• Journal of Labour Economics
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• v.29 no.2
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• pp.145-169
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• 2006

This study analyze the effect on wage, labor mobility by using Craft II Class certification out of National skill certification. In this article, we used the parametric and nonparametric method. In the former we used IV that the fraction of certification by occupation by firm scale to solve the selection problem. In the latter, it's used matching method and kernel regression. The paper shows that certification effect on wage has about 5.1~9.9%. The result of analysis between certification and labor mobility indicates better certification effects on long term tenure to the same firm than certification effects on wage from labor mobility. Also, we knew that the employee which have no certification relative is difficult to be established in the same workplace.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.53-63
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• 2008

It is commonly believed that disease of human or economic traits of livestock are caused not by single gene acting alone, but by multiple genes interacting with one an-other. This issue is difficult due to the limitations of parametric statistical method like as logistic regression for detection of gene effects that are dependent solely on interactions with other genes and with environmental exposures. Multifactor dimensionality reduction (MDR) nonparametric statistical method, to improve the identification of single nucleotide polymorphism (SNP) associated with the Hanwoo(Korean cattle) carcass cold weight, is applied and compared with ANOVA results.

• The Journal of Korean Physical Therapy
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• v.20 no.4
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• pp.21-28
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• 2008

Purpose: We measured the Oswestry Low Back Pain Disability Index (OLBPDI) and related factors in patients with low back pain. Methods: The sample consisted of 50 patients who received physical therapy at the physical therapy units of the Andong Seoul Sintong Clinic, St. Luke Clinic, and Yeongju Seoul Sintong Clinic in Andong and Yeongju city from October, 2007, to February, 2008. The OLBPDI questionnaire was administered by 5 physical therapists as a cross-sectional study. Student's t-test and analysis of variance (ANOVA/Tukey and Scheffe) were used to analyze OLBPDI score differences. We also used nonparametric statistic analysis (Wilcoxon rank sum test, Median test). Pearson correlation analysis (Spearman correlation analysis) was used to analyze the relationship between OLBPDI and the visual analogue scale (VAS). Multiple regression analysis was performed to determine the effects of independent variables on pain scores as defined by the OLBPDI. Results: The average patient age was 37.1 years (range: 18$\sim$78 years old), and time from onset was 21.7 months (1$\sim$180). OLBPD and VAS scores were 12.70 (3.0$\sim$28.0) and 5.14 (1$\sim$8), respectively. OLBPDI scores were 14.4 in patients taking medicine and 11.57 in those who did not. There was a statistically significant relationship between OLBPDI and VAS (r=0.54, p=0.0001; r=0.55, p=0.0001 by Spearman coefficient). Gender ($\beta$=6.14, p=0.0124), age ($\beta$=-2.01, p=0.0324), weight ($\beta$=0.31, p=0.0222), time from onset ($\beta$=1.54, p=0.0044), and VAS score ($\beta$=1.59, p=0.0004) were significantly associated with OLBPD by multiple regression analysis. Conclusion: Variables associated with OLBPD were gender, age, weight, time from onset, and VAS score. Collecting information on the pain index using OLBPDI was acceptable to patients with low back pain. Further research should explore the pain index by using larger sample sizes and longer follow-up periods.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3243-3248
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• 2016

Background: Stomach cancer is the fourth most common cancer and the second leading cause of death from cancer in the world. In Iran, this type of cancer has high rates of incidence and mortality. This study aimed to assess the survival rate of patients with stomach cancer and its determinants in Kurdistan, a province with one of the highest incidence rates of stomach cancer in the country. Materials and Methods: We studied a total of 202 patients with stomach cancer who were admitted to Tohid Hospital in Sanandaj from 2009 to 2013. Using Kaplan-Meier nonparametric methods the survival rate of patients was calculated in terms of different levels of age at diagnosis, gender, education, residential area, occupation, underweight, and clinical variables including tumor histology, site of tumor, disease stage, and type of treatment. In addition, we compared the survival rates using the log-rank test. Finally, Cox proportional hazards regression was applied using Stata 12 and R 3.1.0 software. The significance level was set at 0.05. Results: The mean age at diagnosis was $64.7{\pm}12.0$ years. The survival rate of patients with stomach cancer was 43.9% and 7% at the first and the fifth year after diagnosis, respectively. The results of log-rank test showed significant relationships between survival and age at diagnosis, education, disease stage, type of treatment, and degree of being underweight (P<0.05). Moreover, according to the results of Cox proportional hazards regression model, the variables of education, disease stage, and type of treatment were associated with patient survival (P<0.05). Conclusions: The survival rate of patients with stomach cancer is low and the prognosis is very poor. Given the poor prognosis of the patients, it is critical to find ways for early diagnosis and facilitating timely access to effective treatment methods.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.111-120
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• 2016

In usual, the discontinuous variance function was estimated nonparametrically using a kernel type estimator with data sets split by an estimated location of the change point. Kang et al. (2000) proposed the Gasser-$M{\ddot{u}}ller$ type kernel estimator of the discontinuous regression function using the adjusted observations of response variable by the estimated jump size of the change point in $M{\ddot{u}}ller$ (1992). The adjusted observations might be a random sample coming from a continuous regression function. In this paper, we estimate the variance function using the Nadaraya-Watson kernel type estimator using the adjusted squared residuals by the estimated location of the change point in the discontinuous variance function like Kang et al. (2000) did. The rate of convergence of integrated squared error of the proposed variance estimator is derived and numerical work demonstrates the improved performance of the method over the exist one with simulated examples.

