Gender assignment: Monolingual constraints contribute to a bilingual outcome

2021 ◽  
pp. 136700692110534
Author(s):  
Sonya Trawick ◽  
Trevor Bero
Keyword(s):  
Logistic Regression ◽  
New Mexico ◽  
Goodness Of Fit ◽  
Logistic Regression Model ◽  
Operating Characteristic ◽  
Relative Impact ◽  
Gender Assignment ◽  
Independent Variables ◽  
English Bilingual ◽  
Curve Method

Aims and objectives: This study explores the well-researched topic of gender assignment to English nouns in Spanish discourse through a usage-based framework. The goal is to elucidate the relative impact of both previously studied and novel constraints on the variable application of feminine determiners. Methodology: A variationist analysis of English nouns surrounded by Spanish discourse in the spontaneous speech of bilinguals. Data and analysis: Data come from the New Mexico Spanish–English Bilingual Corpus. Tokens ( N = 707) were coded for independent variables and submitted to a logistic regression. The goodness of fit was determined via the area under the receiver operating characteristic (ROC) curve method. Findings: All independent variables were selected as significant by the logistic regression model. Based on factor weight ranges, the hierarchy of constraints is the following, from the most to the least impactful: Analogical Gender, Phonological Shape, Syntactic Role, and Determiner Definiteness. These results suggest that bilinguals utilize a variety of constraints in gender assignment, as opposed to a single default strategy. Originality: While previous studies have tested and found similar results for constraints such as analogical gender and phonological shape, none have offered a unified analysis explaining findings from a usage-based approach. The originality and utility of this approach is most apparent in the discussions of prototypicality and schematicity. Significance/implications: A corpus-based approach and usage-based theory is shown to bring new insight to a topic of interest in many other linguistic sub-fields. The discussion reinterprets previous conclusions about gender assignment using a framework not proposed in previous research, despite similar overall results.

scholarly journals Sonographic Cervical Shortening after Labor Induction is a Predictor of Vaginal Delivery

2016 ◽  
Vol 38 (12) ◽  
pp. 585-588 ◽  
Author(s):  
Ugo Indraccolo ◽  
Gennaro Scutiero ◽  
Pantaleo Greco
Keyword(s):  
Logistic Regression ◽  
Vaginal Delivery ◽  
Regression Models ◽  
Operating Characteristic ◽  
Roc Curves ◽  
Cervical Length ◽  
Labor Induction ◽  
Logistic Regression Models ◽  
Independent Variables ◽  
Sonographic Evaluation

Objective Analyzing if the sonographic evaluation of the cervix (cervical shortening) is a prognostic marker for vaginal delivery. Methods Women who underwent labor induction by using dinoprostone were enrolled. Before the induction and three hours after it, the cervical length was measured by ultrasonography to obtain the cervical shortening. The cervical shortening was introduced in logistic regression models among independent variables and for calculating receiver operating characteristic (ROC) curves. Results Each centimeter in the cervical shortening increases the odds of vaginal delivery in 24.4% within 6 hours; in 16.1% within 24 hours; and in 10.5% within 48 hours. The best predictions for vaginal delivery are achieved for births within 6 and 24 hours, while the cervical shortening poorly predicts vaginal delivery within 48 hours. Conclusion The greater the cervical shortening 3 hours after labor induction, the higher the likelihood of vaginal delivery within 6, 24 and 48 hours.

