• 제목/요약/키워드: categorical effect

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Test of Homogeneity Baseon Complex Survey Data : Discussion Based on Power of Test

  • Heo, Sun-Yeong;Yi, Su-Cheol
    • Journal of the Korean Data and Information Science Society
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    • 제16권3호
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    • pp.609-620
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    • 2005
  • In the secondary data analysis for categorical data, situations often arise in which the estimated cell variances are available, but not the full matrix of variances. In this case researchers are often inclined to use Pearson-type test statistics for homogeneity. However, for a complex sample observed cell proportions are not distributed as multinomial and Pearson-type test statistic generally is not distributed asymptotically as chi-square distribution. This paper evaluates powers for Wald test and Pearson-type test and the first order corrected test of Pearson-type test for homogeneity. The resulting power curves indicate that as the misspecification effect increases, the amount of inflation of significance level and the loss of power Pearson-type test are getting more severe.

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Growth curve modeling of nucleus F0 on Korean accentual phrase

  • Yoon, Tae-Jin
    • 말소리와 음성과학
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    • 제9권3호
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    • pp.17-23
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    • 2017
  • The present study investigates the effect of Accentual Phrase on F0 using a subset of large-scale corpus of Seoul Korean. Four syllable words which were neither preceded nor followed by silent pauses were presumed to be canonical exemplars of Accentual Phrases in Korean. These four syllable words were extracted from female speakers' speech samples. Growth curve analyses, combination of regression and polynomial curve fitting, were applied to the four syllable words. Four syllable words were divided into four groups depending on the categorical status of the initial segment: voiceless obstruents, voiced obstruents, sonorants, and vowels. Results of growth curve analyses indicate that initial segment types have an effect on the F0 (in semitone) in the nucleus of the initial syllable, and the cubic polynomial term revealed that some of the medial low tones in the 4 syllable words may be guided by the principle of contrast maximization, while others may be governed by the principle of ease of articulation.

Knowledge Representation Using Decision Trees Constructed Based on Binary Splits

  • Azad, Mohammad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권10호
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    • pp.4007-4024
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    • 2020
  • It is tremendously important to construct decision trees to use as a tool for knowledge representation from a given decision table. However, the usual algorithms may split the decision table based on each value, which is not efficient for numerical attributes. The methodology of this paper is to split the given decision table into binary groups as like the CART algorithm, that uses binary split to work for both categorical and numerical attributes. The difference is that it uses split for each attribute established by the directed acyclic graph in a dynamic programming fashion whereas, the CART uses binary split among all considered attributes in a greedy fashion. The aim of this paper is to study the effect of binary splits in comparison with each value splits when building the decision trees. Such effect can be studied by comparing the number of nodes, local and global misclassification rate among the constructed decision trees based on three proposed algorithms.

Estimation of Genetic Parameters for Calving Ease by Heifers and Cows Using Multi-trait Threshold Animal Models with Bayesian Approach

  • Lee, D.H.
    • Asian-Australasian Journal of Animal Sciences
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    • 제15권8호
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    • pp.1085-1090
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    • 2002
  • Genetic parameters for birth weights (BWT), calving ease scores observed from calves born by heifers (CEH), and calving ease scores observed from calves born by cows (CEC) were estimated using Bayesian methodology with Gibbs sampling in different threshold animal models. Data consisted of 77,458 records for calving ease scores and birth weights in Gelbvieh cattle. Gibbs samplers were used to obtain the parameters of interest for the categorical traits in two univariate threshold animal models, a bivariate threshold animal model, and a three-trait linear-threshold animal model. Samples of heritabilities and genetic correlations were calculated from the posterior means of dispersion parameters. In a univariate threshold animal model with CEH (model 1), the posterior means of heritabilities for calving ease was 0.35 for direct genetic effects and 0.18 for maternal genetic effects. In the other univariate threshold model with CEC (model 2), the posterior means of heritabilities of CEC was 0.28 for direct genetic effects and 0.18 for maternal genetic effects. In a bivariate threshold model with CEH and CEC (model 3), heritability estimates were similar to those in unvariate threshold models. In this model, genetic correlation between heifer calving ease and cow calving ease was 0.89 and 0.87 for direct genetic effect and maternal genetic effects, respectively. In a three-trait animal model, which contained two categorical traits (CEH and CEC) and one continuous trait (BWT) (model 4), heritability estimates of CEH and CEC for direct (maternal) genetic effects were 0.40 (0.23) and 0.23 (0.13), respectively. In this model, genetic correlation estimates between CEH and CEC were 0.89 and 0.66 for direct genetic effects and maternal effects, respectively. These estimates were greater than estimates between BWT and CEH (0.82 and 0.34) or BWT and CEC (0.85 and 0.26). This result indicates that CEH and CEC should be high correlated rather than estimates between calving ease and birth weight. Genetic correlation estimates between direct genetic effects and maternal effects were -0.29, -0.31 and 0.15 for BWT, CEH and CEC, respectively. Correlation for permanent environmental effects between BWT and CEC was -0.83 in model 4. This study can provide genetic evaluation for calving ease with other continuous traits jointly with assuming that calving ease from first calving was a same trait to calving ease from later parities calving. Further researches for reliability of dispersion parameters would be needed even if the more correlated traits would be concerned in the model, the higher reliability could be obtained, especially on threshold model with property that categorical traits have little information.

