• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.735-749
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• 2008

This article suggests application of logit model for analysis of multicategory responses. Referring to the reference category, characteristic of each category is obtained from analysis of polytomous logit model. With National Pension data it is illustrated that application of logit model helps it possible to find significant factors which may not be found only with polytomous logit model. Application of the logit model is done by reducing the number of categories. Categories are grouped into the former and the latter group according to reference category. Extra finding of significant factor was possible from logistic regression analysis for the two groups after removing the reference category. It is expected that this application would be helpful for finding information and characteristics on ordered multicategory responses where the proportional odds model does not fit.

• Journal of Distribution Science
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• v.17 no.11
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• pp.73-79
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• 2019

Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

• Journal of the Korean Institute of Landscape Architecture
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• v.22 no.3
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• pp.1-12
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• 1994

This study was carried out to identify destination choice behavior for one-day use recreation areas. Previous positioning study was utilized to select 4 study areas, and the secondary data were used for logit analyses. The Hausamn-McFadden test for IIA was conducted to examine whether conditional logit models are valid methodology for this study. The results revealed that IIA assumption among the study areas was violated; therefore, generalized binomial and generalized multinomial logit models were used in this study. In the binomial logit analysis, 2 to 5 independent variables were included in the models: their $\rho$2 values were from 0.1to 0.323, and accuracy of predictions were from 65.38 to 79.86 percent. In the multinomial logit analysis, 4 independent variables were included in the model: its $\rho$2 value was 0.207, and accuracy of prediction was 45.82 percent. The results showed that the conditional logit should be used with caution because of the IIA assumption. Several suggestions were described, mainly due to utilization of the secondary data for this study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.1-8
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• 1997

In case of analysis of discrete data, it shows by way of example orthogonal array experiment for o, 1 data. This paper introduced expirical logit transformation and the type of Freeman-Tukey inverse sine transformation. As the result of analysis of variance, empirical logit transformation turned out a mistake in application but it is possible for graphical analysis by normal probability paper.

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

• The Journal of Korean Academy of Sensory Integration
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• v.18 no.2
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• pp.15-28
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• 2020

Objective : The purpose of this study was to verify the construct validity of Short Sensory Profile-2 (SSP-2) for children with Autism Spectrum Disorder (ASD). Methods : Data were collected from SSP-2 for 120 parents of ASD children. Raw data were analyzed by applying the Rasch analysis to the goodness fit of person and item, item difficulty, rating scale, and separation reliability of SSP-2. Results : 7 persons in sensory processing area and 8 persons in behavioral response area were inappropriate criteria and excluded from the analysis. Item goodness-of-fit analysis determined that the If the Mnsq value is between 0.6 and 1.4 and the Z value is outside the ±2 range for nonconformity. this study All items in the instrument were found to have appropriate criteria. Item difficulty analysis in sensory processing area was high in item 13 (.48 logit) and low in item 10 (-.54 logit). In the behavioral response area, item 25 (1.58 logit) was high and item 30 (-.68 logit) was low. In the rating scale analysis, it was found that the 3-point scale is more appropriate than the 5-point scale. The separation reliability of sensory processing area was .90 and the behavioral response area was .95. Conclusion : This study verified the construct validity of SSP-2 and expected to be applied as a useful evaluation tool for children with ASD.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.437-444
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• 2017

The purpose of this study is to analyze the factors affecting the reverse mortgage utilization and satisfaction of the elderly. Based on the survey data of the reverse mortgage demand in 2016, we carried out empirical analysis using the binary logit model and the ordered logit model. First of all, as a result of the empirical analysis using the binary logit model, the determinants of using the reverse mortgage were age, region, assets, household member, children with financial help, and education level. As a result of the empirical analysis using the ordered logit model, the determinants of the satisfaction level of the reverse mortgage were estimated to be age, gender, and region. Based on the results of the empirical analysis, it is necessary to find a way to increase the participation rate of the reverse mortgage and to improve the satisfaction of the user.

• The Journal of Industrial Distribution & Business
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• v.8 no.4
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• pp.47-52
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• 2017

Purpose - This current study will investigate the average financial ratio of top and failed five-star hotels in the Jeju area. A total of 14 financial ratio variables are utilized. This study aims to; first, assess financial ratio of the first-class hotels in Jeju to establishing variables, second, develop distress prediction model for the first-class hotels in Jeju district by using logit analysis and third, evaluate distress prediction capacity for the first-class hotels in Jeju district by using logit analysis. Research design, data, and methodology - The sample was collected from year 2015 and 14 financial ratios of 12 first-class hotels in Jeju district. The results from the samples were analyzed by t-test, and the independent variables were chosen. This was an empirical study where the distress prediction model was evaluated by logit analysis. This current research has focused on critically analyzing and differentiating between the top and failed hotels in the Jeju area by utilizing the 14 financial ratio variables. Results - The verification result of the accuracy estimated by logit analysis has shown to indicate that the distress prediction model's distress prediction capacity was 83.3%. In order to extract the factors that differentiated the top hotels in the Jeju area from the failed hotels among the 14 chosen, the analysis of t-black was utilized by independent variables. Logit analysis was also used in this study. As a result, it was observed that 5 variables were statistically significant and are included in the logit analysis for discernment of top and failed hotels in the Jeju area. Conclusions - The distress prediction press' prediction capability was compared in this research analysis. The distress prediction press prediction capability was shown to range from 75-85% by logit analysis from a previous study. In this current research, the study's prediction capacity was shown to be 83.33%. It was considered a high number and was found to belong to the range of the previous study's prediction capacity range. From a practical perspective, the capacity of the assessment of the distress prediction model in the top and failed hotels in the Jeju area was considered to be a prominent factor in applications of future hotel appraisal.

• Journal of Families and Better Life
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• v.10 no.1 s.19
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• pp.131-138
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• 1992

Regression analysis has become a standard statistical tool in the behavioral science. Because of its widespread popularity. regression has been often misused. Such is the case when the dependent variable is a qualitative measure rather than a continuous, interval measure. Regression estimates with a qualitative dependent variable does not meet the assumptions underlying regression. It can lead to serious errors in the standard statistical inference. Logit model is recommended as alternatives to the regression model for qualitative dependent variables. Researchers can employ this model to measure the relationship between independent variables and qualitative dependent variables without assuming that logit model was derived from probabilistic choice theory. Coefficients in logit model are typically estimated by the method of Maximum Likelihood Estimation in contrast to ordinary regression model which estimated by the method of Least Squares Estimation. Goodness of fit in logit model is based on the likelihood ratio statistics and the t-statistics is used for testing the null hypothesis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.151-156
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• 2019

This study aims to develop a distress prediction model and to evaluate distress prediction power for the food services industry by using 2017 food service industry financial ratios. Samples were collected from 46 food service industries, and we extracted 14 financial ratios from them. The results show that, first, there are eight ratios (financial ratio, current ratio, operating income to sales, net income to assets, ratio of cash flows, income to stockholders' equity, rate of operating income, and total asset turnover) that can discriminate failures in food service industries and the top-level food service industries. Second, by using these eight financial ratios, the logit function classifies the top-level food service industries, and failures in the food service industry can be estimated by using logit analysis. The verification results as to accuracy in the estimated logit analysis indicate that the model's distress-prediction power is 89.1%.