• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.379-393
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• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• Korean Journal of Social Welfare
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• v.63 no.4
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• pp.83-107
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• 2011

This study examines the duration dependence in the exit rate from National Basic Livelihood Protection Program(NBLP). If the length of time on welfare is negatively correlated with the exit rate after controlling for 'unobserved heterogeneity', the observed declining exit rates would provide evidence of true duration dependence. Data are drawn from Korean Welfare Panel study 2005~2008. A variety of discrete-time hazard models are estimated, including parametric/nonparametric hazard model, gamma frailty hazard model/mass point technique model. It is found that welfare dynamics in Korea does not show strong evidence of duration dependence after controlling for unobserved heterogeneity. All the models estimated show that this finding is quite robust. The observed declining exit rate is largely due to differences in the unobservable characteristics of recipients. Thus, the detrimental effect of the welfare on the preference and attitude among recipients is not likely to be strengthened as time on welfare increases.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

• Journal of Life Science
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• v.33 no.3
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• pp.277-286
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• 2023

Sarcopenia is the age-related loss of muscle mass and function. It is a natural part of aging and can lead to decreased mobility and increased frailty. The ubiquitin-proteasome pathway, which is involved in muscle protein degradation, is closely linked to sarcopenia. Germinated Rhynchosia nulubilis hydrolysate (GRH) has been reported to have anti-inflammatory and antioxidant properties, but there have been no reports on its inhibitory effect on muscle reduction. However, no study has yet explored the relationship between GRH and muscle loss inhibition. In this study, we evaluated the effects of GRH on muscle atrophy inhibitory activity in dexamethasone (Dexa)-induced muscle atrophy C2C12 myotubes and mouse models. Moreover, we identified a molecular pathway underlying the effects of GRH on skeletal muscle. May Grunwald-Giemsa staining showed that the length and area of myotubes increased in the groups treated with GRH. In addition, the GRH-treated group significantly reduced the expression of muscle ring finger protein 1 and muscular atrophy F-box (MAFbx) in the Dexa-induced muscular atrophy C2C12 model. GRH also improved muscle strength in C57BL/6 mice with Dexa-induced muscle atrophy, resulting in prolonged running exhaustive time and increased grip strength. We found that muscle strengthening by GRH was correlated with a decreased expression of the MAFbx gene in mouse muscle tissue. In conclusion, GRH can attenuate Dexa-induced muscle atrophy by inhibiting the ubiquitin-proteasome pathway via downregulation of the MAFbx gene expression.