• The Korean Journal of Pain
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• v.27 no.3
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• pp.246-252
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• 2014

Background: Neuropathic pain is generally defined as a chronic pain state resulting from peripheral and/or central nerve injury. There is a lack of effective treatment for neuropathic pain, which may possibly be related to poor understanding of pathological mechanisms at the molecular level. Curcumin, a therapeutic herbal extract, has shown to be effectively capable of reducing chronic pain induced by peripheral administration of inflammatory agents such as formalin. In this study, we aimed to show the effect of curcumin on pain behavior and serum COX-2 level in a Chronic Constriction Injury (CCI) model of neuropathic pain. Methods: Wistar male rats (150-200 g, n = 8) were divided into three groups: CCI vehicle-treated, sham-operated, and CCI drug-treated group. Curcumin (12.5, 25, 50 mg/kg, IP) was injected 24 h before surgery and continued daily for 7 days post-surgery. Behavioral tests were performed once before and following the days 1, 3, 5, 7 after surgery. The serum COX-2 level was measured on day 7 after the surgery. Results: Curcumin (50 mg/kg) decreased mechanical and cold allodynia (P < 0.001) and produced a decline in serum COX-2 level (P < 0.001). Conclusions: A considerable decline in pain behavior and serum COX-2 levels was seen in rat following administration of curcumin in CCI model of neuropathic pain. High concentration of Curcumin was able to reduce the chronic neuropathic pain induced by CCI model and the serum level of COX-2.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.349-359
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• 2017

In this paper, we conducted survival analyses by fitting the Cox proportional hazards model to stage III proximal colon cancer data obtained from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute. We investigated the effect of covariates on the hazard function for death from proximal colon cancer in stage III with surgery performed and estimated the survival probability for a patient with specific covariates. We showed that the proportional hazards assumption is satisfied for covariates that were used to analyses, using a test based on the Schoenfeld residuals and plots of the Schoenfeld residuals and $log[-log\{{\hat{S}}(t)\}]$. We evaluated the model calibration and discriminatory accuracy by calibration plot and time-dependent area under the ROC curve, which were calculated using 10-fold cross validation.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.241-247
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• 2015

The purpose of the warranty data analysis can be classified into two categories. Two goals is a failure cause analysis and life prediction analysis. In this paper first, we applied multivariate analysis method that can be estimated in consideration of various factors on the failure cause warranty data. In particular, we apply the Tree model and Cox model. The advantage of the Tree is easy to interpret this result as compared to other models. In addition Cox model can quantitatively express the risk. Second, this paper proposed a multivariate life prediction model (AFT) considering a variety of factors. By applying the actual warranty data confirmed the usability.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.21-29
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• 2009

Engle and Russell (1998) proposed the ACD(Autoregressive Conditional Duration) model to explain the relationship between the prices and the duration times of the stocks. In this paper, we first introduce the various types of the ACD models such as the linear ACD, log ACD and Box-Cox ACD models and we evaluate the performance of the models for analysing the transaction data of the stocks in Korea.

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.1-11
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• 1993

The Cox's regression model is frequently used for covariate effects in survival data analysis, But, much of the statistical work has focused on asymptotic behavior so the small sample evaluation has been neglected. In this paper, we compare the small or moderate sample performances of the survival function estimators for the Cox's regression model using bootstrap method. The smoothed PL type estimator and the Link estimator are slightly better than corresponding the PL type estimator and the Nelson type estimator in the sense of the achieved error rates.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.94.2-94.2
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• 2003

CJ-11668 is a new potent and selective COX-2 inhibitor. CJ-11668 showed COX-2 inhibition (IC50) of 65nM and selectivity ratio (COX-l/COX-2) of 770 in the cell based assay. In the human whole blood assay, CJ-11668 showed COX-2 inhibition (IC50) of 370nM and selectivity ratio (COX-l/COX-2), 135. The treatment of CJ-11668 (5 mg/kg, p.o) produced a significant inhibition (35%) of inflamed rat paw volume in the carrageenan-induced acute inflammation. CJ-11668 also suppressed the PGE2 level (69% inhibition, 1 mg/kg, p.o) in the zymosan-induced mouse air pouch model after 3 hrs. (omitted)

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.189-196
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• 2004

The sensitivity of the multivariate Box-Cox transformation model to simultaneous perturbations of all the data based on the likelihood displacement is studied in order to detect outliers. An example is given for illustration.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.227-233
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• 2004

This paper presents our work on constructing a model that is intended to predict the probability of attrition at specified points in time among customers of an insurance company. There are some difficulties in building a data-based model because a data set may contain possibly censored observations. In an effort to avoid such kind of problem, we performed logistic regression over specified time intervals while using explanatory variables to construct the proposed model. Then, we developed a Cox-type regression model for estimating the probability of attrition over a specified period of time using time-dependent explanatory variables subject to changes in value over the course of the observations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.143-150
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• 2006

Box-Cox model and T-factor method have been widely used to measure economic depreciations for industrial property. The Box-Cox model which combines economic efficiency with depreciation pattern is here extended to the reliability function. To do so a Rayleigh distribution which has been used to estimate the reliability of current assets was chosen as an efficiency curve of marginal productivity. Such an approach provides the possibility to classify the efficiency curves into four categories. It is also possible to analyze the types of depreciation curves. Therefore, the power family of a non-linear Box-Cox model could be set at certain constant values, then the model can be transformed into a linear model to estimate the economic depreciation rates by utilizing the reliability function. Estimating the resultant linear regression equation requires minimal number of observations, while at the same time facilitating the test of hypothesis on depreciation rates.