• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.200-201
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• 2005

• Genomics & Informatics
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• v.20 no.3
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• pp.34.1-34.11
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• 2022

Multilevel analysis is an appropriate and powerful tool for analyzing hierarchical structure data widely applied from public health to genomic data. In practice, however, we may lose the information on multiple nesting levels in the multilevel analysis since data may fail to capture all levels of hierarchy, or the top or intermediate levels of hierarchy are ignored in the analysis. In this study, we consider a multilevel linear mixed effect model (LMM) with single imputation that can involve all data hierarchy levels in the presence of missing top or intermediate-level clusters. We evaluate and compare the performance of a multilevel LMM with single imputation with other models ignoring the data hierarchy or missing intermediate-level clusters. To this end, we applied a multilevel LMM with single imputation and other models to hierarchically structured cohort data with some intermediate levels missing and to simulated data with various cluster sizes and missing rates of intermediate-level clusters. A thorough simulation study demonstrated that an LMM with single imputation estimates fixed coefficients and variance components of a multilevel model more accurately than other models ignoring data hierarchy or missing clusters in terms of mean squared error and coverage probability. In particular, when models ignoring data hierarchy or missing clusters were applied, the variance components of random effects were overestimated. We observed similar results from the analysis of hierarchically structured cohort data.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4042-4051
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• 2021

In this work, we applied a multilevel modeling technique to estimate the diametral creep in the pressure tubes of Korean Canada Deuterium Uranium (CANDU) units. Data accumulated from in-service inspections were used to develop the model. To confirm the strength of the multilevel models, a 2-level multilevel model considering the relationship between channels for a CANDU unit was compared with existing linear models. The multilevel model exhibited a very robust prediction accuracy compared to the linear models with different data pooling methods. A 3-level multilevel model, which considered individual bundles, channels, and units, was also implemented. The influence of the channel installation direction was incorporated into the three-stage multilevel model. For channels that were previously measured, the developed 3-level multilevel model exhibited a very good predictive power, and the prediction interval was very narrow. However, for channels that had never been measured before, the prediction interval widened considerably. This model can be sufficiently improved by the accumulation of more data and can be applied to other CANDU units.

• Analyses & Alternatives
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• v.5 no.1
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• pp.3-24
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• 2021

This paper introduces a multilevel item-response-theory (IRT) model as a unifying model for hypothesis testing using legislative voting data. This paper shows that a probit or logit model is a special type of multilevel IRT model. In particular, it is demonstrated that, when a probit or logit model is applied to multiple votes, it makes unrealistic assumptions and produces incorrect coefficient estimates. The advantages of a multilevel IRT model over a probit or logit model are illustrated with a Monte Carlo experiment and an example from the U.S. House. Finally, this paper provides a practical guide to fitting this model to legislative voting data.

• The Journal of Industrial Distribution & Business
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• v.10 no.6
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• pp.7-17
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• 2019

Purpose - The purpose of this study is to explore how advertising for multilevel marketing brands affect the salesperson's activity including customer-salesperson interactivity, work attitude, and perceived and actual performance after the campaign. Research Design, data, and methodology - This study collects experimental data, survey data, and actual sales data and applies statistical analyses such as factor analysis, t-tests, and a structural equation model. Results - The results show that advertising campaign can enhance a salesperson's selling activities and provide wide managerial implications to a multilevel marketing firm by filling the gaps for the field of advertising research. Conclusions - Managerial implications include: i) multilevel marketing firms should consider advertising campaigns as a means of changing customer responses because advertising plays a significant role in increasing familiarity with, and knowledge of, attitudes toward the brand, which also helps salespeople interact with customers; ii) multilevel marketing firms should consider brand advertising as a means to support the sales activities of salespeople including sales effectiveness, work attitudes, and perceived performance, and iii) multilevel marketing firms should consider brand advertising as a means to enhance a salesperson's pride and motivation for selling their brand, which will lead to improved sales performances.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2844-2853
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• 2023

A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.89-102
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• 2014

In this study, we analyze the effect on the smoking status in the Seoul Metropolitan area using a multilevel logistic model with Community Health Survey data from the Korea Centers for Disease Control and Prevention. Intraclass correlation coefficient (ICC), profiling analysis and two types of predicted value were used to determine the appropriate multilevel analysis level. Sensitivity, specificity, percentage of correctly classified observations (PCC) and ROC curve evaluated model performance. We showed the applicability for multilevel analysis allowed for the possibility that different factors contribute to within group and between group variability using survey data.

• The Korean Journal of Health Service Management
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• v.9 no.2
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• pp.81-88
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• 2015

The purpose of this study was to compare the risk-adjusted in-hospital mortality for craniotomies between logistic regression and multilevel analysis. By using patient sample data from the Health Insurance Review & Assessment Service, in-patients with a craniotomy were selected as the survey target. The sample data were collected from a total number of 2,335 patients from 90 hospitals. The sample data were analyzed with SAS 9.3. From the results of the existing logistic regression analysis and multilevel analysis, the values from the multilevel analysis represented a better model than that of logistic regression. The intra-class correlation (ICC) was 18.0%. It was found that risk-adjusted in-hospital mortality for craniotomies may vary in every hospital. The agreement by kappa coefficient between the two methods was good for the risk-adjusted in-hospital mortality for craniotomies, but the factors influencing the outcome for that were different.

• Journal of Sensor Science and Technology
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• v.25 no.2
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• pp.131-137
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• 2016

In this study, a multilevel visible light communication (VLC) system based on resistor ladder circuit is designed to transmit medical data. VLC technology is being considered as an alternative wireless communication due to various advantages such as ubiquity, license free operation, low energy consumption, and no radio frequency (RF) radiation characteristics. With VLC even in places where traditional RF communication (e.g., Wi-Fi) is forbidden, significant bio-medical signal including the electrocardiography (ECG) and photoplethysmography (PPG) data can be transmitted. More lives could be saved anywhere by this potential advantage of VLC with a fast emergency response time. A multilevel transmission scheme is adopted to improve the data capacity with keeping simplicity, where data transmission rate can increase by log2m times (m is the number of voltage levels) than that of conventional VLC transmission based on on/off keying. In order to generate multi-amplitudes, resistor ladder circuit, which is a basic principle of digital to analog convertor, is employed, and information is transferred through LED (Light-Emitting Diode) with different voltage level. In the receiver side, multilevel signal is detected by optical receiver including a photo diode. Then, the collected data are analyzed to serve the necessary medical care to the concerned patient.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.24-31
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• 2001

In this paper, we present an advanced transaction scheduling protocol to improve the degree of concurrency and satisfy the security requirements for multilevel secure database. We adapted two-phase locking protocol, namely traditional syntax-oriented serializability notions, to multilevel secure database. Altruistic locking, as an advanced protocol, has attempted to reduce delay effect associated with lock release moment by use of the idea of donation. An improved form of altruism has also been deployed for extended altruistic locking OffiLl. This is in a way that scope of data to be early released is enlarged to include even data initially not intended to be donated. We also adapted XAL to multilevel secure database and we first of all investigated limitations inherent in both altruistic schemes from the perspective of alleviating starvation occasions for transactions in particular of short-lived nature for multilevel secure database. Our protocol is based on extended altruistic locking for multilevel secure database (XAL/MLS), but a new method, namely two-way donation locking for multilevel secure database (2DL!/-MLS), is additionally used in order to satisfy security requirements and concurrency. The efficiency of the proposed protocol was verified by experimental results.