CONDITIONAL AND MULTINOMIAL LOGITS AS BINARY LOGIT REGRESSIONS

2011 ◽  
Vol 03 (03) ◽  
pp. 309-324 ◽  
Author(s):  
STAN LIPOVETSKY
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Link Function ◽  
Logit Models ◽  
Categorical Variable ◽  
Multinomial Models ◽  
Multinomial Logit Models ◽  
Dependent Variables ◽  
Binary Logit ◽  
Logit Modeling

For a categorical variable with several outcomes, its dependence on the predictors is usually considered in the conditional or multinomial logit models. This work considers elasticity features of the binary and categorical logits and introduces the coefficients individual by observations. The paper shows that by a special rearrangement of data the more complicated conditional and multinomial models can be reduced to binary logistic regression. It suggests the usage of any software widely available for logit modeling to facilitate constructing for complex conditional and multinomial regressions. In addition, for binary logit, it is possible to obtain meaningful coefficients of regression by transforming data to the linear link function, which opens a possibility to obtain meaningful parameters of the complicated models with categorical dependent variables.

scholarly journals Use of different approach in finding catch effort relationship in hook and line fishery in Kombuthurai village of Thoothukudi district of Tamil Nadu

2018 ◽  
Vol 10 (2) ◽  
pp. 648-654
Author(s):  
A. Anuja ◽  
Vinod K. Yadav
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Linear Model ◽  
Tamil Nadu ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Link Function ◽  
Catch Per Unit Effort ◽  
Binary Logistic Regression Model ◽  
Independent Variable

Kombuthurai has been described as a fishing village in Thoothukudi district, Tamil Nadu which has gained immense importance by practicing sustainable fishing practices. In Kombuthurai village during 2009-2013, catch per unit effort (CPUE) has varied from 0.20 tonnes to the maximum of 0.25 tonnes during this period. It is interesting to know that despite the range of effort varying from 1598hrs to 1720hrs, the catch remained in the range of 347.4 tonnes to a maximum of 430.8tonnes. The influence of various variables (latitude, longitude, distance, depth, seasons, years and fishing gear type) on CPUE was studied by General Linear Model (GLM) and Generalized Linear Model (GLMs). Normal distribution with identity link function and a gamma distribution with log link function were used in GLMs. The variables that were found to be significant in both of the models and distributions are year and season. GLM model was good fit with R2 ranging from 67.60% to a high of 91.7%.The low and high abundance of CPUE were categorized taking the below and above average CPUE. A binary logistic regression model was used between the CPUE abundance and with above mentioned independent variables. The binary logistic regression model explained 75.4% (Nagelkerke R2) of the variance in high CPUE abundance and correctly classified 88% of cases. The independent variable such as latitude, longitude, depth, and distance added significantly to the model, but the year, season and hooks did not add significantly to the model.

Logistic and multinomial-logit models: A brief review on their modifications and extensions

2021 ◽  
Vol 16 (4) ◽  
pp. 279-282
Author(s):  
Stan Lipovetsky
Keyword(s):  
Discrete Choice ◽  
Principal Component ◽  
Multinomial Logit ◽  
Singular Value ◽  
Logit Models ◽  
Applied Psychology ◽  
Multinomial Logit Models ◽  
Best Worst Scaling ◽  
Value Decomposition ◽  
Logit Modeling

The work presents various techniques of the logistic and multinomial-logit modeling with their modifications. These methods are useful for regression modeling with a binary or categorical outcome, structuring in regression and clustering, singular value decomposition and principal component analysis with positive loadings, and numerous other applications. Particularly, these models are employed in the discrete choice modeling and the best-worst scaling known in applied psychology and socio-economics studies.

scholarly journals Magnitude, pattern and management outcome of intestinal obstruction among non-traumatic acute abdomen surgical admissions in Arba Minch General Hospital, Southern Ethiopia

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mulatie Atalay ◽  
Abinet Gebremickael ◽  
Solomon Demissie ◽  
Yonas Derso
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Small Bowel ◽  
Intestinal Obstruction ◽  
General Hospital ◽  
Acute Abdomen ◽  
Binary Logistic Regression ◽  
P Value ◽  
Binary Logistic Regression Analysis ◽  
Dependent Variables

Abstract Background Intestinal obstruction is defined as a blockage or partial blockage of the passage of the intestinal contents. It is a potentially risky surgical emergency associated with high morbidity and mortality. Its pattern differs from country to country and even from place to place within a country. Therefore, this study aimed to find out the magnitude, pattern and management outcome of intestinal obstruction in Arba Minch General Hospital. Methods A retrospective cross-sectional study was conducted in Arba Minch General hospital from January 09, 2015, to November 09, 2018. The data collection period was from December 15, 2018, to February 09, 2019. A simple random technique was applied to select 801 study participants. Then, the required data entered into Epi Info version 7.2.1.0 and exported to the statistical package for the social sciences software package version 20 for analysis. The binary logistic regression analysis has been done to determine crude statistical associations between independent variables and dependent variables. Linearity, Multivariate normality and multicollinearity were checked between independent and dependent variables by using scatter plot and Q–Q plot respectively. Variables with a p-value of less than 0.25 in the binary logistic regression analysis were entered into multivariable logistic regression. Statistical significance factors were identified based on a p-value of < 0.05 and with a 95% confidence interval. Result This study revealed that the overall magnitude of intestinal obstruction was 40.60% with 95% CI (34.95–45.95). The magnitude of unfavorable management outcomes and deaths during the study period were 22.3% with 95% CI (18.00–27.00) and 7.1% with 95% CI (4.00–10.00) respectively. Persistent tachycardia 10.3 (3.28–32.42), Dehydration 13.7 (3.34–56.56), elevated serum creatinine 10.2 (1.89–54.94), gangrenous small bowel volvulus 2.7 (1.27–5.84), ischemic bowel 3.4 (1.17–9.81) and perforated bowl 7.68 (2.96–19.93) were significantly associated with the management outcome of intestinal obstruction. Conclusion and recommendation Intestinal obstruction was the most common among all acute abdomen cases and its management outcome highly associated with dehydration. Adequate early preoperative resuscitation and proper post-operative care with appropriate surgical techniques and wound care with sterile techniques would help to reduce further mortality. This could be achieved by increasing public awareness of health-seeking behavior. Moreover, health facilities capable of handling patients with small bowel obstruction should be available within the reach of the community.

