• Title/Summary/Keyword: mixed-effects model

Search Result 493, Processing Time 0.021 seconds

A Cumulative Logit Mixed Model for Ordered Response Data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
    • /
    • v.17 no.1
    • /
    • pp.123-130
    • /
    • 2006
  • This paper discusses about how to build up a mixed-effects model using cumulative logits when some factors are fixed and others are random. Location effects are considered as random effects by choosing them randomly from a population of locations. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

  • PDF

Analysis of Field Test Data using Robust Linear Mixed-Effects Model (로버스트 선형혼합모형을 이용한 필드시험 데이터 분석)

  • Hong, Eun Hee;Lee, Youngjo;Ok, You Jin;Na, Myung Hwan;Noh, Maengseok;Ha, Il Do
    • The Korean Journal of Applied Statistics
    • /
    • v.28 no.2
    • /
    • pp.361-369
    • /
    • 2015
  • A general linear mixed-effects model is often used to analyze repeated measurement experiment data of a continuous response variable. However, a general linear mixed-effects model can give improper analysis results when simultaneously detecting heteroscedasticity and the non-normality of population distribution. To achieve a more robust estimation, we used a heavy-tailed linear mixed-effects model for a more exact and reliable analysis conclusion than a general linear mixed-effects model. We also provide reliability analysis results for further research.

Mixed-effects LS-SVR for longitudinal dat

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
    • /
    • v.21 no.2
    • /
    • pp.363-369
    • /
    • 2010
  • In this paper we propose a mixed-effects least squares support vector regression (LS-SVR) for longitudinal data. We add a random-effect term in the optimization function of LS-SVR to take random effects into LS-SVR for analyzing longitudinal data. We also present the model selection method that employs generalized cross validation function for choosing the hyper-parameters which affect the performance of the mixed-effects LS-SVR. A simulated example is provided to indicate the usefulness of mixed-effect method for analyzing longitudinal data.

A Proportional Odds Mixed - Effects Model for Ordinal Data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
    • /
    • v.18 no.2
    • /
    • pp.471-479
    • /
    • 2007
  • This paper discusses about how to build up mixed-effects model for analysing ordinal response data by using cumulative logits. Random factors are assumed to be coming from the designed sampling scheme for choosing observational units. Since the observed responses of individuals are ordinal, a proportional odds model with two random effects is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

  • PDF

Small Area Estimation via Nonparametric Mixed Effects Model

  • Jeong, Seok-Oh;Shin, Key-Il
    • The Korean Journal of Applied Statistics
    • /
    • v.25 no.3
    • /
    • pp.457-464
    • /
    • 2012
  • Small area estimation is a statistical inference method to overcome the large variance due to the small sample size allocated in a small area. Recently some nonparametric estimators have been applied to small area estimation. In this study, we suggest a nonparametric mixed effect small area estimator using kernel smoothing and compare the small area estimators using labor statistics.

Credibility estimation via kernel mixed effects model

  • Shim, Joo-Yong;Kim, Tae-Yoon;Lee, Sang-Yeol;Hwa, Chang-Ha
    • Journal of the Korean Data and Information Science Society
    • /
    • v.20 no.2
    • /
    • pp.445-452
    • /
    • 2009
  • Credibility models are actuarial tools to distribute premiums fairly among a heterogeneous group of policyholders. Many existing credibility models can be expressed as special cases of linear mixed effects models. In this paper we propose a nonlinear credibility regression model by reforming the linear mixed effects model through kernel machine. The proposed model can be seen as prediction method applicable in any setting where repeated measures are made for subjects with different risk levels. Experimental results are then presented which indicate the performance of the proposed estimating procedure.

  • PDF

A Mixed-effects Height-Diameter Model for Pinus densiflora Trees in Gangwon Province, Korea

  • Lee, Young Jin;Coble, Dean W.;Pyo, Jung Kee;Kim, Sung Ho;Lee, Woo Kyun;Choi, Jung Kee
    • Journal of Korean Society of Forest Science
    • /
    • v.98 no.2
    • /
    • pp.178-182
    • /
    • 2009
  • A new mixed-effects model was developed that predicts individual-tree total height for Pinus densiflora trees in Gangwon province as a function of individual-tree diameter (cm). The mixed-effects model contains two random-effects parameters. Maximum likelihood estimation was used to fit the model to 560 height-diameter observations of individual trees measured throughout Gwangwon province in 2007 as part of the National Forest Inventory Program in Korea. The new model is an improvement over fixed-effects models because it can be calibrated to a local area, such as an inventory plot or individual stand. The new model also appears to be an improvement over the Forest Resources Evaluation and Prediction Program for the ten calibration trees used in this study. An example is provided that describes how to estimate the random-effects parameters using ten calibration trees.

A generalized logit model with mixed effects for categorical data (다가자료에 대한 혼합효과모형)

  • 최재성
    • The Korean Journal of Applied Statistics
    • /
    • v.15 no.1
    • /
    • pp.129-137
    • /
    • 2002
  • This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but considered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

Semiparametric and Nonparametric Mixed Effects Models for Small Area Estimation (비모수와 준모수 혼합모형을 이용한 소지역 추정)

  • Jeong, Seok-Oh;Shin, Key-Il
    • The Korean Journal of Applied Statistics
    • /
    • v.26 no.1
    • /
    • pp.71-79
    • /
    • 2013
  • Semiparametric and nonparametric small area estimations have been studied to overcome a large variance due to a small sample size allocated in a small area. In this study, we investigate semiparametric and nonparametric mixed effect small area estimators using penalized spline and kernel smoothing methods respectively and compare their performances using labor statistics.

A marginal logit mixed-effects model for repeated binary response data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
    • /
    • v.19 no.2
    • /
    • pp.413-420
    • /
    • 2008
  • This paper suggests a marginal logit mixed-effects for analyzing repeated binary response data. Since binary repeated measures are obtained over time from each subject, observations will have a certain covariance structure among them. As a plausible covariance structure, 1st order auto-regressive correlation structure is assumed for analyzing data. Generalized estimating equations(GEE) method is used for estimating fixed effects in the model.

  • PDF