OBJECTIVETo explore several numerical methods of ordinal variable in one-way ordinal contingency table and their interrelationship, and to compare corresponding statistical analysis methods such as Ridit analysis and rank sum test.

METHODSFormula deduction was based on five simplified grading approaches including rank_r(i), ridit_r(i), ridit_r(ci), ridit_r(mi), and table scores. Practical data set was verified by SAS8.2 in clinical practice (to test the effect of Shiwei solution in treatment for chronic tracheitis).

RESULTSBecause of the linear relationship of rank_r(i) = N ridit_r(i) + 1/2 = N ridit_r(ci) = (N + 1) ridit_r(mi), the exact chi2 values in Ridit analysis based on ridit_r(i), ridit_r(ci), and ridit_r(mi), were completely the same, and they were equivalent to the Kruskal-Wallis H test. Traditional Ridit analysis was based on ridit_r(i), and its corresponding chi2 value calculated with an approximate variance (1/12) was conservative. The exact chi2 test of Ridit analysis should be used when comparing multiple groups in the clinical researches because of its special merits such as distribution of mean ridit value on (0,1) and clear graph expression. The exact chi2 test of Ridit analysis can be output directly by proc freq of SAS8.2 with ridit and modridit option (SCORES =).

CONCLUSIONThe exact chi2 test of Ridit analysis is equivalent to the Kruskal-Wallis H test, and should be used when comparing multiple groups in the clinical researches.

With fast development and wide applications of next generation sequencing (NGS), genomic sequence information is within reach to various research fields. Three benchtop NGS instruments are now available. The 454 GS Junior (Roche), Ion PGM (Life Technologies) and MiSeq (Illumina) are laser-printer sized and offer modest set-up and running costs. By reviewing 2 studies that compared the performance of these instruments, the major characteristics of each benchtop platforms are compared to enable direct comparisons. The 454 GS Junior generated the longest reads and most contiguous assemblies but had the lowest throughput. The Ion Torrent PGM had the highest throughput and fastest run time. The MiSeq had the highest throughput per run and lowest error rates. The Ion Torrent PGM and 454 GS Junior both produced homopolymer-associated indel errors. Although all the platforms allow multiplexing of samples, details of experimental design, library preparation and data analysis may constrain the options. The features of the platforms provide opportunities both to conduct groundbreaking studies and to waste money. Thus, careful considerations should be made before purchasing or using any of them.
Research Design ; Running ; Statistics as Topic

The purpose of this study was to examine the effects of 6-wk low intensity exercise program on fatigue, perceived health state, exercise-related affect, perceived benefits, and exercise self-efficacy for female college student's. The subjects of the study consisted of thirty-four female college students. The research subjects were assigned to experimental and control group. The experimental group participated in 13-17 and 30-60 minute sesseions of exercise program over 6 weeks. Data analysis was done by t-test with SAS program. The results of this study are as follows. 1) The first hypothesis, "The fatigue of experimental group will be lower than control group", was supported. 2) The second hypothesis, "The perceived health state of experimental group will be higher than control group", was not supported. 3) The third hypothesis, "The exercise-related affect of experimental group will be higher than control group", was not supported. 4) The fourth hypothesis, "The benefits of exercise of experimental group will be higher than control group", was not supported. 5) The fifth hypothesis, "The self-efficacy for exercise of experimental group will be higher than control group", was supported.
Fatigue* ; Female* ; Humans ; Research Subjects ; Statistics as Topic

PURPOSE: The purpose of this study is to test the reliability of the clinical performance examination (CPX) using Generalizability theory (G-theory). Through G-theory, the effects of not only students and tasks but also the school will be analyzed as primary sources of error, which can affect the interpretation of the reliability of the CPX. METHODS: One thousand three hundred nineteen students from 16 medical schools that participated in the Seoul-Gyeonggi CPX Consortium 2008 were enrolled. In our research design, we suppose that student is nested within school and crossed with task. Data analysis was conducted with urGenova. RESULTS: According to our analysis, the percentage of error variance was 6.2% for school, 14.9% for student nested within school, 14.4% for task, and 3% for interaction between school and task. An effect of school on students was observed, but the interaction between task and school was insignificant. When student is nested within school, the universe score decreased and the g-coefficient was less than the g-coefficient of the p x t (p: studentm, t: task) design. CONCLUSION: The results show that generalizability theory is useful in detecting various error components in the CPX. Using the generalizability theory to improve the technical quality of performance assessments provides us with greater information compared with traditional test theories.
Humans ; Research Design ; Schools, Medical ; Statistics as Topic

