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Journal articles on the topic 'Multinomial logit regression model'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Jakaitienė, Audronė. "Multinomial logit death forecasting model." Lietuvos matematikos rinkinys, no. III (December 17, 1999): 367–69. http://dx.doi.org/10.15388/lmd.1999.35662.

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The multinomial regression logit model is analyzed. The algorithms and software are made for this model in order to get estimation of parameters. Calculations are made using generated population of 1000 cases.

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Amalahu, Christian Chinenye, Joy Chioma Nwabueze, and Chibueze Barnabas Ekeadinotu. "EGG QUALITY ASSESSMENT: A MODEL COMPARISON APPROACH USING BAYESIAN MIXED LOGIT, MIXED LOGIT, LOGISTIC REGRESSION AND MULTINOMIAL REGRESSION MODELS." FUDMA JOURNAL OF SCIENCES 9, no. 5 (2025): 110–13. https://doi.org/10.33003/fjs-2025-0905-3656.

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This study compares the performance of Bayesian mixed logit, mixed logit, logistic regression, and multinomial regression models in analyzing egg quality. The results show that the Bayesian mixed logit model outperforms traditional models, with egg weights, shell thickness, and shape index emerging as significant determinants of egg quality. The Bayesian mixed logit model's superior performance is evident in its lower AIC, DIC, RMSE, and MAE values. These findings have implications for the poultry industry, highlighting the importance of considering complex relationships between egg quality tr

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McFadden, Daniel. "Regression-based specification tests for the multinomial logit model." Journal of Econometrics 34, no. 1-2 (1987): 63–82. http://dx.doi.org/10.1016/0304-4076(87)90067-4.

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Kalina, J. "Model choice for regression models with a categorical response." Journal of Applied Mathematics, Statistics and Informatics 18, no. 1 (2022): 59–71. http://dx.doi.org/10.2478/jamsi-2022-0005.

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Abstract The multinomial logit model and the cumulative logit model represent two important tools for regression modeling with a categorical response with numerous applications in various fields. First, this paper presents a systematic review of these two models including available tools for model choice (model selection). Then, numerical experiments are presented for two real datasets with an ordinal categorical response. These experiments reveal that a backward model choice procedure by means of hypothesis testing is more effective compared to a procedure based on Akaike information criterio

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Månsson, Kristofer, Ghazi Shukur, and B. M. Golam Kibria. "Performance of some ridge regression estimators for the multinomial logit model." Communications in Statistics - Theory and Methods 47, no. 12 (2018): 2795–804. http://dx.doi.org/10.1080/03610926.2013.784996.

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Głuszak, Michał. "Multinomial Logit Model Of Housing Demand In Poland." Real Estate Management and Valuation 23, no. 1 (2015): 84–89. http://dx.doi.org/10.1515/remav-2015-0008.

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Abstract When compared to mature housing markets, little has been done to understand the nature of demand on emerging housing markets in Central and Eastern Europe and to develop testable models for post-socialist economies. With the exception of Bazyl 2009 and Głuszak 2010, there is hardly any econometric evidence on factors behind housing tenure choices in Poland. The article focus mainly on: permanent (and current) income, household structure, lifecycle, and differences between local market characteristics. In the research, multinomial logistic regression is used to analyze factors that inc

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Augustin, Nicole H., Roger P. Cummins, and Donald D. French. "Exploring spatial vegetation dynamics using logistic regression and a multinomial logit model." Journal of Applied Ecology 38, no. 5 (2001): 991–1006. http://dx.doi.org/10.1046/j.1365-2664.2001.00653.x.

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Jakaitienė, Audronė. "Fixed time competing risk model." Lietuvos matematikos rinkinys 40 (December 18, 2000): 389–91. http://dx.doi.org/10.15388/lmr.2000.35185.

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The competing risks under multinomial regression logit model is analyzed. The algorithms and software are made for this model in order to get estimation of parameters. Calculations are made using data of Cardiology Institute about health of 45-60 years old men, which were collected from 1972 till 1977.

