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Search Results: 1 - 10 of 22294 matches for " Jae Kwang Kim "
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 Jae Kwang Kim Mathematics , 2004, DOI: 10.1214/009053604000000175 Abstract: Finite sample properties of multiple imputation estimators under the linear regression model are studied. The exact bias of the multiple imputation variance estimator is presented. A method of reducing the bias is presented and simulation is used to make comparisons. We also show that the suggested method can be used for a general class of linear estimators.
 Statistics , 2015, Abstract: Multiple imputation is a popular imputation method for general purpose estimation. Rubin(1987) provided an easily applicable formula for the variance estimation of multiple imputation. However, the validity of the multiple imputation inference requires the congeniality condition of Meng(1994), which is not necessarily satisfied for method of moments estimation. This paper presents the asymptotic bias of Rubin's variance estimator when the method of moments estimator is used as a complete-sample estimator in the multiple imputation procedure. A new variance estimator based on over-imputation is proposed to provide asymptotically valid inference for method of moments estimation.
 Statistics , 2015, Abstract: Fractional imputation (FI) is a relatively new method of imputation for handling item nonresponse in survey sampling. In FI, several imputed values with their fractional weights are created for each missing item. Each fractional weight represents the conditional probability of the imputed value given the observed data, and the parameters in the conditional probabilities are often computed by an iterative method such as EM algorithm. The underlying model for FI can be fully parametric, semiparametric, or nonparametric, depending on plausibility of assumptions and the data structure. In this paper, we give an overview of FI, introduce key ideas and methods to readers who are new to the FI literature, and highlight some new development. We also provide guidance on practical implementation of FI and valid inferential tools after imputation. We demonstrate the empirical performance of FI with respect to multiple imputation using a pseudo finite population generated from a sample in Monthly Retail Trade Survey in US Census Bureau.
 Statistics , 2014, DOI: 10.1214/14-AOAS746 Abstract: Self-selected samples are frequently obtained due to different levels of survey participation propensity of the survey individuals. When the survey participation is related to the survey topic of interest, propensity score weighting adjustment using auxiliary information may lead to biased estimation. In this paper, we consider a parametric model for the response probability that includes the study variable itself in the covariates of the model and proposes a novel application of two-phase sampling to estimate the parameters of the propensity model. The proposed method includes an experiment in which data are collected again from a subset of the original self-selected sample. With this two-phase sampling experiment, we can estimate the parameters in a propensity score model consistently. Then the propensity score adjustment can be applied to the self-selected sample to estimate the population parameters. Sensitivity of the selection model assumption is investigated from two limited simulation studies. The proposed method is applied to the 2012 Iowa Caucus Survey.
 Journal of Biomedical Science and Engineering (JBiSE) , 2015, DOI: 10.4236/jbise.2015.810063 Abstract: Abdominal obesity describes the accumulation of excessive fat in the abdomen. It is known that depending on its distribution, visceral obesity presents a greater danger to health than subcutaneous obesity. To properly prevent and treat visceral obesity, accurate evaluation methods are necessary, and hence quantitative VAT estimation is extremely important. CT scans are the most accurate method for estimating VAT, but it requires a great deal of time and effort, limiting its use in studying or evaluating obesity in patients. This paper proposed automatic measurement software that could quickly differentiate between and measure VAT and SAT. The method was verified using a total of 100 abdominal CT data values; this paper measured the SAT and VAT in the entire abdomen using the automatic measurement software. Additionally, through a comparative evaluation between the automated measurements and manual measurements such as BMI and waist circumference, clinical reliability and viability were validated and evaluated. Between automated measurements and manual measurements, the TAT (r = 0.995, p = 0.01), SAT (r = 0.987, p = 0.01) and VAT (r = 0.993, p = 0.01) showed high correlation. Using BMI as the main metric, the TAT for automated measurements (r = 0.674, p = 0.01) and the TAT for manual measurements (r = 0.703, p = 0.01) showed the strongest correlation. When using waist circumference, the VAT for automated measurements (r = 0.826, p = 0.01) and the VAT for manual measurements (r = 0.822, p = 0.01) showed the strongest correlation. With these results, the reliability and viability of the automatic measurement software were confirmed. The software is expected to help greatly in reducing the time and in providing objective data of VAT measurements from CT scans for clinical research.