Intuitionistic Fuzzy Partial Logistic Regression Model Using Ridge Methodology

2020 ◽  
Vol 28 (04) ◽  
pp. 527-543
Author(s):  
Gholamreza Hesamian ◽  
Mohammad Ghasem Akbari ◽  
Mehdi Roozbeh
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Smooth Function ◽  
Potential Application ◽  
Goodness Of Fit ◽  
Logistic Regression Model ◽  
Numerical Examples ◽  
Ridge Estimation ◽  
Intuitionistic Fuzzy

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.

scholarly journals Determinan Keputusan Melakukan Migrasi Ulang-Alik

2018 ◽  
Vol 1 (3) ◽  
pp. 242-251
Author(s):  
Rifqi Nur Fahmy
Keyword(s):  
Logistic Regression ◽  
Marital Status ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Analysis Method ◽  
Binary Logistic Regression Model ◽  
Level Of Education ◽  
Independent Variables ◽  
Variable Level

The aim of this research is to analyze the influence of dependent variable of family dependent, education level, age, marital status, and distance partially to workforce’s decision to migrate from Surakarta to Karanganyar Regency. This research used binary logistic regression analysis method. The sample in this research is 100 respondents. The result of binary logistic regression model analysis in this research shows that from five independent variables, there are two variables that have significant effect on workforce’s decision to do the commuter migration that is dependent variable of family and marital status. While the variable level of education, age, and distance have no effect on workforce’s decisions to do the commuter migration. Tujuan dari penelitian ini adalah untuk menganalisis pengaruh variabel dependen dependen keluarga, tingkat pendidikan, usia, status perkawinan, dan jarak secara parsial terhadap keputusan tenaga kerja untuk bermigrasi dari Surakarta ke Kabupaten Karanganyar. Penelitian ini menggunakan metode analisis regresi logistik biner. Sampel dalam penelitian ini adalah 100 responden. Hasil analisis model regresi logistik biner dalam penelitian ini menunjukkan bahwa dari lima variabel independen, ada dua variabel yang berpengaruh signifikan terhadap keputusan angkatan kerja untuk melakukan migrasi komuter yang merupakan variabel dependen keluarga dan status perkawinan. Sedangkan tingkat variabel pendidikan, usia, dan jarak tidak berpengaruh pada keputusan tenaga kerja untuk melakukan migrasi komuter.  

scholarly journals Handicraft small enterprises as an instrument for rural economic growth and poverty eradication

2020 ◽  
Vol 18 (4) ◽  
pp. 25-36
Author(s):  
Oluwayemisi A. Abisuga-Oyekunle ◽  
Mammo Muchie
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Goodness Of Fit ◽  
Logistic Regression Model ◽  
Growth Potential ◽  
Small Enterprises ◽  
Potential Contribution ◽  
Goodness Of Fit Test ◽  
Kwazulu Natal ◽  
Two Factors

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.

A Predictive Statistical Model To Identify Thalassemic Phenotype (β0 vs β+) in Heterozygous β-Thalassemia.

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 ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Goodness Of Fit ◽  
Logistic Regression Model ◽  
Globin Gene ◽  
Genetic Alterations ◽  
Theoretic Model ◽  
Fisher Exact Test ◽  
Globin Genes ◽  
Adjusted Model

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.

scholarly journals The Factors Affecting Eye Patients (Cataract) In Jordan by Using the Logistic Regression Model

2017 ◽  
Vol 11 (8) ◽  
pp. 38
Author(s):  
Adeeb Ahmed Ali AL Rahamneh ◽  
Omar M. Hawamdeh
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Likelihood Ratio Test ◽  
Logistic Regression Model ◽  
Ratio Test ◽  
Response Variable ◽  
Factors Affecting ◽  
Independent Variables ◽  
Lemeshow Test ◽  
The Right

This study aims to use the logistic regression model to classify patients as infected and without cataracts. The independent variables were used to represent the gender, the age, the pressure in the right eye, the pressure in the left eye, HbA1C, and the anemia, representative variables for the study of Cataract disease affects the eyes, based on a random sample of (116) patients. The results proved that the used logistic regression model is an efficient and representative for data that shows through (Likelihood Ratio Test) and (Hosmer and Lemeshow test), and the study proved that the value of (R Square Nagelkerke=1) this means that 100% of the change in the occurred changes in the response variable explained through the Logistic regression model.

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