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Li, Xiaowei, Yuting Wang, Yao Wu, Jun Chen, and Jibiao Zhou. "Modeling Intercity Travel Mode Choice with Data Balance Changes: A Comparative Analysis of Bayesian Logit Model and Artificial Neural Networks." Journal of Advanced Transportation 2021 (September 14, 2021): 1–22. http://dx.doi.org/10.1155/2021/9219176.

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This study conducts a comprehensive comparative analysis of regression-based multinomial models and artificial neural network models in intercity travel mode choices. The four intercity travel modes of airplane, high-speed rail (HSR), train, and express bus were used for analysis. Passengers’ activity data over the process of intercity travel were collected to develop the models. The standard multinomial logit (MNL) regression and Bayesian multinomial logit (BMNL) regression were compared with the radial basis function (RBF) and multilayer perceptron (MLP). The results show that MLP performs b

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Thrane, Christer. "Examining tourists' long-distance transportation mode choices using a Multinomial Logit regression model." Tourism Management Perspectives 15 (July 2015): 115–21. http://dx.doi.org/10.1016/j.tmp.2014.10.004.

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11

Jarvis, Benjamin F. "Estimating Multinomial Logit Models with Samples of Alternatives." Sociological Methodology 49, no. 1 (2018): 341–48. http://dx.doi.org/10.1177/0081175018793460.

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This comment reconsiders advice offered by Bruch and Mare regarding sampling choice sets in conditional logistic regression models of residential mobility. Contradicting Bruch and Mare’s advice, past econometric research shows that no statistical correction is needed when using simple random sampling of unchosen alternatives to pare down respondents’ choice sets. Using data on stated residential preferences contained in the Los Angeles portion of the Multi-City Study of Urban Inequality, it is shown that following Bruch and Mare’s advice—to implement a statistical correction for simple random

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Waweru, David, and Naftaly Mose. "Household Fuel Choice in Urban Kenya: A Multinomial Logit Analysis." Financial Internet Quarterly 18, no. 2 (2022): 30–41. http://dx.doi.org/10.2478/fiqf-2022-0011.

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Abstract This study applied a logistic regression model to determine the odds ratio of selecting clean versus unclean energy as the main household fuel choice. This study also undertook to establish the coefficients of the factors determining household fuel energy choice. A large microeconomic dataset from KIPPRA’s comprehensive study and analysis on fuel use patterns in Kenya (2010) was employed to carry out the analysis. This study employed a multinomial logit regression model to determine the fuel choices and patterns of cooking fuels in urban Kenyan households. The results showed that in a

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Song, Mi Kyung, and Inkyung Jung. "Comparison of Goodness-of-Fit Tests using Grouping Strategies for Multinomial Logit Regression Model." Korean Journal of Applied Statistics 26, no. 6 (2013): 889–902. http://dx.doi.org/10.5351/kjas.2013.26.6.889.

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Franses, Philip Hans, and Richard Paap. "Testing for Bias in Forecasts for Independent Multinomial Outcomes." Forecasting 7, no. 1 (2025): 4. https://doi.org/10.3390/forecast7010004.

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This paper deals with a test on forecast bias in predicting independent multinomial outcomes where the predictions are probabilities. The new Likelihood Ratio (and Wald) test extends the familiar Mincer Zarnowitz regression to a multinomial logit model instead of a linear regression. The test is evaluated using various simulation experiments, which indicate that the size and power properties are good, even for small sample sizes, in the sense that the size is close to the used 5% level, and the power quickly reaches 1. We implement the test in an empirical setting on brand choice by individual

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van der Lans, Ralf. "Bayesian estimation of the multinomial logit model: a comment on Holmes and Held, "Bayesian auxiliary variable models for binary and multinomial regression"." Bayesian Analysis 6, no. 2 (2011): 353–55. http://dx.doi.org/10.1214/11-ba613.

