• 대한가정학회지
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• 제39권3호
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• pp.35-45
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• 2001

The purposes of this study are to identify the factors associated with the degree of role conflict and the likelihood of exits of the labor force of working wives and to investigate the relationship between the role conflict and job quitting behavior of working wives. The major results of this study are as follows. First, the ratio of reservation wage relative to wife's earnings, wife's earnings, husband's behavioral support, the presence of child under age of 6, the type of occupation, and job satisfaction are associated with the role conflict of working wives. Second, there is a significant difference in the job quitting behavior of working wives according to the degree of role conflict of working wives. Third, the level of role conflict, educational level, the ratio of resonation wage relative to wife's earnings, husband's behavioral support, the presence of child under age of 6, the type of occupation, and job satisfaction are associated with the likelihood of job quitting of working wives.

• Communications for Statistical Applications and Methods
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• 제20권3호
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• pp.217-223
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• 2013

Two influence diagnostic methods for the common mean model are proposed. First, an investigation of the influence of observations according to minor perturbations of the common mean model is made by adapting the local influence method which is based on the likelihood displacement. It is well known that the maximum likelihood estimates are in general sensitive to influential observations. Case-deletions can be a candidate for detecting influential observations. However, the maximum likelihood estimators are iteratively computed and therefore case-deletions involve an enormous amount of computations. An approximation by Newton's method to the maximum likelihood estimator obtained after a single observation was deleted can reduce much of computational burden, which will be treated in this work. A numerical example is given for illustration and it shows that the proposed diagnostic methods can be useful tools.

• Communications for Statistical Applications and Methods
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• 제26권3호
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• pp.315-323
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• 2019

Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.187-198
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• 2020

This study investigates the determinants of the likelihood of a tax re-audit in Korea. It adopts a researcher-administered questionnaire survey method for data collection. The survey questionnaire is randomly distributed to 1,120 individuals with tax-related knowledge and experience. Using a final sample of 342 responses, we conduct a cross-sectional regression analysis to test our hypotheses. The results show that the level of tax non-compliance significantly affects the likelihood of a tax re-audit. This finding suggests that the increase in re-audits in Korea is attributable to the tendency of the tax authority to conduct a re-audit to detect taxpayers' non-compliance behavior by excessively broadening the scope of re-audits. This study also finds that the level of tax non-compliance is influenced by the perception of procedural unfairness, measured by operational inconsistency and regulatory lack of clarity. Lastly, the results reveal that the level of tax non-compliance mediates the relationship between the perception of procedural unfairness and likelihood of a tax re-audit. This finding indicates that enhancing procedural fairness could fundamentally reduce unnecessary re-audits that infringe on the rights of taxpayers, as the likelihood of a tax re-audit is not solely determined by the level of tax non-compliance but also by perceived procedural fairness.

• 천문학회지
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• 제25권1호
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• pp.1-9
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• 1992

We present new approach to analysis of velocity data of globular clusters. Maximum likelihood method is applied to get model parameters such as central potential, anisotropy radius, and total mass fractions in each mass class. This method can avoid problems in conventional binning method of chi-square. We utilize three velocity components, one from line of sight radial velocity and two from proper motion data. In our simplified scheme we adopt 3 mass-component model with unseen high mass stars, intermediate visible stars, and low mass dark remnants. Likelihood values are obtained for 124 stars in M13 for various model parameters. Our preferred model shows central potential of $W_o=7$ and anisotropy radius with 7 core radius. And it suggests non-negligible amount of unseen high mass stars and considerable amount of dark remnants in M13.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.381-397
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• 2004

The marginal likelihood has become an important tool for model selection in Bayesian analysis because it can be used to rank the models. We discuss the marginal likelihood for Poisson regression models that are potentially useful in small area estimation. Computation in these models is intensive and it requires an implementation of Markov chain Monte Carlo (MCMC) methods. Using importance sampling and multivariate density estimation, we demonstrate a computation of the marginal likelihood through an output analysis from an MCMC sampler.

• Journal of the Korean Statistical Society
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• 제30권3호
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• pp.467-480
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• 2001

This paper considers the use of local $\phi$-divergence measures between posterior distributions under classes of perturbations in order to investigate the inherent robustness of certain classes. The smaller value of the limiting local $\phi$-divergence implies more robustness for the prior or the likelihood. We consider the cases when the likelihood comes form the class of weighted distribution. Two kinds of perturbations are considered for the local sensitivity analysis. In addition, some numerical examples are considered which provide measures of robustness.

• Journal of the Korean Statistical Society
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• 제12권1호
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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.

• 한국산업융합학회 논문집
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• 제9권3호
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• pp.207-214
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• 2006

In this paper, the stability of SA(Spectral Acceleration) fragility curves is studied for the two sets of elastic modulus of concrete. In doing that, general purpose structural analysis program and generally used probability density function are used. The results of structural analysis are represented by Bernoulli distribution which says damage or no damage. By the use of Maximum Likelihood Method, two parameters of lognormal distribution - median and standard deviation - are found. With them, the fragility curves are constructed.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.401-410
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• 2005

In this paper, we calculate the premium rate of reliability insurance policy for brake pads for automobiles using real failure data obtained from use-condition. We try process capability analysis for the manufacturing process of brake-system. We describe the performance factors which have an effect on failure characteristics of brake pads. We also obtain the maximum likelihood estimates of shape and scale parameters of the fitted Weibull distribution for brake pads.