• Title/Summary/Keyword: mixed-effects.

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Mixed-effects LS-SVR for longitudinal dat

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.363-369
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    • 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.

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
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    • v.28 no.2
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    • pp.361-369
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    • 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.

A Cumulative Logit Mixed Model for Ordered Response Data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.123-130
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    • 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.

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A Comparison of Influence Diagnostics in Linear Mixed Models

  • Lee, Jang-Taek
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.125-134
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    • 2003
  • Standard estimation methods for linear mixed models are sensitive to influential observations. However, tools and concepts for linear mixed model diagnostics are rudimentary until now and research is heavily demanded in linear mixed models. In this paper, we consider two diagnostics to evaluate the effects of individual observations in the estimation of fixed effects for linear mixed models. Those are Cook's distance and COVRATIO. Results of our limited simulation study suggest that the Cook's distance is not good statistical quantity in linear mixed models. Also calibration point for COVRATIO seems to be quite conservative.

Mode effects in concurrent mixed-mode surveys (병행적 혼합조사의 모드효과 분석)

  • Baek, Jeeseon;Min, Kyung A
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.787-806
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    • 2016
  • Mixed-mode (MM) designs in which data are collected by different modes in one design have become increasingly popular. An MM data collection has several advantages such as reductions of coverage error, non-response and cost. However, MM designs may introduce mode effects that are confounded by selection effects and measurement effects, which can make MM data quality poor. In order to investigate mode effects, SRI implemented a concurrent mixed-mode experiment in 2014 where respondents could choose between a self-administrated Web survey and a self-administrated paper survey. This paper separately estimates selection effects and measurement effects. We found that measurement effects on some items are large.

Small Area Estimation via Nonparametric Mixed Effects Model

  • Jeong, Seok-Oh;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.25 no.3
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    • pp.457-464
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    • 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.

Effects of Aluminum and Silicon as Additive Materials for the Zinc Anode in Zn-Air Batteries

  • Lee, Yong-Seok;Ryu, Kwang-Sun
    • Journal of the Korean Electrochemical Society
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    • v.21 no.1
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    • pp.12-20
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    • 2018
  • To solve low cycle efficiency of the zinc anode in Zn-air batteries by corrosion, this study examined the effects of Al as a cathodic protection additive to Zn. The Al-mixed Zn anodes were produced by mixing Zn and Al powder (1, 2, and 3 wt. %). To compare the effects of the Al additive, Si was selected under the same conditions. The morphology and elemental composition of the additives in the Zn were characterized by scanning electron microscopy, energy dispersive X-ray spectroscopy, and inductively coupled plasma - mass spectrometry. The anti-corrosion effects of the Al and Si-mixed Zn anodes were examined by linear polarization. Cyclic voltammetry and charge-discharge tests were conducted to evaluate the electrochemical performance of the Al and Si-mixed Zn anodes. As a result, the Al-mixed Zn anodes showed highest corrosion resistance and cycling performance. Among these, the 2 wt.% Al-mixed Zn anodes exhibited best electrochemical performance.

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
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    • v.26 no.1
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    • pp.71-79
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    • 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.

THE EFFECTS OF sAMUTANG AND Samultang-Mixed-Kamibulhwangumjungkisan on the recovery of exercise induced fatigue (사물탕 및 사물탕합가비불환금정기산이 흰 주의 운동 피로 회복에 미치는 경향)

  • 박연용;박동일
    • Journal of Life Science
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    • v.8 no.3
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    • pp.241-248
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    • 1998
  • In an attempt to investigate the effects of Samultang, Samultang-Mixed-Kamibulhwangumjungkisan extract on the ability of rat to recover from exhaustion after severe exercise. The results are as follows 1. Lactate was found to show remarkable decrease in the rat with administration of Samultang-Mixed-Kamibulhwangumjungkisan group at 120 min (p<0.001). 2. LDH showed elevation in the rat with administration of Samultang-Mixed-Kamibulhwangumjungkisan group 120 min.(p<0.05) 3. Glucose showed elevation in the rat with administration of Samultang-Mixed-Kamibulhwangumjungkisan group at 120 min.(p<0.05) 4. FFA showed decrease in the rat with adminstration of Samultang-Mixed-Kamibulhwangumjungkisan hroup at 120min.(p<0.05) From these results, we recoginized that the effects of Samul-tangmixedKamiBulhwangumjungkisan group is better than Samultang group on the recovery of exercise induced fatigue.

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A Proportional Odds Mixed - Effects Model for Ordinal Data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.471-479
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    • 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.

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