• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.85-104
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• 1997

Proportional hazards model has been widely used for analyzing survival data. This article reviews some well-known goodness-of-fit tests for proportional hazards model. Simulation studies also provide some insights into the properties of these test statistics across several types of survival distributions and degerees of censorship.

• Korean Management Science Review
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• v.19 no.2
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• pp.59-73
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• 2002

There have been academic debates upon which measure is more desirable in measuring service quality between SERVQUAL and SERVPERF In addition, Korean fast food industry is rapidly growing due to increasing income and globalization. Our study tried to contribute to both academic and practical issues. We compared SERVQUAL and SERVPERF measures to determine which one is superior to measure service quality in Korean fast food franchise. We collected data from two branch restaurants of one American global fast food franchise system. Regression analyses resulted in that SERVPERF outperformed SERVQUAL. Furthermore, we compared the goodness of fit of the two structural equation models of SERVQUAL anO SERVPERF, respectively. The SERVPERF model showed a much better model fit than the SERVQUAL model did. Thus, we suggest that SERVPERF be used to measure service quality in Korean fast food industry.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.673-683
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• 2012

Cabral et al. (2012) defined a mixture model of multivariate skew t-distributions(STMM), and proposed the use of an ECME algorithm (a variation of a standard EM algorithm) to fit the model. Their estimation by the ECME algorithm is closely related to the estimation of the degree of freedoms in the STMM. With the ECME, their purpose is to escape from the calculation of a conditional expectation that is not provided by a closed form; however, their estimates are quite unstable during the procedure of the ECME algorithm. In this paper, we provide a conditional expectation as a closed form so that it can be easily calculated; in addition, we propose to use the ECM algorithm in order to stably fit the STMM.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.197-212
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• 2002

When assessing goodness-of-fit of a model, a small subset of deviating observations can give rise to a significant lack of fit. It is therefore important to identify such observations and to assess their effects on various aspects of analysis. A Cook's distance measure is usually used to detect influential observation. But it sometimes is not fully effective in identifying truly influential set of observations because there may exist masking or swamping effects. In this paper we confine our attention to influential subset In GLMs such as logistic regression models and loglinear models. We modify a backwards stepping algorithm, which was originally suggested for detecting outlying cells in contingency tables, to detect influential observations in GLMs. The algorithm consists of two steps, the identification step and the testing step. In identification step we Identify influential observations based on influencial measures such as Cook's distances. On the other hand in testing step we test the subset of identified observations to be significant or not Finally we explain the proposed method through two types of dataset related to logistic regression model and loglinear model, respectively.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.651-659
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• 2012

In this paper we developed a statistical model for circular data with noises. In this case, model fitting by single circular model has a lack-of-fit problem. To overcome this problem, we consider some mixture models that include circular uniform distribution and apply an EM algorithm to estimate the parameters. Both von Mises and Wrapped skew normal distributions are considered in this paper. Simulation studies are executed to assess the suggested EM algorithms. Finally, we applied the suggested method to fit 2008 EHFRS(Epidemic Hemorrhagic Fever with Renal Syndrome) data provided by the KCDC(Korea Centers for Disease Control and Prevention).

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.3
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• pp.656-671
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• 2015

The purpose of the present study is to examine relationships between disconnection and rejection schema, defense mechanism, and mental health in college students using structural equation modeling. The present study suggested a proposed model in which defense mechanism exerted a full mediating effect on the relation between disconnection and rejection schema and mental health. Goodness of fit tests were used to compare the proposed model against competing models. The subjects consisted of 304 college students. They completed the Young Schema Questionnaire(YSQ-SF), the Defense Style Questionnaire(DSQ), and the Mental Health Scale. The results showed that the second model had a better goodness of fit. Based on these findings, it is suggested that psychological interventions for mental health in college students should consider strategies to use more flexible and more adaptive defense mechanism style.

• International Journal of Costume and Fashion
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• v.18 no.2
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• pp.45-64
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• 2018

This study assessed scuba divers' wetsuit selection criteria based on the gender, age and scuba diving commitment level along with identifying currently owned and preferred wetsuit types. Lamb and Kallal's Functional, Expressive, and Aesthetic Consumer Needs (FEA) Model was the conceptual framework used for this study. Scuba diving has seen consistent growth, worldwide, it is necessary to investigate with wetsuit needs of this consumer group. A survey of 302 active scuba divers participated in the study. Total participants included 202 male and 100 female scuba divers. Divers stated fit was the most highly rated criteria with don/doff being most problematic. Female and older divers regarded functional performance criterion greatly(p<.05). Highly committed divers regarded the functional quality (p<.01) and aesthetic/expressive features (p<.05) of the wetsuit as important and owned more wetsuits(p<.01). Gender saw differences in required sizes ranges(p<.001) and style preferences(p<.05). Results suggest gender, age, and commitment levels all impact the wetsuit selection criteria of scuba divers.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.1-25
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• 2022

A modified Bagdonavičius-Nikulin chi-square goodness-of-fit is defined and studied. The lymphoma data is analyzed using the modified goodness-of-fit test statistic. Different non-Bayesian estimation methods under complete samples schemes are considered, discussed and compared such as the maximum likelihood least square estimation method, the Cramer-von Mises estimation method, the weighted least square estimation method, the left tail-Anderson Darling estimation method and the right tail Anderson Darling estimation method. Numerical simulation studies are performed for comparing these estimation methods. The potentiality of the new model is illustrated using three real data sets and compared with many other well-known generalizations.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.49-63
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• 2023

A lot of studies on the summary measures of predictive strength of categorical response models consider the likelihood ratio index (LRI), also known as the McFadden-R², a better option than many other measures. We propose a simple modification of the LRI that adjusts for the effect of the number of response categories on the measure and that also rescales its values, mimicking an underlying latent measure. The modified measure is applicable to both binary and ordinal response models fitted by maximum likelihood. Results from simulation studies and a real data example on the olfactory perception of boar taint show that the proposed measure outperforms most of the widely used goodness-of-fit measures for binary and ordinal models. The proposed R² interestingly proves quite invariant to an increasing number of response categories of an ordinal model.

• Journal of Information Technology Applications and Management
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• v.29 no.5
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• pp.13-25
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• 2022

The purpose of this study is to explore the factors that influence the purchase of AI speakers in China. We integrate the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-technology fit (TTF) model into one model and put forward assumptions. According to the characteristics of AI speakers, we selected 6 independent variables, such as Performance Expectation, Effort Expectation, Social Influence, Facilitating Conditions, Task and Technology-characteristics. The final impact on purchase behavior is evaluated through Task-technology fit and purchase intention. After counting 478 samples, through SPSS22.0 and AMOS analysis, hypotheses have been proved by strong experimental data, except facilitating conditions. These results also imply that improving the technical level of AI speakers and enhancing consumers' purchasing intention are the central line of marketing. Based on this, we put forward several suggestions to marketers, including strengthening the research and development of AI speaker technology, and building a circle of friends of AI speakers.