• 제목/요약/키워드: Hierarchical linear model

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Using the Hierarchical Linear Model to Forecast Movie Box-Office Performance: The Effect of Online Word of Mouth

  • Park, Jongmin;Chung, Yeojin;Cho, Yoonho
    • Asia pacific journal of information systems
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    • 제25권3호
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    • pp.563-578
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    • 2015
  • Forecasting daily box-office performance is critical for planning the distribution of marketing resources, and by extension, maximizing profits. For certain movies, the number of viewers increases rapidly at the beginning of their theatrical run, and the increments slow down later. Other movies are not popular in the beginning, but the audience sizes grow rapidly afterward. Thus, the audience attendance of movies grow in different trajectories, which are influenced by various factors including marketing budget, distributors, directors, actors, and word of mouth. In this paper, we propose a method for predicting the daily performance trajectory of running movies based on the hierarchical linear model. More specifically, we focus on the effect of online word of mouth on the shape of the growth curves. We fitted the mean trajectory of the cumulative audience size as a cubic function of time, and allowed the intercept and slope to vary movie-to-movie. Moreover, we fitted the linear slope with a function of online word of mouth predictors to help determine the shape of the trajectories. Finally, we provide performance predictions for individual movies.

Joint HGLM approach for repeated measures and survival data

  • Ha, Il Do
    • Journal of the Korean Data and Information Science Society
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    • 제27권4호
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    • pp.1083-1090
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    • 2016
  • In clinical studies, different types of outcomes (e.g. repeated measures data and time-to-event data) for the same subject tend to be observed, and these data can be correlated. For example, a response variable of interest can be measured repeatedly over time on the same subject and at the same time, an event time representing a terminating event is also obtained. Joint modelling using a shared random effect is useful for analyzing these data. Inferences based on marginal likelihood may involve the evaluation of analytically intractable integrations over the random-effect distributions. In this paper we propose a joint HGLM approach for analyzing such outcomes using the HGLM (hierarchical generalized linear model) method based on h-likelihood (i.e. hierarchical likelihood), which avoids these integration itself. The proposed method has been demonstrated using various numerical studies.

Bayesian Curve-Fitting in Semiparametric Small Area Models with Measurement Errors

  • Hwang, Jinseub;Kim, Dal Ho
    • Communications for Statistical Applications and Methods
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    • 제22권4호
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    • pp.349-359
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    • 2015
  • We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

개인과 집단의 특성이 지식창출에 미치는 영향 (The Effect of Individual and Team Characteristics on Knowledge Creation : An Analysis by Hierarchical Linear Model (HLM))

  • 강소라;김민선
    • Journal of Information Technology Applications and Management
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    • 제17권4호
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    • pp.19-38
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    • 2010
  • This paper investigates the effect of stress on knowledge creation. The goal stress of resource inadequacy and job stress had negative influences on knowledge creation. However, the cohesion and mastery climate of team had positive influence on knowledge creation. Therefore this paper verifies the moderate role of the cohesion and mastery climate of team on the relationship between stress and knowledge creation. The model developed was tested using data collected from knowledge based industry with 375 members in 69 teams in 12 different firms. A Hierarchical Linear Model (HLM) was used to test the hypotheses generated from the model. Results show that job stress had a negative influence on knowledge creation as we expected but the goal stress didn't. The mastery climate of team affected knowledge creation positively and moderated the relationship between the goal stress and knowledge creation. Furthermore, the team cohesion had a positive influence on knowledge creation. The study provided some implications that practitioners should consider the stress when they design jobs for team members and suggest them the way to manage their job stress when they work.

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A Study of HME Model in Time-Course Microarray Data

  • Myoung, Sung-Min;Kim, Dong-Geon;Jo, Jin-Nam
    • 응용통계연구
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    • 제25권3호
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    • pp.415-422
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    • 2012
  • For statistical microarray data analysis, clustering analysis is a useful exploratory technique and offers the promise of simultaneously studying the variation of many genes. However, most of the proposed clustering methods are not rigorously solved for a time-course microarray data cluster and for a fitting time covariate; therefore, a statistical method is needed to form a cluster and represent a linear trend of each cluster for each gene. In this research, we developed a modified hierarchical mixture of an experts model to suggest clustering data and characterize each cluster using a linear mixed effect model. The feasibility of the proposed method is illustrated by an application to the human fibroblast data suggested by Iyer et al. (1999).

