Isolation-with-migration (IM) models have become popular for explaining population divergence in the presence of migrations. Bayesian methods are commonly used to estimate IM models, but they are limited to small data analysis or simple model inference. Recently three methods, IMa3, MIST, and AIM, resolved these limitations. Here, we describe the major problems addressed by these three software and compare differences among their inference methods, despite their use of the same standard likelihood function.
Bayes Theorem ; Gene Flow ; Likelihood Functions ; Phylogeny ; Statistics as Topic

No abstract available.
Data Accuracy ; Data Interpretation, Statistical ; Statistics as Topic ; Biomedical Research ; Analysis of Variance

In this article we introduce modern statistical machine learning and bioinformatics approaches that have been used in learning statistical relationships from big data in medicine and behavioral science that typically include clinical, genomic (and proteomic) and environmental variables. Every year, data collected from biomedical and behavioral science is getting larger and more complicated. Thus, in medicine, we also need to be aware of this trend and understand the statistical tools that are available to analyze these datasets. Many statistical analyses that are aimed to analyze such big datasets have been introduced recently. However, given many different types of clinical, genomic, and environmental data, it is rather uncommon to see statistical methods that combine knowledge resulting from those different data types. To this extent, we will introduce big data in terms of clinical data, single nucleotide polymorphism and gene expression studies and their interactions with environment. In this article, we will introduce the concept of well-known regression analyses such as linear and logistic regressions that has been widely used in clinical data analyses and modern statistical models such as Bayesian networks that has been introduced to analyze more complicated data. Also we will discuss how to represent the interaction among clinical, genomic, and environmental data in using modern statistical models. We conclude this article with a promising modern statistical method called Bayesian networks that is suitable in analyzing big data sets that consists with different type of large data from clinical, genomic, and environmental data. Such statistical model form big data will provide us with more comprehensive understanding of human physiology and disease.
Bayes Theorem ; Behavioral Sciences ; Computational Biology ; Data Interpretation, Statistical ; Dataset ; Gene Expression ; Humans ; Learning ; Logistic Models ; Machine Learning* ; Models, Statistical ; Physiology ; Polymorphism, Single Nucleotide ; Statistics as Topic* ; Systems Biology

The current existing literature offers little guidance on how to decide which method to use to analyze one-channel microarray measurements when dealing with large, grouped samples. Most previous methods have focused on two-channel data;therefore they can not be easily applied to one-channel microarray data. Thus, a more reliable method is required to determine an appropriate combination of individual basic processing steps for a given dataset in order to improve the validity of onechannel expression data analysis. We address key issues in evaluating the effectiveness of basic statistical processing steps of microarray data that can affect the final outcome of gene expression analysis without focusingon the intrinsic data underlying biological interpretation.
Analysis of Variance ; Dataset ; Gene Expression ; Statistics as Topic

PURPOSE: We wanted to analyze the citation trend and to find a way to improve the impact factor (IF) of the Journal of the Korean Radiological Society (JKRS). MATERIALS AND METHODS: The number of articles and references, the total citations and self-citations, the IF and the IF excluding self-citations (ZIF) were described by an analysis of Korean Medical Citation Index (KoMCI) during 2000-2005. The total and self citations of the JKRS were compared to that of the Top 5 journals. RESULTS: There was a 57% decrease of papers for 6 years. The Korean references/paper ranged from 0.98-0.85. The number of total citations received steadily decreased from 394 in 2000 to 180 in 2005. The IF (ZIF) of the JKRS has been gradually lowered from 0.142 (0.049) in 2000 to 0.063 (0.059) in 2005. Although the total citations that cited all papers published/the annual number of papers was 55% of that of the top 5 journals, the total citations citing papers published within the recent two years was only 24% of that of the top 5 journals. CONCLUSION: The citation status of the JKRS hassteadily decreased for the recent 6 years, and the IF of the JKRS was very low among all the Korean medical journals. To improve the IF, active advertising for the journal members of the importance of the IF is needed to encourage citing JKRS papers that have been published within the recent two years.
Statistics as Topic

No abstract available.
Statistics as Topic*

Tissue array consists of a slide containing hundreds or thousands of cases, making this method useful for rapid analysis of molecular markers in a large number of cases. The method significantly facilitates and accelerates the clinicopathologic analysis of cancer. To maximize the efficacy of the tissue array method in pathologic study, the pros and cons of this method should be understood. In this review, the history and a detailed method of tissue array production is described, emphasizing the advantage of the large core size (2.0 mm). Some methological points, including slide storage, microtoming, core size, reliability, and data analysis, are discussed.
Statistics as Topic

To guarantee the inter-reviewer reliability is very important in evaluating the quality of large number of clinical research papers by multiple reviewers. We cannot find reports on statistical methods for evaluating reliability for multiple raters in clinical research field. The purpose of this paper is to introduce the statistical methods focused on kappa statistic and five kinds of loglinear models for, which can be applied when evaluating the reliability of multiple raters. We have applied these methods to the result of a project, in which seven reviewers have evaluated the quality of 33 papers with regard to four aspects of paper contents including study hypothesis, study design, study population, study method, data analysis and interpretation. Among the five loglinear models including Symmetry model, Conditional symmetry model, Quasi-symmetry model, Independence model, and Quasi-independence model, Quasi-symmetry model shows the best model of fitting. And the level of reliability among seven reviewers revealed to be acceptable as meaningful.
Statistics as Topic

No abstract available.
Statistics as Topic*

PURPOSE: To measure the cement mantle thickness that developed from a rotation of the femoral stem in virtual space made by the broach. MATERIALS AND METHODS: The C stem and Versys stem of the subjects enrolled in this study were examined. A C250/400VZ(Steinbichler Co. Germany) and S/W: Geomagic & CATIA V5 was used to examine the three-dimensional configurations. The axial images were acquired after neutral placement of the femoral stem, horizontal rotation, coronal tilting, and a combination of both. The thickness was measured from the distance between the outer surface of the femoral stem and the closest vertex in the outer contour of the broach in cross-sectional images. RESULTS: The distance was <1 mm at the horizontal rotation of 3 degrees in the C stem, and at 5 degrees in the Versys stem. The distance was <1 mm at varus of 0.25 degrees in the C stem, and touched at 0.8 degrees. In the case of the Versys stem, the femoral stem touched at a varus of 1 degree. A combination of both horizontal and pivot rotation made the distance <1 mm at rotation of all angles. CONCLUSION: It might be necessary to develop a new instrument for the accurate insertion of the femoral stem along the broached space or to modify the stem design to stand against the change in the femoral stem position in the broached space.
Statistics as Topic*