PLS-MGA 방법론을 활용한 제도론적 관점에서의 공공제도 품질과 사용자 행태의 분석 (Analysis of Public System's Quality and User Behavior Using PLS-MGA Methodology : An Institutional Perspective)

  • 이재열;황승준
    • 산업경영시스템학회지
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    • 제40권2호
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    • pp.78-91
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    • 2017
  • In this study, we conducted a comparative study on user's perception and behavior on public system service (PSS) using institutionalism theory and MGA (multi-group analysis) methodology. In particular, this study focuses on how institutional isomorphism is applied to public system services and how MGA can be implemented correctly in a variance based SEM (structural equation model) such as PLS (partial least square). A data set of 496 effective responses was collected from pubic system users and an empirical research was conducted using three segmented models categorized by public proximity theory (public firms = 113, government contractors = 210, private contractors = 173). For rigorous group comparisons, each model was estimated by the same indicators and approaches. PLS-SEM was used in testing research hypotheses, followed by parametric and non-parametric PLS-MGA procedures in testing categorical moderation effects. This study applied novel procedures for testing composite measurement invariance prior to multi-group comparisons. The following main results and implications are drawn : 1) Partial measurement invariance was established. Multi-group analysis can be done by decomposed models although data can not be pooled for one integrated model. 2) Multi-group analysis using various approaches showed that proximity to public sphere moderated some hypothesized paths from quality dimensions to user satisfaction, which means that categorical moderating effects were partially supported. 3) Careful attention should be given to the selection of statistical test methods and the interpretation of the results of multi-group analysis, taking into account the different outcomes of the PLS-MGA test methods and the low statistical power of the moderating effect. It is necessary to use various methods such as comparing the difference in the path coefficient significance and the significance of the path coefficient difference between the groups. 4) Substantial differences in the perceptions and behaviors of PSS users existed according to proximity to public sphere, including the significance of path coefficients, mediation and categorical moderation effects. 5) The paper also provides detailed analysis and implication from a new institutional perspective. This study using a novel and appropriate methodology for performing group comparisons would be useful for researchers interested in comparative studies employing institutionalism theory and PLS-SEM multi-group analysis technique.

Autoregressive Cholesky Factor Modeling for Marginalized Random Effects Models

  • Lee, Keunbaik;Sung, Sunah
    • Communications for Statistical Applications and Methods
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    • 제21권2호
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    • pp.169-181
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    • 2014
  • Marginalized random effects models (MREM) are commonly used to analyze longitudinal categorical data when the population-averaged effects is of interest. In these models, random effects are used to explain both subject and time variations. The estimation of the random effects covariance matrix is not simple in MREM because of the high dimension and the positive definiteness. A relatively simple structure for the correlation is assumed such as a homogeneous AR(1) structure; however, it is too strong of an assumption. In consequence, the estimates of the fixed effects can be biased. To avoid this problem, we introduce one approach to explain a heterogenous random effects covariance matrix using a modified Cholesky decomposition. The approach results in parameters that can be easily modeled without concern that the resulting estimator will not be positive definite. The interpretation of the parameters is sensible. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using this method.

A modification of McFadden's R2 for binary and ordinal response models

  • Ejike R. Ugba;Jan Gertheiss
    • Communications for Statistical Applications and Methods
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    • 제30권1호
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    • pp.49-63
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    • 2023
  • A lot of studies on the summary measures of predictive strength of categorical response models consider the likelihood ratio index (LRI), also known as the McFadden-R2, a better option than many other measures. We propose a simple modification of the LRI that adjusts for the effect of the number of response categories on the measure and that also rescales its values, mimicking an underlying latent measure. The modified measure is applicable to both binary and ordinal response models fitted by maximum likelihood. Results from simulation studies and a real data example on the olfactory perception of boar taint show that the proposed measure outperforms most of the widely used goodness-of-fit measures for binary and ordinal models. The proposed R2 interestingly proves quite invariant to an increasing number of response categories of an ordinal model.