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Guo, Yanyong, Yao Wu, Jian Lu, and Jibiao Zhou. "Modeling the Unobserved Heterogeneity in E-bike Collision Severity Using Full Bayesian Random Parameters Multinomial Logit Regression." Sustainability 11, no. 7 (2019): 2071. http://dx.doi.org/10.3390/su11072071.

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Understanding the risk factors of e-bike collisions can improve e-bike riders’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates risk factors that significantly contribute to the severity of e-bike collisions. Two months of e-bike collision data were collected in the city of Ningbo, China. A random parameters multinomial logit regression (RP-MNL) is proposed to account for the unobserved heterogeneity across observations. A fixed parameters multinomial logit regression (FP-MNL) is estimated and compared with the RP-MNL under the Bayes

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Ramatu, M. Al-Hassan, K. M. Kuwornu John, and Osei-Owusu Yaw. "Determinants of Choice of Indigenous Climate Related Strategies by Smallholder Farmers in Northern Ghana." British Journal of Environment and Climate Change 3, no. 2 (2013): 172–87. https://doi.org/10.9734/BJECC/2013/2495.

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This study assessed the determinants of Choice of Indigenous Climate Related Strategies by Smallholder Farmers in Northern Ghana using primary data obtained through community focus group discussions and household survey, and subjected to the Multinomial Logit regression model. The empirical results reveal that presence of a market, informal credit from friends and relatives, location of farmer, farmer-to-farmer extension, noticing of a decrease in rainfall and noticing an increase in temperature influence the choice of indigenous climate related strategies. There is therefore the need to impro

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Lipovetsky, Stan. "Logistic and multinomial-logit models: A brief review on their modifications and extensions." Model Assisted Statistics and Applications 16, no. 4 (2021): 279–82. http://dx.doi.org/10.3233/mas-210543.

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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.

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Irfan, Mohd, Sarani Saha, and Sanjay Kumar Singh. "A random effects multinomial logit model for the determinants of exit modes." Journal of Economic Studies 45, no. 4 (2018): 791–809. http://dx.doi.org/10.1108/jes-03-2017-0075.

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Purpose The purpose of this paper is to examine the factors associated with three modes of firms’ exit (voluntary liquidation, involuntary liquidation and acquisition) in a mutually exclusive environment. In particular, three modes of exit are treated as independent events given that different causes and consequences exist for each exit mode. The data set is a panel of 4,408 US manufacturing firms spanning over the period 1976–1995. Design/methodology/approach The discrete choice model is used to establish a relationship between modes of exit and a set of explanatory variables, which are speci

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Foster, Kwashie Dugble (MPhil), Kosi Kumassah (MPhil) Eliot, and Kofi Owusu (MSc) Damianus. "Determinants of Pupils' Poor Academic Performance in Basic Education Certificate Examination in Mathematics: A Multinomial Logistic Regression Model." International Journal of Academic Research in Business, Arts & Science ( IJARBAS.COM ) 1, no. 1 (2019): 49–74. https://doi.org/10.5281/zenodo.3363501.

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The aim of the present study is to examine and to model in multinomial logit some selected demographic, homes-related, school-related, teachers-related and pupils-related factors as predictors on pupils’ Basic Education Certificate Examination (BECE) performance in mathematics as categorical response variable (upper grade, average grade, and lower grade). A combination of systematic and simple random sample of 62 pupils was selected from a cohort of BECE candidates of University Junior High School in Cape Coast municipality. The instrument for data collection was the interview guide. It

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Balash, Vladimir A., Olga S. Balash, and Aleksey R. Faizliev. "Using Multi-state Markov models to predict the probability of borrowers’ default." Izvestiya of Saratov University. Economics. Management. Law 23, no. 1 (2023): 35–41. http://dx.doi.org/10.18500/1994-2540-2023-23-1-35-41.

