• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.427-439
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• 2017

Quade (1967) proposed RANK ANCOVA, which is a nonparametric method to test differences between treatments when there are covariates. Hwang and Kim (2012) also proposed a joint placement test on covariate-adjusted residuals. In this paper, we proposed a new nonparametric method to control the effect of covariate on a response variable that uses linear statistics on covariate adjusted-residuals. The score function used in the linear statistics was proposed by Jeon and Kim (2016). Monte Carlo simulation is also conducted to compare the empirical powers of the proposed method with previous methods.

• Journal of East-West Nursing Research
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• v.14 no.1
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• pp.78-86
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• 2008

본 연구는 여대생의 건강증진행위를 설명하기 위하여, 문헌고찰을 통해 가설적 모형을 도출하고, 여대생을 대상으로 건강증진행위를 횡단적으로 조사하여 모형의 적합성과 모형에서 제시된 가설을 검증하는 서술적 상관관계 연구이다. 연구에 사용된 변수는 건강증진행위와 관련된 선행 문헌의 고찰을 근거로 선정되었으며, 총 280명의 자료가 최종 분석에 이용되었다. 설문지는 Pender의 건강증진모형을 기초로 하여 개발하였으며, 조정요인 5문항, 건강상태 지각 3문항, 건강 통제위 4문항, 자아 존중감 5문항, 건강증진 행위 24문항의 총 41문항으로 구성하여 사용하였다. 개발된 항목에 대하여 간호대학생들을 대상으로 사전 조사를 실시하여 최종적인 설문지를 완성하였다. 본 연구모형에 대한 구성개념의 파악을 위해서 탐색적 요인분석을 실시하였고, 측정항목에 대한 요인별 단일 차원성 확인 및 통계적 검정을 위해 확인적 요인분석을 실시하였다. 연구의 가설검증을 위해 공변량 구조분석을 실시하였다. 모형의 적합도는 카이제곱은 244.04(자유도=121, p<0.001), GFI=0.91, CFI=0.97, NNFI=0.96, RMSR= 0.022으로 나타났다. 분석결과 여대생의 자아존중감과 내적통제위는 건강상태지각 및 건강증진행위에 유의한 영향을 미치는 요인으로 확인되었으며, 여대생의 건강상태지각은 건강증진행위에 유의한 영향을 미치는 것으로 나타났다.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.449-460
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• 2015

The reliability of air quality evaluation results for green transportation could be improved by applying correct emission factors. Unlike previous studies, which estimated emission factors that focused on vehicles in laboratory experiments, this study investigates emission factors according to road types and time using real driving data. The real driving data was collected using a Portable Activity Monitoring System (PAMS) according to road types and time, which it compared and analyzed fuel consumption from collected data. The result of the study shows that fuel consumption on national highway is 17.33% higher than the fuel consumption on expressway. In addition, the average fuel consumption of peak time is 4.7% higher than that of non-peak time for 22.5km/h. The difference in fuel consumption for road types and time is verified using ANOCOVA and MANOVA. As a result, the hypothesis of this study - that fuel consumption differs according to road types and time, even if the travel speed is the same - has proved valid. It also suggests correction factor of emission factors by using the difference in fuel consumption. It is highly expected that this study can improve the reliability of emissions from mobile pollution sources.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.559-566
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• 2011

Biplot is a useful graphical method to explore simultaneously rows and columns of two-way data matrix. In particular, canonical correlation biplot is a method for investigating two sets of variables and observations in canonical correlation analysis graphically. For more than three sets of variables, we can apply the generalized canonical correlation biplot in generalized canonical correlation analysis which is an expansion of the canonical correlation analysis. On the other hand, we consider the set of covariate variables which is affecting the linearly two sets of variables. In this case, if we apply the generalized canonical correlation biplot, we cannot clearly interpret the other two sets of variables due to the effect of the set of covariate variables. Therefor, in this paper, we will apply the partial canonical correlation analysis of Rao (1969) removing the linear effect of the set of covariate variables on two sets of variables. We will suggest the partial canonical correlation biplot for inpreting the partial canonical correlation analysis graphically.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.230-230
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• 2019

대규모순환패턴과 같은 기후시스템에서의 상태와 변화를 정량화하여 나타낸 기상인자는 수문기상학적 변수와 밀접한 연관이 있는 것으로 알려져 있으며, 이에 따라 비정상성 빈도해석의 수행에 있어서 확률분포모형의 매개변수에 대한 공변량으로 널리 활용되고 있다. 본 연구에서는 비정상성 강우빈도해석 시 매개변수의 공변량으로 우리나라의 극치강우의 장기경향성을 잘 반영할 수 있는 기상인자를 선정하고자 한다. 먼저, 시계열자료를 주기성을 가지는 내재모드함수와 장기경향성을 나타내는 잔여값으로 분해할 수 있는 앙상블 경험적 모드분해법을 이용하여 우리나라 전역에 분포된 61개 지점에서 관측된 연 최대치 강우자료의 평균 및 분산에 대한 잔여값을 추출하였다. 다음으로 11개의 월 단위 기상인자에 대한 계절별 연 평균 시계열과 추출된 평균 및 분산의 잔여값과의 상관계수를 산정하였다. 그 결과, 11개의 기상인자 중 Atlantic Meridional Mode (AMM), Atlantic Multi-decadal Oscillation (AMO), North Atlantic Oscillation (NAO)가 우리나라 연 최대치 강우자료의 평균 및 분산에 대한 장기경향성과 높은 상관성이 있는 것으로 나타났다. 계절적으로는 AMM과 AMO의 경우 이전 년도 가을철 평균이 전 지점 평균 약 0.6, NAO는 이전 년도 여름철 평균이 전 지점 평균 0.3 이상의 유의한 상관계수를 가지는 것으로 나타났다.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.739-748
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• 2003

