• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1249-1263
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• 2009

The power function in sample size determination has to be characterized by an appropriate statistical test for the hypothesis of interest. Nonparametric tests are suitable in the analysis of ordinal data or frequency data with ordered categories which appear frequently in the biomedical research literature. In this paper, we study sample size calculation methods for the Wilcoxon-Mann-Whitney test for one- and two-dimensional ordinal outcomes. While the sample size formula for the univariate outcome which is based on the variances of the test statistic under both null and alternative hypothesis perform well, this formula requires additional information on probability estimates that appear in the variance of the test statistic under alternative hypothesis, and the values of these probabilities are generally unknown. We study the advantages and disadvantages of different sample size formulas with simulations. Sample sizes are calculated for the two-dimensional ordinal outcomes of efficacy and safety, for which bivariate Wilcoxon-Mann-Whitney test is appropriate than the multivariate parametric test.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.209-218
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• 2012

The method of generalized estimating equations (GEEs) provides consistent esti- mates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). In this paper we compare the estimators of parameters in GEE approach. We consider two aspects: coverage probabilites and efficiency. We adopted to ordinal responses th results derived from binary outcomes.

• Journal of Korean Academy of Nursing
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• v.44 no.5
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• pp.542-551
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• 2014

Purpose: This study was done to examine the incidence of oral mucositis in hematopoietic stem cell transplantation patients and to identify factors influencing oral mucositis and patient outcomes according to severity. Methods: In this retrospective study, data were collected from electronic medical records of 222 patients who had received hematopoietic stem cell transplantation. Oral mucositis was evaluated using WHO's assessment scale. Data were analyzed using Chi-square test, Fisher exact test, Spearman's correlation, Ordinal logistic regression, ANOVA and Kruskal-Wallis test. Results: A total of 69.8% of the patients evaluated developed oral mucositis (grade II and over). As a results of ordinal regression, factors influencing oral mucositis severity were found to be diagnosis, type of transplantation, oxygen inhalation and the number of antiemetics administration before transplantation. The severity of oral mucositis was found to increase the days of hospitalization, days of TPN administration, days of using antibiotics and the number and dosage of analgesics. Conclusion: The results would help predict severity of oral mucositis in hematopoietic stem cell transplantation patients and suggest that provision of appropriate nursing assessment and oral care would improve patient outcomes.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.205-216
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• 2019

Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Health Policy and Management
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• v.30 no.3
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• pp.399-408
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• 2020

Background: The purpose of this study was to examine the impact of the regional characteristics on the accessibility of emergency care and the impact of emergency medical accessibility on the patients' prognosis and the emergency medical expenditure. Methods: This study used the 13th beta version 1.6 annual data of Korea Health Panel and the statistics from the Korean Statistical Information Service. The sample included 8,119 patients who visited the emergency centers between year 2013 and 2017. The arrival time, which indicated medical access, was used as dependent variable for multi-level analysis. For ordinal logistic regression and multiple regression, the arrival time was used as independent variable while patients' prognosis and emergency medical expenditure were used as dependent variables. Results: The results for the multi-level analysis in both the individual and regional variables showed that as the number of emergency medical institutions per 100 km² area increased, the time required to reach emergency centers significantly decreased. Ordinal logistic regression and multiple regression results showed that as the arrival time increased, the patients' prognosis significantly worsened and the emergency medical expenses significantly increased. Conclusion: In conclusion, the access to emergency care was affected by regional characteristics and affected patient outcomes and emergency medical expenditure.

• Journal of Korea Technology Innovation Society
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• v.11 no.3
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• pp.376-399
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• 2008

Science and technology (S&T) is one of the most important elements in a nation's competitiveness. In an effort to strengthen their national competitiveness, all countries are focusing on upgrading the level of eir S&T. With these factors in mind, Korea has increased its support of national research and development (R&D). In recent years, this added support has resulted in an increased interest in the effectiveness of R&D. We have made continuous efforts to enhance the accountability and effectiveness of R&D by strengthening performance evaluation and considering R&D evaluation results during the budget review (appropriation) process. In order to change to a performance based system, we need to develop objective and scientific indicators to measure and evaluate the quality of the research performance of R&D programs. One of the primary research outcomes is publications. The impact factor of publications is widely used to evaluate overall journal quality and the quality of the papers published therein. However, the use of impact factors has been criticised because they can vary greatly when works from different subject areas are compared. In order to overcome this limitation, we have developed three kinds of qualitative indicators, which are functions of the impact factor. Two of these qualitative indicators, Modified Rank Normalized Impact Factor and Ordinal Rank Normalized Impact Factor, are based on order statistics (rank) for all journals from a specific specialty. The third qualitative indicator, Relative Field Impact Factor, uses the average impact factor of all journals within a subject category. We also suggest a quantitative indicator, Percentage of Contribution. In this study, we suggest 4 indicators and use them to evaluate the performance of outcomes from three R&D programs supported by the Ministry of Education, Science & Technology. We also perform a simulation study to verify the effectiveness of the proposed indicators. It can be shown that the proposed Ordinal Rank Normalized Impact Factor is the most reliable and effective indicator for comparing research performance across subject categories. However, we recommend using previous indicators in combination with the proposed indicators in this study for the research evaluation of R&D programs.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.341-353
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• 2009