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Introduction. After the crises, lenders realized the importance of assessing the risk of default on loan portfolios in various economic conditions. Modeling of credit risk assessment occurs mainly using internal ratings of banks based on probabilistic models of defaults of borrowers over a certain period of time. Theoretical models. Three models are considered. The first is a naive Markov model with R states. The transition matrix is given. The second is a Markov model with multiple states with covariates. Macroeconomic indicators are proposed as covariates. The third model is multinomial logi

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Tian, Xinyu, Xuefeng Wang, and Jun Chen. "Network-Constrained Group Lasso for High-Dimensional Multinomial Classification with Application to Cancer Subtype Prediction." Cancer Informatics 13s6 (January 2014): CIN.S17686. http://dx.doi.org/10.4137/cin.s17686.

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Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high di

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Hvattum, L. M. "Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer." International Journal of Computer Science in Sport 16, no. 1 (2017): 50–64. http://dx.doi.org/10.1515/ijcss-2017-0004.

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AbstractOrdinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss. However, the often used ordinal models have an assumption of proportional odds: the influence of an independent variable on the log odds is the same for each outcome. This paper illustrates how ordinal regression models therefore fail to fully utilize independent variables that contain inf

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Masoumi, Houshmand, Martin van Rooijen, and Grzegorz Sierpiński. "Children’s Independent Mobility to School in Seven European Countries: A Multinomial Logit Model." International Journal of Environmental Research and Public Health 17, no. 23 (2020): 9149. http://dx.doi.org/10.3390/ijerph17239149.

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The determinants of children’s independent school mobility and the contextual discrepancies between these determinants have not been comprehensively investigated in previous studies. It is important to examine these determinants because independent school mobility is associated with children’s physical activity, according to the literature. This paper examined the associations of different groups of variables such as household, mobility, perceptions, and the built environment with independent school mobility of children between 9 and 12 years using a sample of 1304 girls (50.9%) and boys (49.1

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Samadder, Shruti, Sudhanand Prasad Lal, Satya Prakash, and K. M. Singh. "Determinants of Food Insecurity in the Sundarbans: Multinomial Logit Approach Apropos the Food Insecurity Experience Scale." European Journal of Nutrition & Food Safety 17, no. 4 (2025): 204–15. https://doi.org/10.9734/ejnfs/2025/v17i41692.

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Aims: This study examines socio-economic and demographic determinants of food insecurity in the Sundarbans region using a multinomial logistic regression model, aiming to identify key determinants of food insecurity levels. Study Design: A cross-sectional analytical study employing multinomial logistic regression to assess categorical predictors of food insecurity. Place and Duration of Study: Data were collected over six months (January 2024–December 2024 at regular intervals) across 11 blocks in South and North 24 Parganas, such as Gosaba, Basanti, Kakdwip, and Sagar. Methodology: Structured

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Niyonshuti, Emmanuel. "Analysis of Household Lighting Fuel Choice in Rwanda, Africa: Using the Multinomial Logit Model." Journal of Business and Social Sciences Research 6, no. 2 (2021): 87–97. http://dx.doi.org/10.3126/jbssr.v6i2.44714.

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This paper seeks to identify the determining control factors that influence the fuel energy choice for lighting purposes in Rwanda by applying the Multinomial Logit Regression to the national representative survey at household level data. The study revealed that the households with higher income adopt the use the cleaner and modern fuel energy sources, confirming the hypothesis for the energy ladder. Not only household income exerting impact on the fuel energy choice for lighting, but also the other fuel choices that are the significant determining variables in Rwanda are the number of the roo

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Fullerton, Andrew S., and Jun Xu. "Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables." Sociological Methods & Research 47, no. 2 (2015): 169–206. http://dx.doi.org/10.1177/0049124115613781.

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Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which is an extension of the traditional model that relaxes the proportional odds assumption for a subset of independent variables. In the unconstrained partial model, the variables without proportional odds have coefficients that freely vary across cutpoin

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Ma, Changxi, Jibiao Zhou, and Dong Yang. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model." International Journal of Environmental Research and Public Health 17, no. 4 (2020): 1259. http://dx.doi.org/10.3390/ijerph17041259.

