• Asia pacific journal of information systems
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• v.19 no.4
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• pp.47-75
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• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• Journal of ILASS-Korea
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• v.21 no.4
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• pp.207-213
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• 2016

To protect air pollution of urban area from motor vehicles, emission limits for diesel vehicles have been dramatically lowered in short period. But recent studies have shown that on-road NOx emissions of light-duty diesel vehicles are considerably higher than the values measured with laboratory test procedures used for emission certification. To tackle with this issue, Ministry of Environment have a plan to introduce EU RDE-LDV (Real-driving Emission-Light-duty Vehicle) regulation. In this study, 4 Euro 6 diesel vehicles have been tested with the new test procedures published by EU to estimate on-road NOx emissions using PEMS (Portable Emission Measurement System). The results have shown that the requirements of EU RDE-LDV could be met in driving condition of metropolitan area for constitution of test routes and validity of test results. In analysing with Moving Averaging Window method the completeness and normality of test data were validated with the requirement. On-road NOx emissions were quite deviated as test vehicles and higher than the new limit of on-road NOx emission enforced from Sept. 2017, which means that RDE-LDV can effectively reduce NOx emission of diesel vehicles in real driving conditions of Korea.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.507-516
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• 2018

Widely used among the various single imputation methods is k-nearest neighbors (KNN) imputation due to its robustness even when a parametric model such as multivariate normality is not satisfied. We propose a weighted adaptive nearest neighbors imputation method that combines the adaptive nearest neighbors imputation method that accounts for the local features of the data in the KNN imputation method and weighted k-nearest neighbors method that are less sensitive to extreme value or outlier among k-nearest neighbors. We conducted a Monte Carlo simulation study to compare the performance of the proposed imputation method with previous imputation methods.

• Child Health Nursing Research
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• v.11 no.2
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• pp.179-188
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• 2005

Purpose: This study was conducted to analyze the discourse of puberty in the early teenage girls. Method: The participants were 24, 11-15years old girls who were interviewed in face-to-face using a semi-structured questionnaire. The interviews were done between October 29 and December 27 2003. Analysis of the qualitative data was done in 2 steps. Results: First, the theme of the girls' puberty discourse was identifying normality and consisted of 5 categories : i) defining puberty as experiencing changes, ⅱ) acknowledging their own puberty connecting it with their definitions of puberty, ⅲ) selectively excluding/recognizing the actual pubertal changes by seeing themselves as nonsexual and negative beings, ⅳ) recognizing the pubertal changes as becoming women and making them not peculiar but normal, and ⅴ) sharing the knowledge and experience of change inactively and exclusively and resisting the dominant discourse. Three main discourse frames, marking off sexual/nonsexual, man/women, and major/minor were revealed in the second step of the analysis. They were intricately woven with each other and converged on sex. Conclusion: The girls posited themselves as being asexual, unstable, and marginal. So there is a need to help them recognize their pubertal state as physical and mental paradigmatic changes and assure their pubertal changes as positive.

• The Korean Journal of Pain
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• v.30 no.4
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• pp.243-249
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• 2017

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.49-58
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• 2020

This paper examines the impact of mergers on the financial performance of the Jordanian banking sector. This paper applies the financial approaches in analysing the effects of mergers on Jordanian banks' performance for two the periods: four years pre-merger and four years' post-merger for the period from 2001 to 2009. The sample of the study solely contains the case of the merger of the Jordan Ahli Bank (AHLI bank) with Philadelphia Bank in 2005. Data are tested for normality using the Shapiro-Wilk Test and Kolmogorov Smirnov test. The financial ratios and a statistical technique as a Mann-Whitney U test were used to assess the significant differences in the financial performance of the selected banks pre- and post-merger by investigating the performance-related financial ratio groups that are expressed by leverage, liquidity, efficiency, and cash flow ratio. The results show that there is an insignificant improvement in the ratios of AHLI bank in the period after the merger, except for the superior result provided by this study indicating that the leverage ratios improved significantly. The reason for the insignificant improvement in financial ratios may be that the post-merger period corresponds to the period of the global financial crisis that began in 2007.

