• 유통과학연구
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• 제17권3호
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

• Communications for Statistical Applications and Methods
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• 제30권1호
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• pp.65-73
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• 2023

Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.

• 한국ITS학회 논문지
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• 제14권1호
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• pp.85-93
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• 2015

기존의 교통사고모형은 수집된 데이터에 대한 추정된 모수가 고정되어있다고 가정하여 교통량이나 기하구조의 길이와 폭 등은 설치형태와 관계없이 동일한 값을 적용하는 고정효과모형을 이용하여 개발하였다. 하지만 고정효과를 이용한 모형은 모형을 통해 추정된 계수의 표준오차 값이 과소 추정되거나 각 계수의 t-값이 과도하게 산정되어 모형의 설명력이 낮아지게 된다. 이를 극복하기 위하여 교통량, 기하구조, 그리고 관측되지 않은 다른 요인 등에 대한 이질성을 고려한 임의효과모형을 활용하여 모형을 개발할 수 있다. 본 연구에서는 임의효과모형의 효용성을 파악하고자 대전광역시 주요 89개 교차로를 대상으로 데이터를 수집하여 임의효과와 고정효과를 이용한 음이항 회귀모형을 개발하고 이를 비교 분석하였다. 모형개발 결과 년평균일교통량, 제한속도, 차로수, 우회전 전용차로 설치유무, 전방신호등 설치유무 등이 유효한 설명변수로 나타났으며 모형의 설명력을 비교해보면 로그-우도함수값이 임의효과에서 -1537.802로 고정효과의 로그-우도함수값 -1691.327보다 모형 설명력이 좋은 것으로 나타났으며 우도비의 경우 임의효과에서 0.279로 고정효과의 0.207보다 개선된 것으로 나타나 임의효과를 이용한 모형이 고정효과를 이용한 모형보다 우수한 것으로 나타났다.

• Asian-Australasian Journal of Animal Sciences
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• 제20권2호
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• pp.160-165
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• 2007

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1429-1440
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• 2008

In a meta-analysis combining the results from different clinical trials, it is important to consider the possible heterogeneity in outcomes between trials. Such variations can be regarded as random effects. Thus, random-effect models such as HGLMs (hierarchical generalized linear models) are very useful. In this paper, we propose a HGLM framework for analyzing the binominal response data which may have variations in the odds-ratios between clinical trials. We also present the prediction intervals for random effects which are in practice useful to investigate the heterogeneity of the trial effects. The proposed method is illustrated with a real-data set on 22 trials about respiratory tract infections. We further demonstrate that an appropriate HGLM can be confirmed via model-selection criteria.

• 응용통계연구
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• 제28권2호
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• pp.269-279
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• 2015

본 논문에서는 임의효과에 대한 추론 문제가 다루어졌으며 이 추론에서 신뢰분포를 사용하는 것이 제안되었다. 신뢰분포를 이용한 방법은 표본의 크기가 작아도 임의절편들이 있는 로지스틱 회귀분석에서 좋은 결과를 보여주었으며, 자료분석을 통해서도 각 개체가 가지는 임의효과들에 대한 세밀한 분석이 가능함을 확인하였다.

• 품질경영학회지
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• 제34권3호
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• pp.19-30
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• 2006

For highly reliable products, it is difficult to assess the lifetime of the products with traditional life tests. Accordingly, a recent approach is to observe the performance degradation of product during the test rather than regular failure time. This study compares performances of three methods(i.e. the approximation, analytical and numerical methods) to estimate the parameters and quantiles of the lifetime when the time-to-failure distribution follows Weibull and lognormal distributions under a random coefficient degradation rate model. Numerical experiments are also conducted to investigate the effects of model error such as measurements in a random coefficient model.

• 한국도로학회논문집
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• 제20권2호
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• pp.119-126
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• 2018

PURPOSES : The purpose of this study is to develop a crash prediction model at signalized intersections, which can capture the randomness and uncertainty of traffic accident forecasting in order to provide more precise results. METHODS : The authors propose a random parameter (RP) approach to overcome the limitation of the Count model that cannot consider the heterogeneity of the assigned locations or road sections. For the model's development, 55 intersections located in the Daejeon metropolitan area were selected as the scope of the study, and panel data such as the number of crashes, traffic volume, and intersection geometry at each intersection were collected for the analysis. RESULTS : Based on the results of the RP negative binomial crash prediction model developed in this study, it was found that the independent variables such as the log form of average annual traffic volume, presence or absence of left-turn lanes on major roads, presence or absence of right-turn lanes on minor roads, and the number of crosswalks were statistically significant random parameters, and this showed that the variables have a heterogeneous influence on individual intersections. CONCLUSIONS : It was found that the RP model had a better fit to the data than the fixed parameters (FP) model since the RP model reflects the heterogeneity of the individual observations and captures the inconsistent and biased effects.

• 응용통계연구
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• 제28권2호
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• pp.211-219
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• 2015

일반화 선형혼합모델은 일반적으로 경시적 범주형 자료를 분석하는데 사용된다. 이 모델에서 임의효과는 반복 측정치들의 시간에 따른 의존성을 설명한다. 임의효과 공분산행렬의 추정은 여러가지 제약조건들 때문에 쉽지 않은 문제이다. 제약조건으로는 행렬의 모수들의 수가 많으며, 또한 추정된 공분산행렬은 양정치성을 만족하여야 한다. 이러한 제한을 극복하기 위해, 임의효과 공분산행렬의 모형화를 위한 여러가지 방법이 제안되었다: 수정 단냠레스키분해, 이동평균 단냠레스키분해와 부분 자기상관행렬을 이용한 방법이 있다. 이 논문에서 위의 제안된 방법들을 소개한다.

• 응용통계연구
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• 제28권2호
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• pp.123-136
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• 2015

관측 가능한 변수들 사이의 관계를 묘사한 갈릴레오의 물리학 법칙 발견 이후, 과학은 큰 성과를 거두며 발전해왔다. 그러나, 관측할 수 없는 변량효과를 함께 이용하여 더 많은 자연 현상을 설명할 수 있게 되었고, 이를 이용한 최초의 통계적 모형인 혼합효과모형이 소개되었다. 계산기술의 발달과 더불어 복잡한 현상에 대한 추론을 위하여 혼합효과모형은 그 중요성이 더욱 커지고 있다. 이러한 혼합효과모형은 최근 다단계 일반화 선형모형을 포함한 여러 모형으로 확장되었으며, 관측할 수 없는 변량효과를 추론하기 위한 다단계 가능도가 제시되었다. 혼합효과모형 특집호를 통해 이러한 모형들이 여러 통계학적 문제점을 해결하는 과정을 제시하고, 앞으로 어떤 확장이 추가적으로 요구되는 지에 대하여 논할 것이다. 빈도록적 접근법과 베이지안 접근법을 함께 다룬다.