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Understanding the influence factors and related causation of hazardous materials can improve hazardous materials drivers’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates the statistical distribution characteristics, such as types of hazardous materials transportation accidents, driver properties, vehicle properties, environmental properties, road properties. In total, 343 data regarding hazardous materials accidents were collected from the chemical accident information network of China. An ordered logit regression (OLR) model is pro

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Boltz, Frederick, and Douglas R. Carter. "Multinomial logit estimation of a matrix growth model for tropical dry forests of eastern Bolivia." Canadian Journal of Forest Research 36, no. 10 (2006): 2623–32. http://dx.doi.org/10.1139/x06-155.

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Multinomial logistic (MNL) regression was employed to estimate the transition probabilities of a matrix growth model for dry forests of the eastern Bolivian lowlands. Probabilities of mortality, stability, and upgrowth of a size and species group were estimated as a function of tree and stand attributes influencing growth and mortality. Data for model estimation were drawn from logged and undisturbed permanent sample plots (PSPs) measured over 6 and 7 years in Chiquitania forests south of Concepción, Santa Cruz, Bolivia. The estimated transition probabilities of the MNL models are not signific

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Putman, Stephen H. "Extending DRAM Model: Theory-Practice Nexus." Transportation Research Record: Journal of the Transportation Research Board 1552, no. 1 (1996): 112–19. http://dx.doi.org/10.1177/0361198196155200116.

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The DRAM and EMPAL models of household and employment location and land use, respectively, have seen numerous applications by regional planning agencies and metropolitan planning organizations. One reason for this is that compared with other location and land use models, they are relatively easy to use. The theoretical structure of these models is that of aggregate multinomial logit. They are representations of choice probability means for household types and employment types, with their structures being derived from location surplus formulations. In operation the parameters of these models’ e

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Erokhin, Viktor V. "FORECASTING THE ECONOMY OF THE SCIENTIFIC SECTOR BASED ON DISCRETE CHOICE MODELS USING ARTIFICIAL NEURAL NETWORKS IN CROSS-COUNTRY ANALYSIS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 5/7, no. 146 (2024): 6–20. http://dx.doi.org/10.36871/ek.up.p.r.2024.05.07.001.

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The article presents a study of the influence of artificial deep neural networks (AGNN) on increasing the accuracy and reliability of predictive regression models in the economics of the scientific sector of 61 countries, including Russia. We integrated the feedforward IGNS into the econometric discrete choice model (DCM), which represents a multinomial logit model (MNLR). AGNN in regression models built on statistical data with a large range of standard deviation lead to an increase in forecasting accuracy by at least 32% within 0,8 periods of the analyzed data. The use of integration of AGNN

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Khoirun Nisa, Wahyu, Patria Yunita, and Ayis Mukholik. "The Effect of Yuan Exchange Rate to Islamic Banking Credit Risk in Asia Case Study of Indonesia." International Economic and Finance Review 2, no. 2 (2023): 51–63. http://dx.doi.org/10.56897/iefr.v2i2.37.

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This study aims to analyze the effect of the yuan exchange rate on non- performing financing in Islamic banking for the period March 2012 to February 2022. The type of data used in this study is quantitative data and the source of data used in this study is secondary data obtained from the official website of the Authority. Financial Services (OJK) and Bank Indonesia (BI) . The data analysis model in this study uses multinomial logit regression analysis, where multinomial logistic regression is a logistic regression used when the dependent variable has a polychotomous or multinomial scale. The

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Bucklin, Randolph E., Sunil Gupta, and S. Siddarth. "Determining Segmentation in Sales Response across Consumer Purchase Behaviors." Journal of Marketing Research 35, no. 2 (1998): 189–97. http://dx.doi.org/10.1177/002224379803500205.

