• Title/Summary/Keyword: test statistics

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The Effect Measures for Diagnostic Test: A Graph Approach (진단검사에서 측도들의 효과적인 표현: 그래프를 활용한 방법)

  • Cho, Tae-Kyoung;Son, Chang-Kyoon
    • The Korean Journal of Applied Statistics
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    • v.26 no.1
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    • pp.15-22
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    • 2013
  • In clinical study or epidemic research, the $2{\times}2$ frequency table is useful to present a summary statistic The values of four cells in $2{\times}2$ table use to calculate the effect measures such as risk ratio, relative ris ratio or odds ratio. In this paper, we suggest that the improved visualization method using a radar diagram supported by MS-office Excel from the $2{\times}2$ frequency table is able to understand and draw easily betweendiagnosti measures such as sensitivity, specificity, predictivity, and likelihood ratio. We use some numerical example in order to show the usage of the proposed method.

Comparison of covariance thresholding methods in gene set analysis

  • Park, Sora;Kim, Kipoong;Sun, Hokeun
    • Communications for Statistical Applications and Methods
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    • v.29 no.5
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    • pp.591-601
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    • 2022
  • In gene set analysis with microarray expression data, a group of genes such as a gene regulatory pathway and a signaling pathway is often tested if there exists either differentially expressed (DE) or differentially co-expressed (DC) genes between two biological conditions. Recently, a statistical test based on covariance estimation have been proposed in order to identify DC genes. In particular, covariance regularization by hard thresholding indeed improved the power of the test when the proportion of DC genes within a biological pathway is relatively small. In this article, we compare covariance thresholding methods using four different regularization penalties such as lasso, hard, smoothly clipped absolute deviation (SCAD), and minimax concave plus (MCP) penalties. In our extensive simulation studies, we found that both SCAD and MCP thresholding methods can outperform the hard thresholding method when the proportion of DC genes is extremely small and the number of genes in a biological pathway is much greater than a sample size. We also applied four thresholding methods to 3 different microarray gene expression data sets related with mutant p53 transcriptional activity, and epithelium and stroma breast cancer to compare genetic pathways identified by each method.

Note on the Equality of Variances in Two Sample t-Test (두 집단 평균 차이 검정에서 분산의 동질성에 관한 소고)

  • Kim, Sang-Cheol;Lim, Jo-Han
    • Communications for Statistical Applications and Methods
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    • v.17 no.1
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    • pp.79-88
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    • 2010
  • Introductory statistic class proposes two tests for the equality of two population means according to the homogeneity of their variances. However, in practice, the variances are also unknown and practitioners often test their homogeneity before they do two sample t-test. This is also true in many popular statistical packages such as SAS and SPSS. In this paper, we study the type I error of this two stage procedure and propose a procedure to control it at a given significance level.

A study on alternatives to the permutation test in gene-set analysis (유전자집합분석에서 순열검정의 대안)

  • Lee, Sunho
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.241-251
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    • 2018
  • The analysis of gene sets in microarray has advantages in interpreting biological functions and increasing statistical powers. Many statistical methods have been proposed for detecting significant gene sets that show relations between genes and phenotypes, but there is no consensus about which is the best to perform gene sets analysis and permutation based tests are considered as standard tools. When many gene sets are tested simultaneously, a large number of random permutations are needed for multiple testing with a high computational cost. In this paper, several parametric approximations are considered as alternatives of the permutation distribution and the moment based gene set test has shown the best performance for providing p-values of the permutation test closely and quickly on a general framework.

Politics behavior data analysis using the adaptive Neyman test (적응-네이만-검정을 이용한 미국 정치 행동분석)

  • Kim, Myo Jeong;Hahn, Kyu S.;Lim, Johan;Lee, Kyeong Eun
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.2
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    • pp.289-301
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    • 2013
  • We analyze respondents' reaction to Obama's advertisement, titled 'Fix the Economy'. These respondents are divided into three groups of democratic party, republican party and independent group. By manipulating the skin complexion of the Obama photo, participants were either exposed to the dark or light version of the Obama photograph. In order to obtain decorrelated stationary data, we have applied the discrete Fourier transform to each curve and then we have applied Fan (1998)'s adaptive Neyman test to the discrete Fourier transformed data. As a result, a significant difference is found out only in the independent group.

