Intuitionistic Fuzzy Partial Logistic Regression Model Using Ridge Methodology

Author(s):  
Gholamreza Hesamian ◽  
Mohammad Ghasem Akbari ◽  
Mehdi Roozbeh

This paper applies a ridge estimation approach in an existing partial logistic regression model with exact predictors, intuitionistic fuzzy responses, intuitionistic fuzzy coefficients and intuitionistic fuzzy smooth function to improve an existing intuitionistic fuzzy partial logistic regression model in the presence of multicollinearity. For this purpose, ridge methodology is also involved to estimate the parametric intuitionistic fuzzy coefficients and nonparametric intuitionistic fuzzy smooth function. Some common goodness-of-fit criteria are also used to examine the performance of the proposed regression model. The potential application of the proposed method are illustrated and compared with the intuitionistic partial logistic regression model through two numerical examples. The results clearly indicate the proposed ridge method is quite efficient in model’s performances when there is multicollinearity among the predictors.

2020 ◽  
Vol 18 (4) ◽  
pp. 25-36
Author(s):  
Oluwayemisi A. Abisuga-Oyekunle ◽  
Mammo Muchie

In South Africa, exploiting economic opportunities in the handicraft sector could create livelihood and employment for ordinary citizens living in rural areas. The potential contribution of handicraft small enterprises to sustainable livelihoods and poverty alleviation is yet to be fully exploited. It is also regarded as a sector with great growth potential, but the degree of support provided to the handicraft sector is low. The study aims to evaluate the socioeconomic factors influencing the viability of handicraft small businesses operating in KwaZulu-Natal. Data collection was drawn from a stratified random sample of 196 handicraft practitioners operating in different areas of KwaZulu-Natal Province with a structured questionnaire. Data analysis was performed with the STATA statistical package. The results obtained from the study have shown that 84 enterprises (42.86%) were not viable, whereas 112 of the 196 handicraft enterprises (57.14%) were viable. The percentage of overall correct classification for this procedure was equal to 77.96%. Percentage sensitivity for the fitted logistic regression model was equal to 60.71%. Percentage specificity for the fitted logistic regression model was equal to 82.14%. The p-value obtained from Hosmer-Lemeshow goodness-of-fit test was equal to 0.0884 > 0.05. This indicates that the fitted logistic regression model is fairly well reliable. The findings from the analysis showed that two factors significantly influenced the viability of handicraft enterprises. These two factors were the belief that handicraft business could sustain the handicraft practitioner, and the level of support for handicraft businesses from non-governmental organizations is decreasing. AcknowledgmentSouth Africa SarChi Chair, Nation Research Fund and Department of Science and Technology, South African, for providing funding for this research.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3823-3823
Author(s):  
Jose Manuel Calvo-Villas ◽  
Paloma Ropero ◽  
Silvia De la Iglesia ◽  
Maria Francisca Zapata ◽  
Alejandro Mayosky ◽  
...  

Abstract β thalassemias are a heterogeneous group of genetic alterations characterized by a decreasing (β+) or eliminating (β0) expression of b globin gene. Previous studies have reported that mean corpuscular volume (MCV) and mean corpuscular haemoglobin (MCH) values would be useful to differentiate between β+ and β0 thalassemia phenotypes in heterozygous carriers. An accurate and valid risk model for belonging to each of these groups may be valuable for prioritizing identification of genetic alterations in some populations. The aim of this study was to develop a theoretic model that combine information from the haematological indices for phenotypic prediction (β+ vs. β0) in heterozygous β thalassemia. The study was conducted on 238 unrelated β thalassemia carriers. Hematological parameters were obtained using analyzer Coulter ®GEN-S™. HbA2 and HbF were analysed by high performance liquid chromatography. Molecular analysis for β globin and α-globin genes was performed by real-time PCR, direct sequencing techniques and standard PCR techniques. β-thalassemic subjects who also exhibited either αthalassemia or extra α globin genes were excluded. Statistical significance was calculated by using the χ2 or Fisher exact test for qualitative variables and the t test for continuous variables. A multivariate logistic regression model, with stepwise selection, was fitted from a case group of 64 β+thalassemia subjects and a reference group of 174 β0carriers. Odds ratios and their 95% confidence intervals (CIs) were computed. Statistical analysis was performed with the SPSS 12.0 statistical software package. The mean level of HbA2 (4.5 ± 0.7% vs. 5.1 ± 0.7%, [p<0.0001]), MCV (66.9 ± 4.6 fL vs. 62.9 ± 3.1 fL, [p<0.0001]) and MCH (21.6 ± 1.8 pg vs. 20.1 ± 1.1 pg, [p<0.0001]) were significantly different between the β+ and β0 groups. By using an multivariate analysis, the three significant variables that finally entered the logistic regression model were MCH, HbA2 and HbF. These variables were dichotomized as HbA2> 4 vs. HbA2< 4, MCH> 20.5 vs. MCH< 20.5 and HbF> 1.5 vs. HbF< 1.5. The adjusted model implies that with a HbA2< 4, the chance of having β+thalassemia increase by a factor 8.3 (CI 1.6–43.1) compared with a HbA2> 4. Analogously, at a MCH > 20.5, the chance of having β +thalassemia increase by a factor 9.4 (CI 4.3–20.2) compared with a MCH< 20.5. Regarding to HbF, it is 1.3 times more likely (CI 1.1–1.9) to be included in the β+thalassemia group with HbF< 1.5 than with HbF> 1.5. For this adjusted model, with a 26,8% heterozygous β+thalassemia prevalence, model test performance characteristics included: sensitivity 61.4% and specificity 89.1% (p=0.000). The logistic multivariate model to allow accurate prediction of the phenotype of β thalassemia trait (β+ vs β0) in the 84.1% of the carriers. The Hosmer-Lemeshow statistics indicated fine goodness of fit of the logistic regression equation (P=0.739). In summary, this logistic regression analysis using a combination of hematological indices such as MCH, HbA2 and HbF has showed an acceptable value in predicting phenotype of heterozygous b thalassemia (β+ vs β0) in a predominant Spanish population. The present model should be validated by independent data from different populations.


2004 ◽  
Vol 24 (1) ◽  
pp. 121-130 ◽  
Author(s):  
Nico Nagelkerke ◽  
Jeroen Smits ◽  
Saskia le Cessie ◽  
Hans van Houwelingen

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