PURPOSE: This study aimed to identify research trends in the Journal of Korean Academy of Nursing Administration from 2013 to 2015. METHODS: For this study, 171 articles were analyzed. Research designs, participants, research settings, sampling, and data analyses methods were reviewed using established analysis criteria. Keyword centrality and clusters were generated by keyword network analysis. RESULTS: Most of studies used quantitative methods (82.5%), and sampling mainly focused on nurses (68.8%). The most commonly used data analyses methods were t-test, ANOVA, correlation, and regression. The most central keywords were turnover and empowerment. Network analysis generated four network groups: 1) burnout; 2) turnover; 3) happiness; and 4) nursing professionalism. CONCLUSION: The results of this study identify current trends and interests in Korean nursing administration research. The findings from this study suggest that future studies include a variety of research methods and maintain appropriate research ethics.
Ethics, Research ; Happiness ; Nursing Administration Research ; Nursing Research ; Nursing* ; Power (Psychology) ; Professionalism ; Research Design ; Statistics as Topic

PURPOSE: The purpose of this study was to analyze the published articles in the Journal of Korean Academy of Adult Nursing from 2004 through 2006. METHODS: Two hundreds and ten articles were analyzed focusing on research methodology and key words using descriptive statistics. RESULTS: The proportion of quantitative research was 88.1%, while the proportion of qualitative research was 5.2%. The majority of the qualitative research design was survey(67.1%). Seventy-four percent of the research had verbal consent and 8% had written consent from the participants. Eight percent of the research provided conceptual framework. The prevailing data collection settings were hospitals(50.5%) and community(37.1%). For the data analysis, 95% used parametric analysis methods; descriptive statistics(26.2%), chi-square test(18.3%), t-test(18%) and ANOVA(17.4%). Key words were categorized into four nursing domain: human, health, nursing, and environment. The most frequently used domain was health. CONCLUSION: The number of the published articles in the Journal of Korean Academy of Adult Nursing has been increased and quality has been improved compared with the articles published before the 2000 year. Varied research methodology and data analysis methods were utilized.
Adult ; Data Collection ; Humans ; Nursing Research ; Qualitative Research ; Research Design ; Statistics as Topic

Qualitative research is very important in educational research as it addresses the “how” and “why” research questions and enables deeper understanding of experiences, phenomena and context. Qualitative research allows you to ask questions that cannot be easily put into numbers to understand human experience. Getting at the everyday realities of some social phenomenon and studying important questions as they are really practiced helps extend knowledge and understanding. To do so, you need to understand the philosophical stance of qualitative research and work from this to develop the research question, study design, data collection methods and data analysis. In this article, I provide an overview of the assumptions underlying qualitative research and the role of the researcher in the qualitative process. I then go on to discuss the type of research objectives which are common in qualitative research, then introduce the main qualitative designs, data collection tools, and finally the basics of qualitative analysis. I introduce the criteria by which you can judge the quality of qualitative research. Many classic references are cited in this article, and I urge you to seek out some of these further reading to inform your qualitative research program.
Data Collection ; Education, Medical* ; Humans ; Methods ; Qualitative Research ; Statistics as Topic

WHY: Calculating the sample size is essential to reduce the cost of a study and to prove the hypothesis effectively. HOW: Referring to pilot studies and previous research studies, we can choose a proper hypothesis and simplify the studies by using a website or Microsoft Excel sheet that contains formulas for calculating sample size in the beginning stage of the study. MORE: There are numerous formulas for calculating the sample size for complicated statistics and studies, but most studies can use basic calculating methods for sample size calculation.
Chi-Square Distribution ; *Research Design ; *Sample Size ; Statistics as Topic/*methods

Confounding effect is a critical issue in clinical research of otolaryngology because it can distort the research's conclusion. In this review, we introduce the definition of confounding effect, the methods of verifying and controlling the effect. Confounding effect can be prevented by research's design, and adjusted by data analysis. Clinicians would be aware and cautious about confounding effect in their research. They would be able to set up a research's design in which appropriate methods have been applied to prevent this effect.They would know how to adjust confounding effect after data collection. It is important to remember that sometimes it is impossible to eliminate confounding effect completely, and statistical method is not a master key. Solid research knowledge and critical thinking of our brain are the most important in controlling confounding effect.
Bias ; Humans ; Otolaryngology ; Regression Analysis ; Research Design ; Statistics as Topic

PURPOSE: This study was to explore the process of belongingness experienced during the apprentice course for advanced practice nurses. METHODS: Data were collected through in-depth interviews with 15 people, who attended the apprentice course for advanced practice nurse, from three schools in Seoul from Jan. 19 until Feb. 25, 2010. The constant comparative method was adapted for data analysis. RESULTS: The core category of this study was the 'learning-connected process' and this process was categorized into three stages. These stages were: going along with the atmosphere, exchanging, and integrating. During the course, the 'uncomfortable participation' as the central idea meant a sense of responsibility and a tension about practice learning of the participant and was influenced by the quality of interaction and the distinct instruction of learning contents. Belongingness was characterized by the Joyful and happy participation which linked to the motivation of new learning opportunities. CONCLUSION: The findings indicate that there is a process to belongingness and a close relationship between belongingness and learning. Further studies would suggest exploring the components of belongingness, a concept analysis and incorporating the belongingness scale with other qualitative research on this topic.
Atmosphere ; Education, Nursing ; Humans ; Learning ; Motivation ; Qualitative Research ; Statistics as Topic