• Title/Summary/Keyword: Analysis of Covariance(ANCOVA)

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Nonparametric Method using Placement in an Analysis of a Covariance Model

  • Hwang, Dong-Min;Kim, Dong-Jae
    • Communications for Statistical Applications and Methods
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    • v.19 no.5
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    • pp.721-729
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    • 2012
  • Various methods control the influence of a covariate on a response variable. These methods are analysis of covariance(ANCOVA), RANK ANCOVA, ANOVA of (covariate-adjusted) residuals, and Kruskal-Wallis tests on residuals. Covariate-adjusted residuals are obtained from the overall regression line fit to the entire data set that ignore the treatment levels or factors. It is demonstrated that the methods on covariate-adjusted residuals are only appropriate when the regression lines are parallel and covariate means are equal for all treatments. In this paper, we proposed the new nonparametric method on the ANCOVA model, as applying joint placement in a one-way layout on residuals as described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed procedure with those of the previous procedure.

DD-Plot for ANCOVA Models (ANCOVA 모형을 위한 DD-plot)

  • Jang, Dae-Heung
    • The Korean Journal of Applied Statistics
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    • v.27 no.2
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    • pp.227-237
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    • 2014
  • We use the regression model with the indicator variables in the case that we use qualitative variables as some predictor variables in regression analysis. We use the ANCOVA(Analysis of Covariance) model when comparing the response variable among groups while statistically controlling for variation in the response variable caused by a variation in the covariate. DD-plot can be used as a graphical exploratory data analysis tool before the confirmatory data analysis. With the DD-plot, we can discriminate the difference of groups in the regression model with the indicator variables or the ANCOVA model at a glance. Making DD-plot does not demand the statistical model assumption about error terms in regression model. Several examples show the usefulness of DD-plots as a graphical exploratory data analysis tool for the regression analysis.

Understanding Security Knowledge and National Culture: A Comparative Investigation between Korea and the U.S

  • Kwak, Dong-Heon;Kizzier, Donna Mcalister;Zo, Hang-Jung;Jung, Eui-Sung
    • Asia pacific journal of information systems
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    • v.21 no.3
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    • pp.51-69
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    • 2011
  • Security has been considered one of the most critical issues for managing IT resources in many organizations. Despite a growing interest and extensive research on security at various levels, little research has focused on the comparison of security knowledge levels between different cultures. The current study investigates and compares the security knowledge level between Korea and the U.S. Based on the literature review of spyware, Hofstede's cultural dimensions, and security knowledge, this study identifies three constructs (i.e., security familiarity, spyware awareness, and spyware knowledge) to examine the difference of security knowledge levels between Korea and the U.S. Six hundred ninety-six respondents from Korea and the U.S. participated in the survey, and an in-depth analysis based on analysis of covariance (ANCOVA) was carried out. The results show that the levels of security familiarity, spyware awareness, and spyware knowledge are significantly lower in Korea than in the U.S., as expected. These findings present a significant association between national culture and security knowledge, and the degree of individualism (or collectivism) plays an especially critical role in the perception of security. A number of implications for academia and practitioners emerge. Limitations and future research directions are discussed in the conclusion.

A descriptive statistical analysis of inpatients with lumbar disc herniation at a Korean medicine hospital in 2014

  • Jeong, Jeong Kyo;Kim, Myung Kwan;Park, Gi Nam;Kim, Jung Ho;Kim, Young Il
    • Journal of Acupuncture Research
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    • v.34 no.2
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    • pp.19-38
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    • 2017
  • Objectives : This is a retrospective statistical analysis of the demographic and therapeutic characteristics influencing the continued improvement of symptoms in patients treated in 2014 for herniated lumbar discs at a Korean medicine hospital; thereby, providing clinical data to further improve medical services of Korean medicine. Methods : We investigated the demographic and therapeutic variables of all patients who were diagnosed with a herniated lumbar intervertebral disc and were hospitalized for more than 1 night at Dunsan Korean medicine hospital from January 1, 2014, to December 31, 2014. IBM SPSS 21.0 was used to conduct a logistic multiple regression analysis and a covariance analysis (ANCOVA) of the demographic and therapeutic variables collected from the electronic medical records and telephone surveys. Results : 1. A longer duration of hospitalization was significantly better for the maintenance of pain relief or a decrease in the pain after discharge. 2. Younger patients were significantly less likely to be treated with a Western medical treatment after discharge. 3. Most of the demographic and therapeutic variables were not statistically significant in regards to treatment for lower back pain since discharge. Conclusion : Some of the demographic and therapeutic variables had a positive effect on the prognosis at one year or greater in patients who received integrative Korean medical treatment for lumbar disc herniation. Continued and systematic research will be needed.

