• The Korean Journal of Applied Statistics
• /
• v.33 no.2
• /
• pp.203-213
• /
• 2020

The self-controlled case series (SCCS) study measures the relative risk of exposure to exposure period by setting the non-exposure period of the patient as the control period without a separate control group. This method minimizes the bias that occurs when selecting a control group and is often used to measure the risk of adverse events after taking a drug. This study used SCCS to examine the increased risk of side effects when two or more drugs are used in combination. A conditional Poisson model is assumed and analyzed for drug interaction between the narcotic analgesic, tramadol and multi-frequency combination drugs. Bayesian inference is used to solve the overfitting problem of MLE and the normal or Laplace prior distributions are used to measure the sensitivity of the prior distribution.

• The Korean Journal of Applied Statistics
• /
• v.23 no.6
• /
• pp.1201-1208
• /
• 2010

In teaching probability and statistics classes, we should increase efforts to develop examples that enhance teaching methodology in delivering more meaningful knowledge to students. Sports is one field that provides a variety of examples and World Cup Soccer events are a treasure house of many interesting problems. Teaching, using examples from this field, is an effective way to enhance the interest of students in probability and statistics because World Cup Soccer is a matter of national interest. In this paper, we have suggested several examples pertaining to counting the number of cases and computing probabilities. These examples are related to many issues such as possible scenarios in the preliminary round, victory points necessary for each participant to advance to the second round, and the issue of grouping teams. Based on a simulation using a statistical model, we have proposed a logical method for computing the probabilities of proceeding to the second round and winning the championship for each participant in the 2010 South Africa World Cup.

• The Korean Journal of Applied Statistics
• /
• v.23 no.6
• /
• pp.1179-1190
• /
• 2010

Management of the existing traffic network and understanding current traffic conditions is the most important and effective way to solve traffic congestion. This research investigates the status of Korea expressway through the Speed-Flow-Density diagram and finds the best suitable queueing model for each area. Dynamic structure in the queueing model enables us to reflect the structural change of the road in case of traffic congestion. To find the best model and estimate the parameters, we use the Newton-Raphson method. Finally, we examine the road efficiency in view of the optimal speed and density using the conditional distribution of speed and density of a S-F-D diagram.

• Journal of KIISE:Software and Applications
• /
• v.28 no.9
• /
• pp.681-687
• /
• 2001

In order to raise a class discrimination power by combining multiple classifiers under the Bayesian decision theory, the upper bound of a Bayes error rate bounded by the conditional entropy of a class variable and decision variables obtained from training data samples should be minimized. Wang and Wong proposed a tree dependence first-order approximation scheme of a high order probability distribution composed of the class and multiple feature pattern variables for minimizing the upper bound of the Bayes error rate. This paper presents an extended high order product approximation scheme dealing with higher order dependency more than the first-order tree dependence, based on the minimization of the upper bound of the Bayes error rate. Multiple recognizers for unconstrained handwritten numerals from CENPARMI were combined by the proposed approximation scheme using the Bayesian formalism, and the high recognition rates were obtained by them.

• Korean Journal of Clinical Pharmacy
• /
• v.26 no.4
• /
• pp.312-317
• /
• 2016

Objective: Midazolam is mainly metabolized by cytochrome P450 (CYP) 3A. Inhibition or induction of CYP3A can affect the pharmacological activity of midazolam. The aims of this study were to develop a population pharmacokinetic (PK) model and evaluate the effect of CYP3A-mediated interactions among ketoconazole, rifampicin, and midazolam. Methods: Three-treatment, three-period, crossover study was conducted in 24 healthy male subjects. Each subject received 1 mg midazolam (control), 1 mg midazolam after pretreatment with 400 mg ketoconazole once daily for 4 days (CYP3A inhibition phase), and 2.5 mg midazolam after pretreatment with 600 mg rifampicin once daily for 10 days (CYP3A induction phase). The population PK analysis was performed using a nonlinear mixed effect model ($NONMEM^{(R)}$ 7.2) based on plasma midazolam concentrations. The PK model was developed, and the first-order conditional estimation with interaction was applied for the model run. A three-compartment model with first-order elimination described the PK. The influence of ketoconazole and rifampicin, CYP3A5 genotype, and demographic characteristics on PK parameters was examined. Goodness-of-fit (GOF) diagnostics and visual predictive checks, as well as bootstrap were used to evaluate the adequacy of the model fit and predictions. Results: Twenty-four subjects contributed to 900 midazolam concentrations. The final parameter estimates (% relative standard error, RSE) were as follows; clearance (CL), 31.8 L/h (6.0%); inter-compartmental clearance (Q) 2, 36.4 L/h (9.7%); Q3, 7.37 L/h (12.0%), volume of distribution (V) 1, 70.7 L (3.6%), V2, 32.9 L (8.8%); and V3, 44.4 L (6.7%). The midazolam CL decreased and increased to 32.5 and 199.9% in the inhibition and induction phases, respectively, compared to that in control phase. Conclusion: A PK model for midazolam co-treatment with ketoconazole and rifampicin was developed using data of healthy volunteers, and the subject's CYP3A status influenced the midazolam PK parameters. Therefore, a population PK model with enzyme-mediated drug interactions may be useful for quantitatively predicting PK alterations.