• The Mathematical Education
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• v.45 no.2 s.113
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• pp.145-154
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• 2006

The main purpose of this study is to investigate the effect of departures from normality and equal variance on the two-sample test when the variances are unknown. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. But the change of type I error was mainly based on the skewness of the parent population. In introductory statistics classes where data analysis includes techniques for detecting skewness of two populations, we recommend the two-sample t-test when maximal skewness of two populations is smalter than the value 4 when the variances seem equal. Furthermore, our simulations reveal that the two-sample t-test appears somewhat more robust than that of z-test if the assumption of equal variance is satisfied. In the case of unequal variance, the two-sample t-test appears somewhat more robust provided the t-statistic using Satterthwaite's approximate degrees of freedom.

• Journal of Distribution Science
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• v.17 no.3
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• pp.5-19
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• 2019

Purpose - The purpose of this research is to investigate the factors contributing to sustainable competitive advantage for multi-level marketing (MLM) firms in Malaysia. The selected variables in this study are company image, product innovation, leadership, distributor rewards system and distributor training system. Research design, data, and methodology - Quantitative research method is employed with collected sample size of 398 respondents using judgmental sampling technique. Normality and reliability test were performed in the first stage utilizing SPSS 22 and Confirmatory Factory Analysis (CFA) and variance analysis were obtained in the subsequent stage, following up with the overall fit of the measurement model, Structural Equation Model (SEM) using AMOS 22 with maximum likelihood estimation to assess the internal consistency, convergent validity and discriminant validity. Results - The research findings show that company image, leadership, distributor rewards system and distributor training system were supported and are factors affecting the sustainable competitive advantage of MLM companies in Malaysia. However, in this study, product innovation was not supported but this result does not depict that it is trivial and inconsequential in maintain sustainable advantage. Conclusion - Companies can build sustainable competitive advantage by focusing on these contributing factors. Several other comments and implications were brought to light and discussed in the paper.

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.6
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• pp.3-10
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• 2017

The efforts for sustainable development in building construction is widely applied by global organizations, governments, etc. However, according to the researchers, if the green rating systems on the building, it is reported that construction costs and durations are increased compared to conventional buildings. In this respect, the objective of this study is to identify the construction costs between LEED and non-LEED buildings. The scope of this study is limited in 21 university buildings of Canada. The methodology is as follows: First, the data of LEED and non-LEED buildings are collected in every university building. Second, the average construction costs per square meter is collected and normality check is conducted. Third, to identify statistical significance, the difference of average construction costs is analyzed by using T-test. As a result, it is concluded that the construction costs of LEED buildings are increased by approximately 3.8% more than non-LEED buildings. In the future, the results of this study can be applied to analyzing the additional costs according to the LEED grade in educational buildings.

• Women's Health Nursing
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• v.18 no.2
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• pp.135-148
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• 2012

Purpose: The purpose of this study was to explore the meanings of 'Natural childbirth' from experiences of Korean women who gave birth to a baby in the midwifery using a feminist approach. Methods: This paper is a qualitative research study and applies a feminist epistemology and methodology to the experiences of women who gave birth in midwifery. The data were collected by individual in-depth interviews with eleven participants. Results: Two main themes emerged from the feminist content analyses and each main theme had three sub themes. A. transformation of control and knowledge on childbirth and the body 1) refusing coercive medicalization and building a new normality, 2) specific expectations about biological health and maternity rather than a return to nature, 3) the subject of pregnancy and childbirth, B. 'natural childbirth' practice as a new embodied discipline 1) helpers to support mothers, midwives, 2) helping the body to do 'natural childbirth', 3) from isolated labor to cooperative reproduction. Conclusion: These results indicate that women desired to practice being a subject, consultation with professionals, self-discipline and named actors except for women as 'other subjects' in childbirth.