영어의 자질 수형도에 관한 연굴 (A Study on Feature Hierarchy in English)

  • 이해봉
    • 대한음성학회지:말소리
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    • 제29_30호
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    • pp.43-60
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    • 1995
  • Standard generative phonologists assumed that there were no orders or hierarchies among distinctive features. This means that the distinctive features which make up a segment are independent and unordered. The unordered linear matrix cannot explain phonological phenomena such as complex segments as hierarchical representation does neatly. The hierarchical feature representation theory which embodies the concept of multi-tiered phonological representation organizes distinctive features in the appearance of hierarchical dominance. This paper aims to show how we can solve some problems of the linear feature representation. As regard underlying representation the theory of underspecification is discussed. I propose a feature hierarchy similar to that of Sagey(1986) but slightly different. I show English consonantal assimilation in feature hierarchical model compared with that of feature changing theory of linear representation.

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근로계층의 빈곤 결정요인에 관한 다층분석 (Determinants of the Working Poor : An Analysis Using Hierarchical Generalized Linear Model)

  • 김교성;최영
    • 한국사회복지학
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    • 제58권2호
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    • pp.119-141
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    • 2006
  • 본 연구의 목적은 우리나라 근로빈곤층의 실태와 특성을 파악하고 근로빈곤층의 정태적 결정요인을 파악하는데 있다. 이를 위해 본 연구는 한국노동패널조사의 제2차년도(1999년)부터 제7차년도(2004년)의 반복측정 자료를 개인간(between-person), 개인내(within-person) 2층(two-level)으로 병합하여 자료를 구성하고 이를 통해 각 수준의 변수들이 근로자의 빈곤지위여부에 미치는 영양을 위계적 일반화 선형모형(HGLM: hierarchical generalized linear model)을 이용하여 추정하였다. 분석의 결과, 우리나라 취업자 가운데 가구소득이 빈곤선 이하의 생활을 하는 근로빈곤층(개인)의 규모는 약 10.0% 내외의 규모를 보이는 것으로 나타났다. 이러한 근로계층의 빈곤지위에 영양을 미치는 요인으로는 성별, 교육수준, 결혼상태, 취업형태, 고용업종, 고용직종 등으로 밝혀졌으며 이외 가구원수, 연령 등은 유의미안 영향을 미치지 않은 것으로 나타났다.

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위계선형모형을 이용한 개인의 정보화 격차 결정요인 (Determinants of the Digital Divide using Hierarchical Generalized Linear Model)

  • 김미영;최영찬
    • 농촌계획
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    • 제14권3호
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    • pp.63-73
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    • 2008
  • The purpose of this study is to analyze the determinants of the digital divide at individual level and regional level in Korea, considering interaction between individual and the regional variables. Following results are obtained. First, individual level digital devide in the 16 different regions has been found in terms of Internet use, implying the needs for further analysis on impact of the regional factor in individual Internet use. Second, the result finds the impact of level-l individual variables, "gender, age, education, income and jobs" on digital divide, significantly at level 10% level. Third, the regional variables influencing the individual digital divide were not found at state level. However, regional factors might affect digital devide at county level. Study suggest some plans to reduce digital divide. First, the digital devide at individual level should be remedied by focusing on neglected class of people. Second, we need to approach the digital divide by analyzing in more detail, reflecting interactions of the regional variables and individual variables. Third, we should come up with a policy for mending the digital divide at regional level.

Empirical Bayes Estimate for Mixed Model with Time Effect

  • Kim, Yong-Chul
    • Communications for Statistical Applications and Methods
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    • 제9권2호
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    • pp.515-520
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    • 2002
  • In general, we use the hierarchical Poisson-gamma model for the Poisson data in generalized linear model. Time effect will be emphasized for the analysis of the observed data to be collected annually for the time period. An extended model with time effect for estimating the effect is proposed. In particularly, we discuss the Quasi likelihood function which is used to numerical approximation for the likelihood function of the parameter.