• Convergence Security Journal
• /
• v.12 no.6
• /
• pp.85-92
• /
• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• The Korean Journal of Applied Statistics
• /
• v.23 no.2
• /
• pp.219-234
• /
• 2010

In index investing according to KOSPI, we estimate Value at Risk(VaR) from the extreme losses of the daily returns which are obtained from KOSPI. To this end, we apply Block Maxima(BM) model which is one of the useful models in the extreme value theory. We also estimate the extremal index to consider the dependency in the occurrence of extreme losses. From the back-testing based on the failure rate method, we can see that the model is adaptable for the VaR estimation. We also compare this model with the GARCH model which is commonly used for the VaR estimation. Back-testing says that there is no meaningful difference between the two models if we assume that the conditional returns follow the t-distribution. However, the estimated VaR based on GARCH model is sensitive to the extreme losses occurred near the epoch of estimation, while that on BM model is not. Thus, estimating the VaR based on GARCH model is preferred for the short-term prediction. However, for the long-term prediction, BM model is better.

• The Korean Journal of Applied Statistics
• /
• v.32 no.5
• /
• pp.763-782
• /
• 2019

This paper proposes a probabilistic document ranking model incorporating term dependencies. Document ranking is a fundamental information retrieval task. The task is to sort documents in a collection according to the relevance to the user query (Qin et al., Information Retrieval Journal, 13, 346-374, 2010). A probabilistic model is a model for computing the conditional probability of the relevance of each document given query. Most of the widely used models assume the term independence because it is challenging to compute the joint probabilities of multiple terms. Words in natural language texts are obviously highly correlated. In this paper, we assume a multinomial distribution model to calculate the relevance probability of a document by considering the dependency structure of words, and propose an information retrieval model to rank a document by estimating the probability with the maximum entropy method. The results of the ranking simulation experiment in various multinomial situations show better retrieval results than a model that assumes the independence of words. The results of document ranking experiments using real-world datasets LETOR OHSUMED also show better retrieval results.

• Korean Journal of Clinical Pharmacy
• /
• v.26 no.2
• /
• pp.137-149
• /
• 2016

Objective: Online pharmacies were introduced in some countries such as United States of America or Canada. They can provide benefits to consumer because they can buy and take conveniently drugs without limitation of location or time. In Korea, online pharmacies are illegal and only pharmacists can sell drugs to consumers or patients. Therefore, we investigated the knowledge of online pharmacy and the possible problem in Korea to survey pharmacists. Methods: We developed questionnaire based on previous articles about online pharmacy and surveyed nation-wide pharmacists by mail or e-mail. The data was analyzed by SPSS and Microsoft Excel. P-values less than 0.05 were statistically significant. Results: 175 pharmacists involved in this study. About introduction of online pharmacies, 53.1% were opposition while 10.3% were approval and 36.6% were conditional. Although online pharmacies were introduced, 46.3% pharmacists do not have a plan to start online pharmacy. However, the approval and tends about starting online pharmacies were higher in younger pharmacists (20s, 30s) (p < 0.05). The criteria of permission about opening online pharmacies were 100% pharmacist license regardless of holding off-line pharmacy. 53.7% pharmacists responded education about taking medication is impossible. When online pharmacies are introduced, 65.1% pharmacists responded traditional pharmacies are affected negatively. Pharmacists concerned that the competition with large-sized distribution corporations, reduced reliance between pharmacists and patients, illegal transaction of counterfeit drugs, increased misuse of drugs. Conclusion: These results showed that Korea pharmacists have negative standard on online pharmacies. Therefore it is required to be more cautious before introducing online pharmacy and it need strict watching system and continuous education and study for safety after introducing online pharmacy.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.13
• /
• pp.5337-5341
• /
• 2015

Background: Individual susceptibility to cancer has been attributed to polymorphisms in xenobiotic metabolizing genes. To evaluate the association of the Leu432Val polymorphism of cytochrome P4501B1 (CYP1B1) with esophageal squamous cell carcinoma (ESCC), we conducted a case control study in Kashmir, India, an area with a relatively high incidence of ESCC. Materials and Methods: We recruited 404 histopathologically confirmed ESCC cases, and an equal number of controls, individually matched for sex, age and district of residence to respective cases. Information was obtained on various dietary, lifestyle and environmental factors in face to face interviews, using a structured questionnaire, from each subject. Genotypes were analysed by polymerase chain reaction, restriction fragment length polymorphism and sequencing of randomly selected samples. Conditional logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs). Results: Among the three possible variants, we did not find any Leu432Leu genotype of CYP1B1 in the study population and the genotypic distribution of Val432Val and Leu432Val carriers was nearly equal in both cases (89.6% and 10.4%) and controls (88.9% and 11.1%) respectively. We did not find any risk associated with this polymorphism in the current study (OR = 0.64; 95% CI: 0.55 - 1.64). Conclusions: The study indicates that (Leu432Val) polymorphism of CYP1B1, is not associated with ESCC risk. However, replicative studies with larger sample size are needed to substantiate the findings.