The objective of this study was to estimate genetic parameters for test-day milk production and somatic cell score using field data collected by dairy herd improvement program in Korea. Random regression animal models were applied to estimate genetic variances for milk production and somatic cell score. Heritabilities for milk yields, fat percentage, protein percentage, solid-not-fat percentage, and somatic cell score from test day records of 5,796 first lactation Holstein cows were estimated by REML algorithm in single trait random regression test-day animal models. For these analyses, Legendre polynomial covariate function was applied to model the fixed effect of age-season, the additive genetic effect and the permanent environment effect as random. Homogeneous residual variance was assumed to be equal throughout lactation. Heritabilities as a function of time were calculated from the estimated curve parameters from univariate analyses. Heritability estimates for milk yields were in range of 0.13 to 0.29 throughout first lactation. Heritability estimates for fat percentage, protein percentage and solid-not-fat percentage were within 0.09 to 0.11, 0.12 to 0.19 and 0.17 to 0.23, respectively. For somatic cell score, heritabilities were within 0.02 to 0.04. Heritabilities for milk productions and somatic cell score were fluctuated by days in milk with comparing 305d milk production.

• Journal of Animal Science and Technology
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• v.47 no.5
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• pp.703-710
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• 2005

Data from Hanwoo steers and bull calves were analyzed to see the phenotypic and genetic relationships between carcass traits from four different covariance models. Four models fit test station and test period as fixed effect of contemporary group and sire as random effect assuming paternal half-sib relationships among animals. Each model fits one of linear covariate (s) of different slaughter end points-age at slaughter in the first order, age at slaughter in the first and second order, slaughter weight or back fat thickness at 12-13th rib of cold carcass. Age at slaughter in its second order was not significant. Age at slaughter accounted for signifi- cant amount of genetic variances and covariances of carcass traits. Heritability estimates of back fat thickness, rib eye area, carcass weight, marbling score and dressing percentage were 0.34, 0.22, 0.24, 0.42 and 0.18, respectively at constant age basis. The genetic correlation between carcass weight and the other variables were all positive and low to high in magnitude. Genetic correlations between back fat thickness and rib eye area and between marbling score and dressing percentage were low but negative. Variance and covariance structure between these traits were shifted to a great extent when these variables were regressed on slaughter weight or on back fat thickness. These two covariates counteracted to each other but they adjusted each carcass variable or their interrelationship according to differential growth of body components, bone, muscle and fat. Slaughter weight tended to decrease genetic variances and covariances of carcass weight and between component traits and back fat thickness tended to increase those of rib eye area and between rib eye area and carcass weight.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.97-105
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• 2012

The generalized canonical correlation biplot is a 2-dimensional plot to graphically investigate the relationship between more than three sets of variables and the relationship between observations and variables. Recently, Choi and Choi (2010) investigated the relationship physique, physical fitness and basic skill factors of Korea Tennis Association(KTA) players of using this biplot; however we consider the set of covariate variables affecting the linearly on two sets of variables. In this case, if we apply the generalized canonical correlation biplot, we cannot clearly interpret the other two sets of variables due to the effect of the set of covariate variables. Moreover, Yeom and Choi (2011) provided partial canonical correlation analysis that removed the linear effect of the set of covariate variables on two sets of variables. In addition, Procrustes analysis is a useful tool for comparing shape between configurations. In this study, we will investigate the relationship between physical fitness and basic skill factors of KTA players of using a partial canonical correlation biplot and Procrustes analysis. We compare shapes and shape variabilities for the generalized, partial and simple canonical correlation biplots.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.287-292
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• 2002

최근 여러 분야에서 로지스틱 회귀에 대한 필요성과 그 응용이 급증하면서 이를 분석하기 위한 통계패키지가 많이 개발되어 사용되고 있다. 이 논문에서는 자료의 유형에 따라 활용할 수 있는 여러 형태의 로지스틱 회귀모형을 간단히 살펴보고, SPSS, SAS, STATA, MINITAB과 같은 통계패키지를 사용하여 로지스틱 회귀모형에 적용할 때 각각 다룰 수 있는 범위와 그 특징에 대해 다룬다.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.113-122
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• 2016

Longitudinal data often occur in prospective follow-up studies. Joint model for longitudinal data and failure time has been applied on several works. In this paper, we extend it to the case where longitudinal data involve informative observation time process as well as competing risks survival times. We use a likelihood approach and derive an EM algorithm to obtain maximum likelihood estimate of parameters. A suggested joint model allows us to make inferences for three components: longitudinal outcome, observation time process and competing risk failure time. In addition, we can test the association among these components. In this paper, liver cirrhosis patients' data is analyzed. The relationship between prothrombin times measured at irregular visiting times and drop outs is investigated with a joint model.