• Journal of Periodontal and Implant Science
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• v.43 no.4
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• pp.177-182
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• 2013

Purpose: Diabetes and periodontal disease are two common diseases with high prevalence rates. Recent evidence has shown a bidirectional relationship between diabetes and periodontitis. The aim of this study was to investigate the effects of nonsurgical periodontal therapy on glycemic control in type 2 diabetes mellitus patients. Methods: Sixty subjects aged 35-45 years with blood sugar controlled by oral hypoglycaemic agents were randomly divided equally among 3 groups: group A (scaling, mouthwash, and brushing), group B (mouthwash and brushing), and group C (brushing only). Glycated haemoglobin (HbA1c), fasting blood sugar (FBS), probing pocket depth (PPD), gingival index (GI), plaque index (PI), and the relevant drug history were recorded at baseline and after 3 months of intervention. Comparison of the mean difference among the variables was performed by parametric and nonparametric tests, which were further evaluated using multiple regression analysis. Results: The mean differences between the PPD, FBS, HbA1c, GI, and PI in groups A and B were found to be statistically significant (P<0.001). Multiple regression analysis in group A showed that out of all the independent variables, GI and frequency of drug administration independently (b=0.3761 and b=0.598) showed a significantly greater impact on HbA1c ($R^2$=0.832, P<0.05). Conclusions: Nonsurgical periodontal therapy can effectively decrease HbA1c levels in type 2 diabetes mellitus patients on medication.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.707-716
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• 2006

When the regression function is discontinuous at a point, the variance function is usually discontinuous at the point. In this case, we had better propose a test for the existence of a discontinuity point with the regression function rather than the variance function. In this paper we consider that the variance function only has a discontinuity point. We propose a nonparametric test for the existence of a discontinuity point with the second moment function since the variance function and the second moment function have the same location and jump size of the discontinuity point. The proposed method is based on the asymptotic distribution of the estimated jump size.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.569-577
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• 2022

Simulation studies are often conducted when it is difficult to compare the performance of nonparametric estimators theoretically. Kim and Kim (2021) showed that more systematic and accurate comparisons can be made if you analyze the simulation results using a regression model,. This study is a complementary study on Kim and Kim (2021). In the variance-covariance matrix for the error term of the regression model, only heteroscedasticity was considered and covariance was ignored in the previous study. When covariance is considered together with the heteroscedasticity, the variance-covariance matrix becomes a block diagonal matrix. In this study, a method of estimating and using the block diagonal variance-covariance matrix for the analysis was presented. This allows you to find more pairs of estimators with significant performance differences while ensuring the nominal confidence level.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.607-618
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• 2019

A new and interesting task in statistics is to effectively analyze functional data that frequently comes from advances in modern science and technology in areas such as meteorology and biomedical sciences. Functional linear regression with scalar response is a popular functional data analysis technique and it is often a common problem to determine a functional association if a functional predictor variable affects the scalar response in the models. Recently, Kong et al. (Journal of Nonparametric Statistics, 28, 813-838, 2016) established classical testing methods for this based on functional principal component analysis (of the functional predictor), that is, the resulting eigenfunctions (as a basis). However, the eigenbasis functions are not generally suitable for regression purpose because they are only concerned with the variability of the functional predictor, not the functional association of interest in testing problems. Additionally, eigenfunctions are to be estimated from data so that estimation errors might be involved in the performance of testing procedures. To circumvent these issues, we propose a testing method based on fixed basis such as B-splines and show that it works well via simulations. It is also illustrated via simulated and real data examples that the proposed testing method provides more effective and intuitive results due to the localization properties of B-splines.

• Journal of Soil and Groundwater Environment
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• v.14 no.5
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• pp.41-50
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• 2009

Water levels in groundwater monitoring wells of Jeju Island were analyzed using parametric and non-parametric trend analyses. Number of used monitoring wells in the analysis are 94 among totally 106 monitoring wells and the monitoring period is greater than single year, from 2001 to 2009. For the trend analysis, both parametric (linear regression) and nonparametric (Mann-Kendall trend test and Sen's trend test) methods were adopted. Results of the linear regression analysis on daily basis indicated that about 58.5% of the monitoring wells showed a decreasing trend, and analysis using monthly median indicated that about 79.8% showed a decreasing trend. The Mann-Kendall trend test and Sen's trend test with monthly median values in confidence levels of 95% and 99% showed the same analysis results. In confidence level of 95%, 32% were decreased, 3% were increased and the remains showed no trend. However, in confidence level of 99%, 16% were decreased, 2% were increased and the remains showed no trend. The largest decline rates of water levels were detected mainly at the coast of the northwestern and southwestern parts, which is expected to closely related to the increased pumping in the urban area and tourist resort.