Evaluating the implementation potential of a transcultural tool for Tamil migrants with gestational diabetes mellitus living in Switzerland

2017 ◽  
Vol 2 (2) ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Online Survey ◽  
Healthcare Professionals ◽  
Binary Logistic Regression ◽  
Private Practices ◽  
Populations At Risk ◽  
Management Procedures

Background: Gestational diabetes mellitus is a condition that affects many pregnancies and ethnicity appears to be a risk factor. Data indicate that approximately 18% of Tamil women are diagnosed with gestational diabetes mellitus. Today, approximately 50,000 of Tamils live in Switzerland. To date, there is no official tool available in Switzerland that considers the eating and physical activity habits of this migrant Tamil population living in Switzerland, while offering a quick overview of gestational diabetes mellitus and standard dietetics management procedures. The NutriGeD project led by Bern University of Applied Sciences in Switzerland aimed at closing this gap. The aim of this present study was to evaluate the implementation potential of the tools developed in the project NutriGeD for dietetic counseling before their wide scale launch in Swiss hospitals, clinics and private practices. Method: An online survey was developed and distributed to 50 recruited healthcare professionals working in the German speaking region of Switzerland from October – December 2016 (31% response rate). The transcultural tools were sent to participants together with the link to the online survey. The evaluation outcome was analysed using binary logistic regression and cross tabulation analysis with IBM SPSS version 24.0, 2016. Results: 94% (N=47) respondents believed that the transcultural tools had good potential for implementation in hospitals and private practices in Switzerland. A binary logistic regression analysis revealed that the age of participants had a good correlation (42.1%) on recommending the implementation potential of the transcultural tool. The participants with age group 34- 54 years old where the highest group to recommend the implementation potential of the transcultural tool and this was found to be statistically significant (p=0.05). 74% (34 out of 50) of the respondents clearly acknowledged the need for transcultural competence knowledge in healthcare practices. 80% (N =40) of the respondents agreed that the information presented in the counseling display folder was important and helpful while 60% (N= 30) agreed to the contents being clinically applicable. 90% (N=45) participants recommended the availability of the evaluated transcultural tools in healthcare settings in Switzerland. Conclusion: The availability in healthcare practice of the evaluated transcultural tools was greatly encouraged by the Swiss healthcare practitioners participating in the survey. While they confirmed the need for these transcultural tools, feed-backs for minor adjustments were given to finalize the tools before their official launch in practice. The developed materials will be made available for clinical visits, in both hospitals and private practices in Switzerland. The Migmapp© transcultural tool can serve as a good approach in assisting healthcare professionals in all fields, especially professionals who practice in areas associated with diet - related diseases or disorders associated with populations at risk.

Intimate Partner Violence and its Association With Contraceptive Use Among Women in Pakistan

2019 ◽  
Vol 34 (Spring 2019) ◽  
pp. 157-173
Author(s):  
Kashif Siddique ◽  
Rubeena Zakar ◽  
Ra’ana Malik ◽  
Naveeda Farhat ◽  
Farah Deeba
Keyword(s):  
Intimate Partner Violence ◽  
Logistic Regression ◽  
Partner Violence ◽  
Contraceptive Use ◽  
Binary Logistic Regression ◽  
Intimate Partner ◽  
Married Women ◽  
Reproductive Age ◽  
Outcome Variable ◽  
Odds Ratios

The aim of this study is to find the association between Intimate Partner Violence (IPV) and contraceptive use among married women in Pakistan. The analysis was conducted by using cross sectional secondary data from every married women of reproductive age 15-49 years who responded to domestic violence module (N = 3687) of the 2012-13 Pakistan Demographic and Health Survey. The association between contraceptive use (outcome variable) and IPV was measured by calculating unadjusted odds ratios and adjusted odds ratios with 95% confidence intervals using simple binary logistic regression and multivariable binary logistic regression. The result showed that out of 3687 women, majority of women 2126 (57.7%) were using contraceptive in their marital relationship. Among total, 1154 (31.3%) women experienced emotional IPV, 1045 (28.3%) women experienced physical IPV and 1402 (38%) women experienced both physical and emotional IPV together respectively. All types of IPV was significantly associated with contraceptive use and women who reported emotional IPV (AOR 1.44; 95% CI 1.23, 1.67), physical IPV (AOR 1.41; 95% CI 1.20, 1.65) and both emotional and physical IPV together (AOR 1.49; 95% CI 1.24, 1.72) were more likely to use contraceptives respectively. The study revealed that women who were living in violent relationship were more likely to use contraceptive in Pakistan. Still there is a need for women reproductive health services and government should take initiatives to promote family planning services, awareness and access to contraceptive method options for women to reduce unintended or mistimed pregnancies that occurred in violent relationships.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

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