We consider sample-size determination problem motivated by comparative clinical trials where patient outcomes are characterized by a bivariate outcome of efficacy and safety. Thall and Cheng (1999) presented a sample size methodology for the case of bivariate binary outcomes. We propose a bivariate Wilcoxon-Mann-Whitney(WMW) statistics for sample-size determination for binary outcomes, and this nonparametric method can be equally used to determine sample sizes of ordinal outcomes. The two methods of sample size determination rely on the same testing strategy for the target parameters but differs in the test statistics, an asymptotic bivariate normal statistic of the transformed proportions in Thall and Cheng (1999) and nonparametric bivariate WMW statistic in the other method. Sample sizes are calculated for the two experimental oncology trials, described in Thall and Cheng (1999), and for the first trial example the sample sizes of a bivariate WMW statistic are smaller than those of Thall and Cheng (1999), while for the second trial example the reverse is true.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.421-439
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• 2022

Phase I dose-finding trials are essential in drug development. By finding the maximum tolerated dose (MTD) of a new drug or treatment, a Phase I trial establishes the recommended doses for later-phase testing. The primary toxicity endpoint of interest is often a binary variable, which describes an event of a patient who experiences dose-limiting toxicity. However, there is a growing interest in dose-finding studies regarding non-binary outcomes, defined by either the weighted sum of rates of various toxicity grades or a continuous outcome. Although several novel methods have been proposed in the literature, accessible software is still lacking to implement these methods. This study introduces a newly developed R package, UnifiedDoseFinding, which implements three phase I dose-finding methods with non-binary outcomes (Quasi- and Robust Quasi-CRM designs by Yuan et al. (2007) and Pan et al. (2014), gBOIN design by Mu et al. (2019), and by a method by Ivanova and Kim (2009)). For each of the methods, UnifiedDoseFinding provides corresponding functions that begin with next that determines the dose for the next cohort of patients, select, which selects the MTD defined by the non-binary toxicity endpoint when the trial is completed, and get oc, which obtains the operating characteristics. Three real examples are provided to help practitioners use these methods. The R package UnifiedDoseFinding, which is accessible in R CRAN, provides a user-friendly tool to facilitate the implementation of innovative dose-finding studies with nonbinary outcomes.

• Korean Journal of Clinical Pharmacy
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• v.26 no.1
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• pp.33-39
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• 2016

Background: Elements of informed consent including capacity, disclosure, understanding, voluntariness, and permission of the participant, are all crucial for clinical trials to be legally and ethically valid. During the informed consent process, the patient information leaflet is an important information source which prospective research subjects can utilize in their decision-making. In the adequate provision of information, KGCP guideline necessitate 20 specific items, as well as the use language that individuals can understand. This study measures the vocabulary level of patient information leaflets in an effort to provide an objective evaluation on the readability of such material. Methods: The word difficulty of 13 leaflets was quantitatively evaluated using Kim kwang Hae's vocabulary grading framework, which was compared to the difficulty level of words found in the $6^{th}$ grade Korean textbook. The quantitative outcomes were statistically analyzed using chi-squared tests and linear by linear association for ordinal data. Results: There was a statistically significant difference between the vocabulary level and frequency of words in leaflets and the 6th Korean textbook. The leaflets were on average 260 sentences and about roughly 15 pages long, including lay language (easier or equal to language used in primary school) of around 12% less; technical language of around 4.5% more. As the vocabulary grades increase, there was a distinct difference in vocabulary level between Korean textbook and each information leaflet (p < 0.001). Conclusion: Patient information leaflets may fail to provide appropriate information for self-determination by clinical trial subject through the difficulty level of its wording. Improvements in the degree of patients' understanding and appropriate use of information leaflets are collaboratively equipped to strengthen patient's autonomy and therefore guaranteeing participant's rights.