• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.589-602
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• 2008

This article studies on disability pensioners' characteristic with multinomial logit and logistic regression model. Seven factors are examined on whether each factor is reflected in degree of disability in the disability pension. By incorporating multinomial logit and logistic regression model, effectiveness and characteristic of the seven factors are investigated on the degree of disability. Result shows all the seven factors are significant on the degree of disability, while among the seven, five factors, age, sex, type of coverage, type of category, insured duration show a trend in degree of disability and the other two, cause of disability and class of standard monthly income are not effective on trend in degree of disability. Results from analyses might be useful for disability pension management.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.889-902
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• 2013

Several goodness-of-fit test statistics have been proposed for a multinomial logit regression model; however, the properties of the proposed tests were not adequately studied. This paper evaluates three different goodness-of-fit tests using grouping strategies, proposed by Fagerland et al. (2008), Bull (1994), and Pigeon and Heyse (1999). In addition, Pearson (1900)'s method is also examined as a reference. Simulation studies were conducted to evaluate the four methods in terms of null distribution and power. A real data example is presented to illustrate the methods.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.217-223
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• 2016

Outcome misclassification is widespread in classification problems, but methods to account for it are rarely used. In this paper, the problem of inference with misclassified multinomial logit data with a large number of multinomial parameters is addressed. We have had a significant swell of interest in the development of novel methods to infer misclassified data. One simulation study is shown regarding how seriously misclassification issue occurs if the number of categories increase. Then, using the group lasso regression, we will show how the best model should be fitted for that kind of multinomial regression problems comprehensively.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.859-869
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• 2011

Interest has increased in academic research regarding key factors that drive box-office success as well as the ability to predict the box-office success of a movie from a commercial perspective. This study analyzed the relationship between key success factors of a movie and box office records based on movies released in 2010 in Korea. At the pre-production investment decision-making stage, the movie genre, motion picture rating, director power, and actor power were statistically significant. At the stage of distribution decision-making process after movie production, among other factors, the influence of star actors, number of screens, power of distributors, and social media turned out to be statistically significant. We verified movie success factors through the application of a Multinomial Logit Model that used the concept of choice probabilities. The Multinomial Logit Model resulted in a higher level of accuracy in predicting box-office success compared to the Artificial Neural Network and Discriminant Analysis.

• Journal of Labour Economics
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• v.43 no.4
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• pp.117-141
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• 2020

The paper focuses on the question of whether and how the labor underutilization indicator supplements the unemployment rate. The research is based on the differences in the labor market behavior among three groups of the not-employed; the unemployed, potential labor force and the rest of outside the labor force. The annual transition rate among the labor market states shows that the potential labor force has the explicit unmet need for employment different from the rest of the outside the labor force. The multinomial logit regression controlling the effects of individual characteristics rejects the hypothesis that the potential labor forces are behaviorally identical to the unemployed. The evidence shows that the two indices should be interpreted distinctively.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.313-322
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• 2005

In this paper, we discuss suppression for logistic regression model. Suppression for linear regression model was defined as the relationship among sums of squared for regression as well as correlation coefficients of. variables. Since it is not common to obtain simple correlation coefficient for binary response variable of logistic model, we consider cumulative logistic models with multinomial and ordinal response variables rather than usual logistic model. As number of category of a response variable for the cumulative logistic model gets collapsed into binary, it is found that suppressions for these logistic models are changed. These suppression results for cumulative logistic models are discussed and compared with those of linear model.

• The Korean Journal of Community Living Science
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• v.21 no.4
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• pp.619-631
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• 2010

The purpose of this study is to segment and examine urban farmers behavior by applying a two-step cluster analysis and multi-nominal logit model. The data were collected by a telephone survey with two-staged stratified random sampling in the cities around the country for the purpose of acquiring representative data. Respondents were asked to describe their awareness of urban agriculture, their agricultural activity, and sociodemographic characteristics. Among 2,000 cases, 381 cases(19.1%) which were of participants in urban agriculture were analysed in SPSS. From the findings, 27.3% of respondents had heard the word 'urban agriculture', and 25.5% of them regarded themselves as urban farmers. Four different clusters were derived from two-step clusters based on motive, place, companion, area and hours. They were 'Large scale hobby farming(cluster 1)', ‘Weekend farm/ hobby farming(cluster 2)', 'Land/ Self-supporting farming(cluster 3)', and 'Small scale hobby farming(cluster 4)'. The result of multinomial logistic regression showed that there were significant differences among these four segmented groups in terms of age, city size and housing type. In other words, there is quite a possibility that urbanites select different urban farming types according to their socio-demographic profiles. Therefore, the urbanite profiles can be used as the basis for promoting policy of several urban agriculture types. According to the result, policy directions for facilitating urban agriculture were presented.

• Health Policy and Management
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• v.20 no.1
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• pp.87-102
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• 2010

The objective of this study were to examine the impact of medicaid coverage expansion policy aimed at improving access to primary care. The case-control study was conducted to compare preventable hospitalization(PH) rate in new medicaid recipients versus national health insurance(NHI) enrollees form 1996 to 2001. Rates of preventable hospitalization associated with ambulatory care sensitive conditions(ACSC) were calculated and standardized by age and sex. Multinomial logit regression model was used to control the confounding factors such as age, gender and charlson comorbidity index Annual PH rates in the new medicaid increased 1.64 times after medicaid expansion, with controling confounding factors. Meanwhile, annual PH rate in the NHI increased 1.68 times during the same period, with adjusting confounding factors. Current findings suggest that the new medicaid PH rate was less likely to rise than NHI PH rate after implementing medicaid expansion. This study is expected to provide policy-relevant evidence of medicaid expansion to include population with low income.

• Journal of Labour Economics
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• v.27 no.1
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• pp.135-164
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• 2004

Using the data from the KLIPS, this study categorizes unemployed women into the four mutually exclusive groups according to the two criteria (whether to have intention to work and the comparison of reservation and market wages), and investigates factors affecting the status of the unemployment of women. Heckman's sample selection regression and multinomial logit are applied for the estimation. The major results are: the proportion of unemployed women who do not have intension to work or whose reservation wages are greater than expected market wages is about 50%, and the proportion of unemployed women who have intension to work or whose reservation wages are less than expected market wages is about 50%; second, human capital, burden of child raising and household production, household economic status, the variables related to work experience are found to be the factors affecting unemployment status of women.

• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.251-276
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• 2014

This study scrutinizes the common sense in the field of disability employment that the bigger the size of a firm, the lower the employment rate of people with disabilities. This common sense has been established by conventional cross-tabulation and multiple regression analyses without taking into account possible interactions between the sizes of firms and the industries in which they operate. This study shows that the distribution of the disability employment rate violates the linearity and homoscedasticity assumptions of the OLS. In an effort to find models that explain the data better, this study fits the OLS model, the weighted linear regression model, and the multinomial logit model as well as the path analysis which is meant to examine the relationships between firm size and other variables relevant to disability employment. The result shows that, when an interaction term between firm size and industry is added to the model, firm size does not have any significant effect on disability employment rate for those firms with 100 or more regular employees, to the contrary of the findings of prior studies. It also demonstrates that other factors such as job setting, the extent of helpfulness of disability employment employers perceive, employers' care for disability, and employers' awareness of disability policies may matter more than does firm size. This study proposes that future research and policy implementation for disability employment should pay no less attention to industry and other factors mentioned above than to firm size.