FUZZY REGRESSION TOWARDS A GENERAL INSURANCE APPLICATION

  • Kim, Joseph H.T.;Kim, Joocheol
    • Journal of applied mathematics & informatics
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    • v.32 no.3_4
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    • pp.343-357
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    • 2014
  • In many non-life insurance applications past data are given in a form known as the run-off triangle. Smoothing such data using parametric crisp regression models has long served as the basis of estimating future claim amounts and the reserves set aside to protect the insurer from future losses. In this article a fuzzy counterpart of the Hoerl curve, a well-known claim reserving regression model, is proposed to analyze the past claim data and to determine the reserves. The fuzzy Hoerl curve is more flexible and general than the one considered in the previous fuzzy literature in that it includes a categorical variable with multiple explanatory variables, which requires the development of the fuzzy analysis of covariance, or fuzzy ANCOVA. Using an actual insurance run-off claim data we show that the suggested fuzzy Hoerl curve based on the fuzzy ANCOVA gives reasonable claim reserves without stringent assumptions needed for the traditional regression approach in claim reserving.

The Effects of Gamification E-Learning Classes Based on Self-Determination Theory on University Students' Class Participation, Learning Immersion, Teaching Presence (자기결정성 이론에 기반한 게이미피케이션 이러닝 수업이 대학생의 수업참여도, 학습몰입도, 교수실재감에 미치는 효과)

  • Myoung-Heo;Sang-woo Jin
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.73-83
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    • 2023
  • This study is a descriptive survey to develop a gamification e-learning class based on self-determination theory and to check its effectiveness. The data collection period was from March 1 to June 15, 2023, and 59 students at G University in G Metropolitan City were surveyed on class participation, learning immersion, and teaching presence before and after the course. IBM SPSS/Win 26.0 was used to analyze the collected data, and descriptive statistics, analysis of variance (ANOVA), and analysis of covariance (ANCOVA) were conducted. The results showed that the self-determination-based gamification class significantly improved students' class participation, learning engagement, and teaching presence (p<.05). An analysis of covariance (ANCOVA) was conducted to determine whether the general characteristics of the participants affected the results of the post-test, and gender affected the post-test results of learning engagement, with an effect of 7.9%. Based on the results of this study, it can be seen that self-determination-based gamification e-learning class is effective in improving learners' class participation, learning engagement, and teaching presence. As the demand for e-learning in universities is expanding, self-determination-based gamification e-learning classes should be developed in various fields of liberal arts and majors.

Detection of superior genotype of fatty acid synthase in Korean native cattle by an environment-adjusted statistical model

  • Lee, Jea-Young;Oh, Dong-Yep;Kim, Hyun-Ji;Jang, Gab-Sue;Lee, Seung-Uk
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.6
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    • pp.765-772
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    • 2017
  • Objective: This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score) of Hanwoo. Methods: To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms) were excluded from the model. Results: The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP) in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion: The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

Regional Gray Matter Volume Reduction Associated with Major Depressive Disorder: A Voxel-Based Morphometry

  • Tae, Woo-Suk
    • Investigative Magnetic Resonance Imaging
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    • v.19 no.1
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    • pp.10-18
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    • 2015
  • Background and Purpose: The association between the low emotional regulation and the brain structural change of major depressive disorder (MDD) has been proposed, but the voxel-based morphometry (VBM) studies on female MDD are rare. The purpose of the present study was to show the regional volume changes of gray matter (GM) in female patients with MDD by optimized VBM. Methods: To control subjects homogeneity, twenty female MDD patients and age, sex matched 21 normal controls were included for the VBM analysis. To identify the change of regional gray matter volume (GMV), the optimized VBM was performed with T1 MRIs. The amounts of gray/white matter and intracranial cavity volumes (ICV) were measured. The analysis of covariance (ANCOVA) and partial correlation analyses covariate with age and ICV were applied for VBM. Results: The age and ICV distributions were similar between the two groups. In the ANCOVA, the total GMV of MDD was smaller than that of normal controls. In the VBM, regional GMV was relatively decreased in the limbic system (amygdalae, ambient gyri, hippocampi heads, subiculum, posterior parahippocampal gyri, pulvinar nuclei, dorsal posterior cingulate gyri, and left pregenual cingulate gyrus). The lingual gyri, short insular gyri, right fusiform gyrus, and right inferior frontal gyrus were also showed decreased regional GMV. Conclusion: The results of this study indicate that the female MDD is mainly associated with the structural deficits of the limbic system and limbic system related cortices, which were known to the center of emotions.

Using ranked auxiliary covariate as a more efficient sampling design for ANCOVA model: analysis of a psychological intervention to buttress resilience

  • Jabrah, Rajai;Samawi, Hani M.;Vogel, Robert;Rochani, Haresh D.;Linder, Daniel F.;Klibert, Jeff
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.241-254
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    • 2017
  • Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in analysis of covariance (ANCOVA) models. A comparison to simple random sampling (SRS) is made to demonstrate efficiency. The results indicate that the required sample sizes for a given precision are smaller under RSS than under SRS. The modified RSS protocol was applied to an experimental study. The experimental study was designed to obtain a better understanding of the pathways by which positive experiences (i.e., goal completion) contribute to higher levels of happiness, well-being, and life satisfaction. The use of the RSS method resulted in a cost reduction associated with smaller sample size without losing the precision of the analysis.