• Title/Summary/Keyword: Statistical regression analysis

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Multivariate statistical analysis of the comparative antioxidant activity of the total phenolics and tannins in the water and ethanol extracts of dried goji berry (Lycium chinense) fruits

  • Kim, Joo-Shin;Kimm, Haklin Alex
    • 한국식품과학회지
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    • 제51권3호
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    • pp.227-236
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    • 2019
  • Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.

A guideline for the statistical analysis of compositional data in immunology

  • Yoo, Jinkyung;Sun, Zequn;Greenacre, Michael;Ma, Qin;Chung, Dongjun;Kim, Young Min
    • Communications for Statistical Applications and Methods
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    • 제29권4호
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    • pp.453-469
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    • 2022
  • The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.

통계해석에 의한 G/T 4톤급 연안어선의 유효마력 추정 (Prediction of Effective Horsepower for G/T 4 ton Class Coast Fishing Boat Using Statistical Analysis)

  • 박충환;심상목;조효제
    • 한국해양공학회지
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    • 제23권6호
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    • pp.71-76
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    • 2009
  • This paper describes a statistical analysis method for predicting a coast fishing boat's effective horsepower. The EHP estimation method for small coast fishing boats was developed, based on a statistical regression analysis of model test results in a circulating water channel. The statistical regression formula of a fishing boat's effective horsepower is determined from the regression analysis of the resistance test results for 15 actual coast fishing boats. This method was applied to the effective horsepower prediction of a G/T 4 ton class coast fishing boat. From the estimation of the effective horsepower using this regression formula and the experimental model test of the G/T 4 ton class coast fishing boat, the estimation accuracy was verified under 10 percent of the design speed. However, the effective horsepower prediction method for coast fishing boats using the regression formula will be used at the initial design and hull-form development stage.

Outlier Identification in Regression Analysis using Projection Pursuit

  • Kim, Hyojung;Park, Chongsun
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.633-641
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    • 2000
  • In this paper, we propose a method to identify multiple outliers in regression analysis with only assumption of smoothness on the regression function. Our method uses single-linkage clustering algorithm and Projection Pursuit Regression (PPR). It was compared with existing methods using several simulated and real examples and turned out to be very useful in regression problem with the regression function which is far from linear.

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Classification Using Sliced Inverse Regression and Sliced Average Variance Estimation

  • Lee, Hakbae
    • Communications for Statistical Applications and Methods
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    • 제11권2호
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    • pp.275-285
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    • 2004
  • We explore classification analysis using graphical methods such as sliced inverse regression and sliced average variance estimation based on dimension reduction. Some useful information about classification analysis are obtained by sliced inverse regression and sliced average variance estimation through dimension reduction. Two examples are illustrated, and classification rates by sliced inverse regression and sliced average variance estimation are compared with those by discriminant analysis and logistic regression.

최근 3년간(2007~2009년) 여성건강간호학회지의 상관분석과 회귀분석 통계활용 논문 분석 (Analysis of the Correlation and Regression Analysis Studies from the Korean Journal of Women Health Nursing over the Past Three Years (2007~2009))

  • 이은주;이은희;김증임;강희선;오현이;전은미;천숙희
    • 여성건강간호학회지
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    • 제17권2호
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    • pp.187-194
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    • 2011
  • Purpose: This study investigated the statistical methods and the results had reported correlation/regression analysis in the studies of Korean Journal of Women Health Nursing (KJWHN). Methods: We reviewed 45 studies using correlation/regression analysis for the suitability of the statistical methods and the research purposes, the criteria for analysis of figures, tables and charts had published in the KJWHN from vol 13 (1) in 2007 to vol 15 (4) in 2009. Results: Forty three studies were fitted to their statistical methodology and their research purposes. Eleven studies considered the minimum sample size. Fourteen regression studies used multiple regression and 12 studies used forward method for variable entry. Only one study among the 17 regression studies accomplished scatter plots and residuals examination. Sixteen studies in correlation studies and six studies in regression studies showed some errors in either the title, variables, category of figures, tables and charts. In the regression study, all reported $R^2$ and ${\beta}$ values except one. Conclusion: It was found that there were still statistical errors or articulation errors in the statistical analysis. All reviewers need to be reviewed more closely for detecting errors not only during reviewing process of the manuscript but also periodic publication for the quality of this academic journal.

규제 순응도와 산업재해 발생 수준간의 관계 분석 - 로지스틱 회귀분석과 포아송 회귀분석을 중심으로 - (Analysis of the relationship between regulation compliance and occupational injuries - Focusing on logistic and poisson regression analysis -)

  • 이경용;김기식;윤영식
    • 대한안전경영과학회지
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    • 제15권2호
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    • pp.9-20
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    • 2013
  • OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.

멀티미디어와 통계 소프트웨어를 활용한 회귀분석 학습 시스템 (Learning system for Regression Analysis using Multimedia and Statistical Software)

  • 안기수;허문열
    • 응용통계연구
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    • 제11권2호
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    • pp.389-401
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    • 1998
  • 본 논문에서는 멀티미디어를 활용한 회귀분석 학습시스템 CybeRClass(Cyber Regression Class)를 소개하고자 한다. CybeRClass는 음성정보와 애니메이션 등을 활용하여 회귀분석에 대한 학습을 시켜주는 시스템이다. 이 시스템은 군집분석이나 판별분석 등의 다변량분석 학습이 가능하도록 설계되었다. 멀티미디어 기술을 위한 도구로는 Multimedia ToolBook을 사용하였으며, 통계계산과 통계그라픽을 위해서는 객체지향 통계 언어인 Xlisp-Stat을 사용하였다.

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상관분석과 회귀분석을 이용한 논문의 통계활용 분석 (Analysis on Reports of Statistical Testings for Correlation and Regression)

  • 조동숙;정재원;김증임;안숙희;박소미;박혜숙
    • 여성건강간호학회지
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    • 제14권3호
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    • pp.213-221
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    • 2008
  • Purpose: This study aimed to examine the accuracy and adequacy of research papers reporting statistical testings for correlation and regression. Method: Original research articles utilized correlation and regression analysis were reviewed from the Korean Journal of Women Health Nursing published from the year 2004 to 2006. Thirty-six papers were evaluated in accordance with formatted criteria in respect to an inclusiveness of research title, accuracy of statistical methods and presentation styles, and errors in reporting statistical outcomes. Result: Thirty articles (83.3%) utilized Pearson's correlational analysis, and ten articles did regression analysis. Lack of accurate understanding and interpretation of the statistical method was a main fault. Basic assumptions and diagnostic testings for each statistical method were not performed or described in most of the studies. Some points like consistency of research questions with statistical methods and criteria for sample size were still left out in part. Details of the presentation in the reporting of outcomes were not complied with the guidelines, which need careful concerns of the writers. Errors in English of result tables were found in more than one third of the tables. Conclusion: The outcome would be reflected in the submission guidelines for future writers. To reach the level comparable with internationally recognized nursing journals, concrete knowledge to apply statistical methods should be ensured in the processes of submission, reviews, and editing.

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Optimal Designs for Multivariate Nonparametric Kernel Regression with Binary Data

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • 제2권2호
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    • pp.243-248
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    • 1995
  • The problem of optimal design for a nonparametric regression with binary data is considered. The aim of the statistical analysis is the estimation of a quantal response surface in two dimensions. Bias, variance and IMSE of kernel estimates are derived. The optimal design density with respect to asymptotic IMSE is constructed.

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