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The authors develop a joint estimation approach to segment households on the basis of their response to price and promotion in brand choice, purchase incidence, and purchase quantity decisions. The authors model brand choice (what to buy) by multinomial logit, incidence (whether to buy) by nested logit, and quantity (how much to buy) by poisson regression. Response segments are determined probabilistically using a latent mixture model. The approach simultaneously calibrates sales response on two dimensions: across segments and the three purchase behaviors. The procedure permits market-level sa

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Dwivedi, Alok Kumar, Indika Mallawaarachchi, Juan B. Figueroa-Casas, Angel M. Morales, and Patrick Tarwater. "Multinomial logistic regression approach for the evaluation of binary diagnostic test in medical research." Statistics in Transition new series 16, no. 2 (2015): 203–22. http://dx.doi.org/10.59170/stattrans-2015-011.

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Evaluating the effect of variables on diagnostic measures (sensitivity, specificity, positive, and negative predictive values) is often of interest to clinical researchers. Logistic regression (LR) models can be used to predict diagnostic measures of a screening test. A marginal model framework using generalized estimating equation (GEE) with logit/log link can be used to compare the diagnostic measures between two or more screening tests. These individual modeling approaches to each diagnostic measure ignore the dependency among these measures that might affect the association of covariates w

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Ignatius, Roni Setyawan, and Listyarti Indra. "Multinomial Logit Modeling of Financial Inclusion and Financial Literacy of Women MSMEs in Tangerang." Journal of Economics, Finance And Management Studies 07, no. 09 (2024): 5908–14. https://doi.org/10.5281/zenodo.13822590.

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This research will examine the determinants of financial literacy and inclusion using sociodemographic variables of women MSMEs in Tangerang. The sociodemographic variables used are education, age, length of business, turnover, source of financing, type of savings, type of credit, credit ceiling, financial literacy score (OJK) and financial inclusion score (OJK). In Indonesia, there has been a lot of research on socio-demographic factors as determinants of financial literacy with mixed and unsatisfactory results, making it less reliable as a research reference. Some of the errors in previous r

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Raparthi, Kiranmayi. "Analyzing the Relationship between Environmental Planning Policies and Climate Change: Multinomial Logit Regression Model Evaluation of Tarrant County, Texas." Current Urban Studies 03, no. 01 (2015): 1–10. http://dx.doi.org/10.4236/cus.2015.31001.

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Guimarães, Paulo, and Richard C. Lindrooth. "Controlling for overdispersion in grouped conditional logit models: A computationally simple application of Dirichlet‐multinomial regression." Econometrics Journal 10, no. 2 (2007): 439–52. http://dx.doi.org/10.1111/j.1368-423x.2007.00215.x.

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Maulana, Robby, and Chaikal Nuryakin. "THE EFFECT OF SAVING ACCOUNT OWNERSHIP AND ACCESS TO FINANCIAL INSTITUTIONS ON HOUSEHOLD LOANS IN INDONESIA." Buletin Ekonomi Moneter dan Perbankan 24, no. 3 (2021): 465–86. http://dx.doi.org/10.21098/bemp.v24i3.1428.

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This study investigates whether saving account ownership and access to financial institutions influence household credit in Indonesia. Using a multinomial logit regression model and a sample of 294,426 households from the 2018 national socioeconomic survey and the village potential data, we find that account ownership is essential in encouraging formal credit and reducing informal credit. Access to commercial banks, rural banks, and cooperatives can then improve formal credit without significantly reducing informal credit. Hence, the government needs to encourage bank account ownership and fac

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Friday, Ajeka, and Musibau Shofoluwe. "Using Multinomial Logistic Regression Model to Predict the Effect of Social Media on Academic Performance of College Students." International Journal of Technology in Education and Science 9, no. 2 (2025): 305–18. https://doi.org/10.46328/ijtes.623.

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Social media networking has become an integral part of communication today, with widespread usage across various demographics. This study was conducted to investigate the impact of social media on student academic performance, recognizing its prevalence and influence in educational settings. A random sample of 1,692 students was selected to participate in the study. A multinomial logit model was developed to predict student performance based on significant predictors, including age, marital status, monthly budget for social networks, monthly stipend, and daily private study time on social medi

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MALIKI, Samir, Abderrezzak BENHABIB, and Abdelnacer BOUTELDJA. "Poverty and Education in Algeria." International Journal for Innovation Education and Research 2, no. 1 (2014): 62–80. http://dx.doi.org/10.31686/ijier.vol2.iss1.138.

