• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.379-389
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• 2002

For two normal distribution with unknown means and unknown variances, a sequential procedure for estimating the difference of two normal means which satisfies both the coverage probability condition and the $\beta$-protection is proposed under some smoothness of variable imprecision function, and the asymptotic normality of the proposed stopping time after some centering and scaling is given.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.415-431
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• 2002

A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1069-1086
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• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.581-594
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• 2013

A group sequential design can end a clinical trial early if a confirmed efficacy or a futility of study medication is found during clinical trials. Adaptation can adjust the design of clinical trials based on accumulated data. The key to this methodology is considered to control the overall type 1 error rate while maintaining the integrity of clinical trials. The estimation would be more complex and the sample size calculation will be more difficult if the clinical trials have repeated measurement data. Lee et al. (2002) suggested a repeated observation case by using the independent increments properties of the interim test statistics and investigated the properties of the proposed confidence interval based on the stage-wise ordering. This study extend Lee et al. (2002) to adaptive group sequential design. We suggest test statistics for the adaptation as redesigning the second stage of clinical trials and induce the stage-wise confidence interval of parameter of interests. The simulation will help to confirm the suggested method.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.271-284
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• 2002

In this paper we consider the robust inference for the parameter of linear regression model based on weighted least squares. First we consider the sequential test of multiple outliers. Next we suggest the way to assign a weight to each observation $(x_i,\;y_i)$ and recommend the robust inference for linear model. Finally, to check the performance of confidence interval for the slope using proposed method, we conducted a Monte Carlo simulation and presented some numerical results and examples.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.65-82
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• 1996

This paper proposes a sequential procedure which can be used to determine a truncation point and run length to reduce or remove bias owing to artificial startup conditions in simulations aimed at estimating steady-state behavior. It is based on the idea of Lyapunov exponent in chaos theory. The performance measures considered are relative bias, coverage, estimated relative half-width of the confidence interval, and mean amount of deleted data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1099-1108
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• 2017

Data points obtained by conducting repetitive experiments under identical environmental conditions are, theoretically, required to correspond. However, experimental data often display variations due to generated errors or noise resulting from various factors and inherent uncertainties. In this study, an algorithm aiming to determine valid bounds of input variables, representing uncertainties, was developed using probabilistic and statistical methods. Furthermore, a reliability assessment was performed to verify and validate applications of this algorithm using bolt-fastening friction coefficient data in a sample application.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1051-1059
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• 1992

In this paper, two general methods using time-series analysis in the functional separation of the myoelectric signal of human arm movements are developed. Autocorrelation, covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation-out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squared error. With the error signals of autoregressive(AR) model, the result showed that the highest success rate was obtained in the case of 4th order, and success rate was decreased with increase of order. Autocorrelation was the method of choice for better success rate. This technique might be applied to biomedical and rehabilitation engineering.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.76-84
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• 1993

In this thesis, general method using autoregressive model in the functional separation of the myoelectric signal of human arm movements are suggested. Covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squares error. With the error signals of autoregressive(AR) model, the result showed that the highest success, rate was abtained in the case of 4th order, and success rate was decreased with increase of order. This technique might be applied to biomedical-and rehabilitation-engi-neering.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.28 no.2
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• pp.115-124
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• 2024

To compare the outcomes of low central venous pressure (CVP) to standard CVP during laparoscopic liver resection. The study design was a systematic review following the PRISMA statement standards. The available literature was searched to identify all studies comparing low CVP with standard CVP in patients undergoing laparoscopic liver resection. The outcomes included intraoperative blood loss (primary outcome), need for blood transfusion, mean arterial pressure, operative time, Pringle time, and total complications. Random-effects modelling was applied for analyses. Type I and type II errors were assessed by trial sequential analysis (TSA). A total of 8 studies including 682 patients were included (low CVP group, 342; standard CVP group, 340). Low CVP reduced intraoperative blood loss during laparoscopic liver resection (mean difference [MD], -193.49 mL; 95% confidence interval [CI], -339.86 to -47.12; p = 0.01). However, low CVP did not have any effect on blood transfusion requirement (odds ratio [OR], 0.54; 95% CI, 0.28-1.03; p = 0.06), mean arterial pressure (MD, -1.55 mm Hg; 95% CI, -3.85-0.75; p = 0.19), Pringle time (MD, -0.99 minutes; 95% CI, -5.82-3.84; p = 0.69), operative time (MD, -16.38 minutes; 95% CI, -36.68-3.39; p = 0.11), or total complications (OR, 1.92; 95% CI, 0.97-3.80; p = 0.06). TSA suggested that the meta-analysis for the primary outcome was not subject to type I or II errors. Low CVP may reduce intraoperative blood loss during laparoscopic liver resection (moderate certainty); however, this may not translate into shorter operative time, shorter Pringle time, or less need for blood transfusion. Randomized controlled trials with larger sample sizes will provide more robust evidence.