The Effect of Construal Level on Variety Seeking across Subcategories

  • Suh, Jiyeon;Won, Eugene J.S.
    • Asia Marketing Journal
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    • 제21권3호
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    • pp.1-20
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    • 2019
  • The present study investigates how consumers' construal level affects their variety seeking behavior when choosing multiple items simultaneously. Especially the authors focus on the perceptual level at which variety seeking takes place and propose that variety seeking can take place not only at brand level but also at category or subcategory level. Categorical variety seeking refers to diversification of one's choices over multiple brands not within the same category but across multiple categories. Building on construal level theory, the authors expected that people engaging in higher-level construals tend to subcategorize the choice set and distribute their choices across more subcategories and designed four experiments to test the related hypotheses. The experimental results showed that consumers' construal level can affect the level at which variety seeking takes place and those with higher construal level tend to choose options seemingly more dissimilar to each other.

수용전념치료(ACT)프로그램 효과의 메타분석에 대한 융합연구 (A Convergence Study about Meta-Analysis on the Effects of ACT Intervention Program)

  • 김경희
    • 한국융합학회논문지
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    • 제7권5호
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    • pp.145-153
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    • 2016
  • 이 연구는 메타분석을 활용하여 현재 다양한 영역에서 실시되고 있는 수용전념치료 프로그램의 효과에 대해 종합적으로 평가하였다. 메타분석은 통계적인 방법을 활용하여 개입의 크기와 방향을 제시한다. 이를 통해 개입에 대한 종합적 분석이 가능하다. 논문의 선정기준을 통해 총 43편의 연구물을 분석 대상으로 선정하였다. 선정된 33편의 연구물에서 183개의 효과크기를 종합하여 전체효과크기, 하위집단별 효과크기, 메타회귀분석 결과를 제시하였다. 그 결과 수용전념치료 프로그램의 전체 효과크기는 0.704로 나타났다. 이는 중간 이상의 효과크기를 의미한다. 수용전념치료의 효과 영역에 따라 효과크기를 비교한 결과, 정의적 영역, 인지적 영역, 행동적 영역 순으로 효과크기를 나타냈다. 참가자의 특성에 따른 효과크기를 비교한 결과 첫째, 성별에 따른 분석결과, 혼성 집단, 여성 집단, 남성 집단 순으로 효과크기를 나타냈다. 둘째 연령에 따른 분석 결과 일반성인, 대학생(대학원생), 청소년 순이었다. 이러한 연구 결과를 바탕으로 후속연구와 향후 프로그램 운영에 대한 시사점을 논의하였다.

임의효과를 이용한 충남지역 소나무림의 바이오매스 모형 개발 (The Development of Biomass Model for Pinus densiflora in Chungnam Region Using Random Effect)

  • 표정기;손영모
    • 한국산림과학회지
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    • 제106권2호
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    • pp.213-218
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    • 2017
  • 본 연구의 목적은 임의효과(random effect)를 이용하여 충남지역 임령-바이오매스 모형을 개발하고 임의효과의 적용성을 평가하는데 있다. 충남지역 소나무림의 임령에 따른 바이오매스 모형 개발을 위해 임분 구조를 고려하여 전국의 중부지방소나무 임분에서 30개소(150그루)를 조사하고 임령과 바이오매스 자료를 수집하였다. 모형 개발에서 중부지방소나무의 임령-바이오매스 관계는 고정효과(fixed effect)이고 지역간 차이를 임의효과로 설정하였다. 임의효과에 따른 모형의 적합도를 검정하기 위해 아카이케의 정보기준(Akaike Information Criterion, AIC)을 참고하고 지역간 차이에 따른 분산-공분산 행렬과 오차항을 추정하였다. 추정된 공분산은 -1.0022, 오차항은 0.6240이고 분산-공분산 행렬을 이용한 임의효과 모형의 AIC는 377.7을 나타내어 선행 연구와 이질적인 차이는 없었다. 이러한 결과는 범주형 자료의 임의효과가 모형 개발에 반영된 결과로 판단된다. 본 연구의 결과는 임의효과를 이용하여 일부지역에 국한되어 개발되었던 바이오매스 모형 연구에 활용이 가능하다.