Browsing by Author "Jane, Ten-Der"

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A systematic approach for identifying level-1 error covariance structures in latent growth modeling
(2017-05-01)
Ding, Cherng G.
;
Jane, Ten-Der
;
Wu, Chiu-Hui
;
Lin, Hang-Rung
;
Shen, Chih-Kang
It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which, however, is not systematically addressed in the literature. In this study, we first discuss characteristics of various covariance structures and their nested relations, based on which we then propose a systematic approach to facilitate identifying a plausible covariance structure. A test for stationarity of an error process and the sequential chi-square difference test are conducted in the approach. Preliminary simulation results indicate that the approach performs well when sample size is large enough. The approach is illustrated with empirical data. We recommend that the approach be used in LGM empirical studies to improve the quality of the specification of the error covariance structure.
Lessons from the global financial crisis for the semiconductor industry
(2015-10-01)
Wu, Chiu-Hui
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Ding, Cherng G.
;
Jane, Ten-Der
;
Lin, Hang-Rung
;
Wu, Cheng-Ying
During the global financial crisis in 2008, governments around the world have used a variety of policies to support threatened industries and to stabilize financial systems. In the present study, we empirically compare the patterns of the dynamic change in the financial performance of the semiconductor industry before and after government intervention by using the piecewise linear trajectory model for Japan, South Korea and Taiwan, three major economies for the industry. The empirical results indicate that during the global financial crisis, the performance of the semiconductor industry can benefit from government support, in spite of the fact that the improvement was somewhat delayed after intervention. Moreover, the change pattern of the performance depends on the performance factor and the economy. Based on the results obtained as well as literature support, we summarize the economic and industrial policies that might have demonstrated usefulness for the industry and discuss some implications. (C) 2015 Elsevier Inc. All rights reserved.
On the multivariate EGARCH model
(2009)
Jane, Ten-Der
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Ding, Cherng G.
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經營管理研究所
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Institute of Business and Management
In this aticle, the extension of Nelson's (1991) univariate EGARCH model to the multivariate version has been reexamined and compared with the existing one given by Koutmos and Booth (1995). The magnitude and sign of standardized innovations have been constrained in Koutmos and Booth's multivariate EGARCH model, but not in the actual multivariate EGARCH model. The constraints imposed on Koutmos and Booth's EGARCH model may lead to inaccurate parameter estimates. Since the actual multivariate EGARCH model obtained is more general, and can produce more accurate inferential results, we suggest that the actual multivariate EGARCH model be used in future financial empirical studies.
On the reliability, consistency, and method-specificity based on the CT-C(M-1) model
(2012-06-01)
Ding, Cherng G.
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Jane, Ten-Der
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經營管理研究所
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Institute of Business and Management
In the present study, we discuss reliability, consistency, and method specificity based on the CT-C(M-1) model, which provides clear definitions of trait and method factors and can facilitate parameter estimation. Properties of the reliability coefficient, the consistency coefficient, and the method-specificity coefficient of the summated score for a trait factor are addressed. The consistency coefficient and the method-specificity coefficient are both functions of the number of items, the average item consistency, and the average item method specificity. The usefulness of the findings is demonstrated in an alternative approach proposed for scale reduction. The approach, taking into account both traits and methods, helps identify the items leading to the maximum of convergent validity or method effects. The approach, illustrated with a simulated data set, is recommended for scale development based on multitrait-multimethod designs.
Using LGM analysis to identify hidden contributors to risk in the operation of a nuclear power plant
(2015-06-01)
Ding, Cherng G.
;
Lin, Hang-Rung
;
Wu, Chiu-Hui
;
Jane, Ten-Der
;
經營管理研究所
In this study, an approach is proposed to identify hidden contributors to risk in the operation of a nuclear power plant. Hypotheses linking safety performance to its influential factors are developed based on theory and literature. The failure to support the relational hypotheses with longitudinal safety performance data from a plant signifies hidden contributors to risk in the operation of the plant, which can be specifically identified by looking into the empirical results inconsistent with theoretical expectations. To demonstrate the use of the approach, we develop five hypotheses and analyze the longitudinal failure data for 28 years collected from 342 pumps in a large nuclear power plant by using latent growth modeling (LGM). The average trajectory of pump failures for the entire plant is inverted-U-shaped. Four hidden risk contributors in the operation of the sample plant have been identified. We suggest that, in addition to the adequacy of training and safety management systems, crew resource management be used to enhance nuclear safety for the sample plant. We recommend that the proposed approach be used for any other nuclear power plant to help identify hidden risk contributors and in other similar situations. (C) 2015 Elsevier Ltd. All rights reserved.
Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models
(2012-09-01)
Ding, Cherng G.
;
Jane, Ten-Der
;
經營管理研究所
;
Institute of Business and Management
In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.