more long-lasting prospects, we must empower these people and remove barriers that restrict them from participating in the community have access to quality education, to find decent work and have their voices heard. In statistical terms, a very useful alternative that can provide support and monitoring of public policies in this area is proposing to be used continuously. A risk index called risk index disabled person who is to assess which factors are associated to this risk, as well as the intensity and direction of each of these factors, yielding a final score that can be sorted or classified according to the probability of people acquire a certain disability. In the Brazilian case, we propose the use of techniques such as binary and ordinal logistic regression to select the most significant factors using criteria such as AIC, BIC and DIC. Calculate the risk probability for different disabilities (see, hear, move and intellectual) and number of disabilities to the dataset Sample of respondents for Full Questionnaire at IBGE 2010 Census. In this work, by using stereotype ordinal logistic model with ordinal response, it was possible to improve the fit quality, to be compared with binary response logistic model. By using ordinal response merged the disability risk for different severity degree and amount of deficiencies. Mains conclusions were: i)the model required a smaller number of explanatory variables was intellectual or mental and greater number was disabilities; ii) the most sensitive adjust was using stereotype ordinal logistic; iii) different disabilities aren´t homogenous as the different predictor variables, and finally; iv) higher incidence of risks were noted visual disability, living in the northeast, female, age 80, yellow race, instruction level until incomplete fundamental, works production form their own consumption and high number of children.

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