• Title/Summary/Keyword: ordered data

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A Mixed Model for Oredered Response Categories

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.339-345
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    • 2004
  • This paper deals with a mixed logit model for ordered polytomous data. There are two types of factors affecting the response varable in this paper. One is a fixed factor with finite quantitative levels and the other is a random factor coming from an experimental structure such as a randomized complete block design. It is discussed how to set up the model for analyzing ordered polytomous data and illustrated how to estimate the paramers in the given model.

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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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Estimation for ordered means in normal distributions

  • Cho, Kil-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.5
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    • pp.951-958
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    • 2010
  • In this paper, we obtain the restricted maximum likelihood estimators (RMLE's) for means in normal distributions with the ordered mean constraints. The biases and mean squared errors (MSE's) of these RMLE's are approximated by Mote Carlo methods. In every case a substantial savings in MSE is obtained at the expense of a small loss in bias when using RMLE's instead of the unrestricted MLE's.

An Evaluation Study of the Practical Application of Preceptorship in an Ordered Elective Clinical Nursing Practice (실습지도자를 활용(preceptorship)한 주문식 선택실습의 평가연구)

  • Kim Chung-Youb
    • Journal of Korean Academy of Fundamentals of Nursing
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    • v.12 no.2
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    • pp.195-205
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    • 2005
  • Purpose: This study was done to use preceptorship in an ordered elective clinical nursing practice and to evaluate the effects on student nurses, nurses managers and preceptors. Method: The participants in this study were 208 students who were majors in the department of nursing, G college located in Inchon Metropolitan City, 54 nurse managers and 187 preceptors from 11 general hospitals. The instrument was a questionnaire which included general characteristics of participants, and 21 items to evaluate the ordered elective clinical nursing practice on a scale of 1 to 4. Data were collected from October 23 to November 7. 2004. Data analysis was done using SPSS WIN with the following statistics: frequency, percentage, mean, standard deviation, and ANOVA. Results and Conclusions: The results of data analysis were as follows: There were meaningful differences in the evaluation scores of the ordered elective clinical nursing practice with preceptors between students ($3.33{\pm}.39$) and nurse managers ($3.33{\pm}.28$) and preceptors ($3.23{\pm}.38$). Evaluation scores for the ordered elective clinical nursing practice with preceptors were categorized as follows: necessity and appropriateness, practice control and management, material for practice, practice report assignment and evaluation, practice ability improvement and connection with getting a job, and contribution to the hospitals.

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Korean Welfare Panel Data: A Computational Bayesian Method for Ordered Probit Random Effects Models

  • Lee, Hyejin;Kyung, Minjung
    • Communications for Statistical Applications and Methods
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    • v.21 no.1
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    • pp.45-60
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    • 2014
  • We introduce a MCMC sampling for a generalized linear normal random effects model with the ordered probit link function based on latent variables from suitable truncated normal distribution. Such models have proven useful in practice and we have observed numerically reasonable results in the estimation of fixed effects when the random effect term is provided. Applications that utilize Korean Welfare Panel Study data can be difficult to model; subsequently, we find that an ordered probit model with the random effects leads to an improved analyses with more accurate and precise inferences.

An Adaptive Test for Ordered Interqartile Ranges among Several Distributions

  • Park, Chul-Gyu
    • Journal of the Korean Statistical Society
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    • v.30 no.1
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    • pp.63-76
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    • 2001
  • An adaptive estimation and testing method is proposed for comparing dispersions among several ordered groups. Based upon the large sampling theory for nonparametric quartile estimators, we derive the order restricted estimators and construct a simple test statistic. This test statistic has a mixture of several chi-square distributions as its asymptotic null distribution. The proposed test is illustratively applied to survival time data for the patients with carcinoma of the oropharynx.

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A Study on Comparison with the Methods of Ordered Categorical Data of Analysis (순서 범주형 자료해석법의 비교 연구)

  • 김홍준;송서일
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.44
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    • pp.207-215
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    • 1997
  • This paper deals with a comparison between Taguchi's accumulation analysis method and Nair test on the ordered categorical data from an industrial experiment for quality improvement. a result of Taguchi's accumulation analysis method is shown to have reasonable power for detecting location effects, while Nair test identifies the location and dispersion effects separately, Accordingly, Taguchi's accumulation analysis needs to develop methods for detecting dispersion effects as well as location effects. In addition this paper rewmmends models for analyzing ordered categorical data, for examples, the cumulative legit model, mean response model etc Successively simple, reasonable methods should be introduced more likely to be used by the practitioners.

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Power Comparison of Independence Test for the Farlie-Gumbel-Morgenstern Family

  • Amini, M.;Jabbari, H.;Mohtashami Borzadaran, G.R.;Azadbakhsh, M.
    • Communications for Statistical Applications and Methods
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    • v.17 no.4
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    • pp.493-505
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    • 2010
  • Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

Development of Analysis Method of Ordered Categorical Data for Optimal Parameter Design (순차 범주형 데이타의 최적 모수 설계를 위한 분석법 개발)

  • Jeon, Tae-Jun;Park, Ho-Il;Hong, Nam-Pyo;Choe, Seong-Jo
    • Journal of Korean Institute of Industrial Engineers
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    • v.20 no.1
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    • pp.27-38
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    • 1994
  • Accumulation analysis is difficult to analyze the ordered categorical data except smaller-the-better type problem. The purpose of this paper is to develop the statistic and method that can be easily applied to general type of problem, including nominal-the-best type problem. The experimental data of contact window process is analyzed and new procedure is compared with accumulation analysis.

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Sensitivity Analysis for Ordered Categorical Data

  • Cho, Il-Hyun;Park, Taesung
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.375-382
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    • 1999
  • Linear-by-linear association models are commonly used to analyze ordered categorical data. To fit these models appropriate scores need to be chosen. In this paper we perform sensitivity analyses in two-way contingency tables to investigate the effect of scores on goodness-of-fits and on tests of significance. In addition we show that the best score which yields the best fit of data can be selected based on the sensitivity analysis results.

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