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Using a multinomial logit measurement, we aim through this paper to quantify the relationship between poverty and education. A subjective measurement of poverty is used with non school factors in quantifying such relationship. For a better understanding of the linkage Poverty-Education, a Multinomial regression model is applied to a representative survey of 500 households in the region of Tlemcen. According to our results , variables such as: individual housing, household's head instruction's level ,expenditures on education , the gender (male), and the age are common variables whatever povert

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Shah, Santosh Kumar. "Multinomial Logistic Regression Model to Identify Factors Associated with Food Insecurity in Rural Households in Nepal." Nepalese Journal of Statistics 4 (December 18, 2020): 17–32. http://dx.doi.org/10.3126/njs.v4i0.33448.

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Background: Food is basics of our lives and many people experiences food insecurity at some time because of food deprivation and lack of access to food due to different resource constraints. It is a global challenge and threatens the rural people in developing countries like Nepal. Objective: The objective of the study is to identify the factors associated with food insecurity in rural area of Nepal. Materials and Methods: The analysis is based on rural household data extracted from the data of Nepal Demographic and Health Survey 2016. The dependent variable food insecurity status

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Mulate, Japhet, and Lawrence Dumisani Nyathi. "A Logit Model Approach in Investigating the Impact of Education on Poverty Alleviation in Urban Bulawayo in Zimbabwe." International Journal of Research and Scientific Innovation XI, no. XI (2024): 737–50. https://doi.org/10.51244/ijrsi.2024.11110059.

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The study investigates the impact of education on poverty in urban Bulawayo using a multinomial logistic regression model. The primary objective is to assess how different levels of education affect the likelihood of households falling into various poverty categories—non-poor, poor, and extremely poor. Additionally, the research examines the role of other factors, including household size, gender, marital status, and the number of dependents, in determining urban poverty status. Data for the study were collected using a combination of primary sources (questionnaires and interviews) and seconda

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Indriyani Abulebu, Henny, Bleiser Tanari, and Muhammad Isran Ramli. "Trip attraction model of central market in Poso City based on multiple linier regression model." MATEC Web of Conferences 181 (2018): 02008. http://dx.doi.org/10.1051/matecconf/201818102008.

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Analysis of trip attraction in shopping centers is one of the most important aspects of travel demand management (TDM) in developing countries. This research aims to describe significant factors that influence people in obtaining their choice of frequency. Variables used in this research are family’s socio-demographic variables, properties of trip to shopping centers, nature of selecting trip time, and ways to travel. This research adopts multinomial logit model by modeling or building causal relationship between significant variables that influence trip frequency. The findings show that on ho

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Martínez-Flórez, Guillermo, Roger Tovar-Falón, and Héctor W. Gómez. "Mathematical Formalization and Applications to Data with Excess of Zeros and Ones of the Unit-Proportional Hazard Inflated Models." Mathematics 12, no. 22 (2024): 3566. http://dx.doi.org/10.3390/math12223566.

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In this study, we model the rate or proportion of a specific phenomenon using a set of known covariates. To fit the regression model, which explains the phenomenon within the intervals (0,1), [0,1), (0,1], or [0,1], we employ a logit link function. This approach ensures that the model’s predictions remain within the appropriate range of zero to one. In cases of inflation at zero, one, or both, the logit link function is similarly applied to model the dichotomous Bernoulli-type variable with a multinomial response. The findings demonstrate that the model yields a non-singular information matrix

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Firth, David. "1. Overcoming the Reference Category Problem in the Presentation of Statistical Models." Sociological Methodology 33, no. 1 (2003): 1–18. http://dx.doi.org/10.1111/j.0081-1750.2003.t01-1-00125.x.