 Advances in Chemical Engineering and Science (ACES) , 2014, DOI: 10.4236/aces.2014.44046 Abstract: Heat transfer and bubble phenomena were investigated by adopting the drift flux model in a viscous slurry bubble column reactor (SBCR), having a diameter of 0.0508 m(ID) and height 1.5 m. The effects of superficial gas velocity (0.002 -0.164 m/s), solid concentration (0 - 20 wt%) and liquid viscosity (paraffin oil; 16.9 mPa•s and squalane; 25.9 mPa•s) on the gas holdup and heat transfer characteristics were examined. It was observed that the gas holdup increased with increasing superficial gas velocity (UG), but decreased with increasing solid concentration (SC) or slurry viscosity. The degree of non-uniformity in a SBCR could be determined by the modified drift flux model at the heterogeneous flow regime. The local heat transfer coefficient (h) between the immersed heater and the bed decreased with increasing liquid viscosity and SC, but it increased with increasing UG. The modified Nusselt number including the gas holdup and local heat transfer coefficient was well correlated in terms of dimensionless groups such as Reynolds and Prandtl numbers.
 World Journal of Gastroenterology , 2012, DOI: 10.3748/wjg.v18.i15.1840 Abstract: Hereditary hemorrhagic telangiectasia (HHT) is a rare autosomal-dominantly inherited disease that occurs in approximately one in 5000 to 8000 people. Clinical diagnosis of HHT is made when a person presents three of the following four criteria: family history, recurrent nosebleeds, mucocutaneous telangiectasis, and arteriovenous malformations (AVM) in the brain, lung, liver and gastrointestinal (GI) tract. Although epistaxis is the most common presenting symptom, AVMs affecting the lungs, brain and GI tract provoke a more serious outcome. Heterozygous mutations in endoglin, activin receptor-like kinase 1 (ACVRL1; ALK1), and SMAD4, the genes involved in the transforming growth factor-β family signaling cascade, cause HHT. We report here the case of a 63 year-old male patient who presented melena and GI bleeding episodes, proven to be caused by bleeding from multiple gastric angiodysplasia. Esophagogastroduodenoscopy revealed multiple angiodysplasia throughout the stomach. Endoscopic argon plasma coagulation was performed to control bleeding from a gastric angiodysplasia. The patient has been admitted several times with episodes of hemoptysis and hematochezia. One year ago, the patient was hospitalized due to right-sided weakness, which was caused by left basal ganglia hemorrhage as the part of HHT presentation. In family history, the patient’s mother and elder sister had died, due to intracranial hemorrhage, and his eldest son has been suffered from recurrent epistaxis for 20 years. A genetic study revealed a mutation in exon 3 of ALK1 (c.199C > T; p.Arg67Trp) in the proband and his eldest son presenting epistaxis.
 World Journal of Gastroenterology , 2011, DOI: 10.3748/wjg.v17.i21.2611 Abstract: The high incidence of gastric cancer has led to the initiation of cancer screening programs. As a result, the number of early gastric cancer cases has increased and consequentially, the cancer mortality rate has decreased. Moreover, the development of minimally invasive endoscopic treatment has been introduced for these early lesions. Endoscopic submucosal dissection (ESD) is now recognized as one of the preferred treatment modalities for premalignant gastrointestinal epithelial lesions and early gastric cancer without lymph node metastasis. We review the results of ESD including experiences in Japan and Korea, as well as western countries.
 Statistics , 2011, DOI: 10.1214/10-AOAS419 Abstract: Variance estimation for estimators of state, county, and school district quantities derived from the Census 2000 long form are discussed. The variance estimator must account for (1) uncertainty due to imputation, and (2) raking to census population controls. An imputation procedure that imputes more than one value for each missing item using donors that are neighbors is described and the procedure using two nearest neighbors is applied to the Census long form. The Kim and Fuller [Biometrika 91 (2004) 559--578] method for variance estimation under fractional hot deck imputation is adapted for application to the long form data. Numerical results from the 2000 long form data are presented.
 Statistics , 2015, Abstract: Statistical matching is a technique for integrating two or more data sets when information available for matching records for individual participants across data sets is incomplete. Statistical matching can be viewed as a missing data problem where a researcher wants to perform a joint analysis of variables that are never jointly observed. A conditional independence assumption is often used to create imputed data for statistical matching. We consider an alternative approach to statistical matching without using the conditional independence assumption. We apply parametric fractional imputation of Kim (2011) to create imputed data using an instrumental variable assumption to identify the joint distribution. We also present variance estimators appropriate for the imputation procedure. We explain how the method applies directly to the analysis of data from split questionnaire designs and measurement error models.
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