Efficient Edge Detection in Noisy Images using Robust Rank-Order Test (잡음영상에서 로버스트 순위-순서 검정을 이용한 효과적인 에지검출)

  • Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.20 no.1
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    • pp.147-157
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    • 2007
  • Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.

Power Comparison between Methods of Empirical Process and a Kernel Density Estimator for the Test of Distribution Change (분포변화 검정에서 경험확률과정과 커널밀도함수추정량의 검정력 비교)

  • Na, Seong-Ryong;Park, Hyeon-Ah
    • Communications for Statistical Applications and Methods
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    • v.18 no.2
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    • pp.245-255
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    • 2011
  • There are two nonparametric methods that use empirical distribution functions and probability density estimators for the test of the distribution change of data. In this paper we investigate the two methods precisely and summarize the results of previous research. We assume several probability models to make a simulation study of the change point analysis and to examine the finite sample behavior of the two methods. Empirical powers are compared to verify which is better for each model.

Influencing Factors of Intention of Undergoing Pap Testing among Unmarried Nurses (미혼 간호사의 Pap 검진의도 영향요인)

  • Kim, Hae Won
    • Women's Health Nursing
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    • v.20 no.3
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    • pp.225-233
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    • 2014
  • Purpose: This study was to assess the intention of undergoing Pap testing and to identify influencing factors of HPV knowledge and their attitude related to Pap test by sexual activity among unmarried nurses. Methods: A cross sectional survey design was employed, utilizing a self-administered questionnaire amongst 343 unmarried nurses. Descriptive statistics was utilized to analyze data and inferential statistics used an independent-t test and ${\chi}^2$ test for the differences in measurement variables, and odds ratios for factors on intention of Pap testing by sexual activity. Results: Nurses not sexually active were significantly higher in intention of Pap testing (${\chi}^2$=40.15, p<.001) and influencing factors of HPV knowledge (t=3.93, p=.048) than did nurses who were sexually active. Factors influencing intention were regularity of the breast self-examination (Adjusted Odds Ratio [AOR]=4.20, 95% Confidence Interval [CI]=1.93~9.17), HPV knowledge (AOR=2.49, 95% CI=1.36~4.56), and attitudes toward the Pap test(AOR=2.33, 95% CI=1.25~4.34) amongst nurses who never had sexual experience. Conclusion: It is necessary to minimize negative attitudes of Pap testing and to increase HPV knowledge in order to improve intention of Pap testing for women who were not sexually active. More focus would be given to sexually active women to get Pap tested as a preventive measure for cervical cancer.

Prediction of the interest spread using VAR model (벡터자기회귀모형에 의한 금리스프레드의 예측)

  • Kim, Junhong;Jin, Dalae;Lee, Jisun;Kim, Suji;Son, Young Sook
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1093-1102
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    • 2012
  • In this paper, we predicted the interest spread using the VAR (vector autoregressive) model. Variables used in the VAR model were selected among 56 domestic and foreign macroeconomic time series through crosscorrelation and Granger causality test. The performance of the VAR model was compared with the univariate time series model, AR (autoregressive) model, in view of MAPE (mean absolute percentage error) and RMSE (root mean square error) of forecasts for the last twelve months.

Criterion of Test Statistics for Validation in Credit Rating Model (신용평가모형에서 타당성검증 통계량들의 판단기준)

  • Park, Yong-Seok;Hong, Chong-Sun;Lim, Han-Seung
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.239-347
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    • 2009
  • This paper presents Kolmogorov-Smirnov, mean difference, AUROC and AR, four well known statistics that have been widely used for evaluating the discriminatory power of credit rating models. Criteria for these statistics are determined by the value of mean difference under the assumption of normality and equal standard deviation. Alternative criteria are proposed through the simulations according to various sample sizes, type II error rates, and the ratio of bads, also we suggest the meaning of statistic on the basis of discriminatory power. Finally we make a comparative study of the currently used guidelines and simulated results.