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Effects of categorical variables in statistical models typically are reported in terms of comparison either with a reference category or with a suitably defined “mean effect,” for reasons of parameter identification. A conventional presentation of estimates and standard errors, but without the full variance-covariance matrix, does not allow subsequent readers either to make inference on a comparison of interest that is not presented or to compare or combine results from different studies where the same variables but different reference levels are used. It is shown how an alternative presentati

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Nyarko, C. C., K. Agyarko, P. K. Nyarko, and L. Brew. "Determinants of Chronic Illness Among Aged Population in Ghana: A Multinomial Logit Approach." Ghana Mining Journal 21, no. 1 (2021): 68–75. http://dx.doi.org/10.4314/gm.v21i1.7.

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Generally, the constant change in demographic trends among the aged depict gradual increase in the size of the aged population globally. The aged population is often capitalised with degenerative conditions such as chronic illness which affect their ability to function effectively and often require special support. Despite the increase in the size of the aged population and their associated degenerative conditions, very few descriptive studies on the determinants of chronic illness among the aged has been researched especially in developing countries such as Ghana and there is no compelling ev

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Bittini, Javier Sada, Salvador Cruz Rambaud, Joaquín López Pascual, and Roberto Moro-Visconti. "Business Models and Sustainability Plans in the FinTech, InsurTech, and PropTech Industry: Evidence from Spain." Sustainability 14, no. 19 (2022): 12088. http://dx.doi.org/10.3390/su141912088.

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After describing the main features of the Spanish companies belonging to the FinTech, InsurTech, and PropTech sectors, the main objective of this study is to analyze whether their B2B/B2C business models are related to the existence of sustainability plans. Specifically, this paper analyzes whether the existence of a sustainability department is a determining factor for the business model adopted by the Spanish FinTechs, InsurTechs, and PropTechs. By using the multinomial logit regression, other factors such as the current closeness of companies to the sustainable development goals (SDGs), the

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Arundina, Tika, and Dato’ Mohd Azmi Omar. "FAKTOR PENENTU PERINGKAT SUKUK." Buletin Ekonomi Moneter dan Perbankan 12, no. 1 (2010): 105–23. http://dx.doi.org/10.21098/bemp.v12i1.351.

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With the development of sukuk market as the Islamic alternatives of the existing bond market, the issue of how to assign a rating to the sukuk issuance rises. This study tries to provide an empirical foundation for the investors to estimate the ratings assign. Using approach from several rating agencies, past researches on bond ratings, financial distress prediction and bankruptcy prediction models, this study is trying to innovate a new model on determining the sukuk ratings. It used Multinomial Logit regression to create a model of rating probability from several theoretical variables, ie. f

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Arundina, Tika, and Dato’ Mohd Azmi Omar. "DETERMINANT OF SUKUK RATINGS." Buletin Ekonomi Moneter dan Perbankan 12, no. 1 (2010): 97–114. http://dx.doi.org/10.21098/bemp.v12i1.468.

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With the development of sukuk market as the Islamic alternatives of the existing bond market, the issue of how to assign a rating to the sukuk issuance rises. This study tries to provide an empirical foundation for the investors to estimate the ratings assign. Using approach from several rating agencies, past researches on bond ratings, financial distress prediction and bankruptcy prediction models, this study is trying to innovate a new model on determining the sukuk ratings. It used Multinomial Logit regression to create a model of rating probability from several theoretical variables, ie. f

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Nandi, Ashim Kumar, and Ann-Zofie Duvander. "Mobile Phone Use and Women’s Empowerment in Bangladesh: An Analysis of the Bangladesh Financial Inclusion Insights Survey 2017." Social Sciences 14, no. 3 (2025): 139. https://doi.org/10.3390/socsci14030139.

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Despite steady economic and social development in Bangladesh, women are in an underprivileged situation in many ways. This study explores the association between the use of information and communication technology (ICT) and women’s empowerment in Bangladesh. This study employs ordinary least squares regression, the ordered logit model, and the multinomial logit model, using Financial Inclusion Insights (2017) Survey data, to investigate the relationship between mobile phone use and women’s empowerment. The study’s main result indicates that mobile phone use facilitates women’s empowerment in g

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