Browsing by Author "Wang, Hsiuying"

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A control chart for the lognormal standard deviation
(2018-01-01)
Huang, Wei-Heng
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Yeh, Arthur B.
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Wang, Hsiuying
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統計學研究所
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Institute of Statistics
Among the statistical process control techniques, the control chart has been proven to be effective in process monitoring. The Shewhart S-chart is one of the most commonly used control charts for monitoring the process variability based on the assumption that the distribution of the quality characteristic to be monitored is normal. However, in real applications, many process distributions may follow a positively skewed distribution such as the lognormal distribution. In this study, a control chart for monitoring the standard deviation of a lognormal distribution is presented. The simulation results show that the proposed chart is more effective than the existing charts when the true value of the scale parameter of the lognormal distribution is large. A real example is used to demonstrate how the proposed chart can be applied in practice.
Anti-NMDA Receptor Encephalitis and Vaccination
(2017-01-01)
Wang, Hsiuying
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統計學研究所
;
Institute of Statistics
Anti-N-methyl-D-aspartate (Anti-NMDA) receptor encephalitis is an acute autoimmune neurological disorder. The cause of this disease is often unknown, and previous studies revealed that it might be caused by a virus, vaccine or tumor. It occurs more often in females than in males. Several cases were reported to be related to vaccination such as the H1N1 vaccine and tetanus/diphtheria/pertussis and polio vaccines. In this study, we reported an anti-NMDA receptor encephalitis case that may be caused by Japanese encephalitis vaccination. To investigate the association between anti-NMDA receptor encephalitis and vaccination, we analyzed the phylogenetic relationship of the microRNAs, which significantly regulate these vaccine viruses or bacteria, and the phylogenetic relationship of these viruses and bacteria. This reveals that anti-NMDA receptor encephalitis may be caused by Japanese encephalitis vaccination, as well as H1N1 vaccination or tetanus/diphtheria/pertussis and polio vaccinations, from the phylogenetic viewpoint.
Anti-NMDA Receptor Encephalitis, Vaccination and Virus
(2019-01-01)
Wang, Hsiuying
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統計學研究所
;
Institute of Statistics
Anti-N-methyl-d-aspartate (Anti-NMDA) receptor encephalitis is an acute autoimmune disorder. The symptoms range from psychiatric symptoms, movement disorders, cognitive impairment, and autonomic dysfunction. Previous studies revealed that vaccination might induce this disease. A few cases were reported to be related to H1N1 vaccine, tetanus/diphtheria/pertussis and polio vaccine, and Japanese encephalitis vaccine. Although vaccination is a useful strategy to prevent infectious diseases, in a low risk, it may trigger serious neurological symptoms. In addition to anti-NMDA receptor encephalitis, other neurological diseases were reported to be associated with a number of vaccines. In this paper, the anti-NMDA receptor encephalitis cases related to a number of vaccines and other neurological symptoms that might be induced by these vaccines were reviewed. In addition, anti-NMDA receptor encephalitis cases that were induced by virus infection were also reviewed.
Anti-NMDA Receptor Encephalitis: Efficacy of Treatment for Male Patients and miRNA Biomarker
(2020-01-01)
Wang, Hsiuying
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統計學研究所
;
Institute of Statistics
Background: Anti-N-methyl-D-aspartate (NMDA) receptor encephalitis is an acute form of encephalitis. Treatments for the anti-NMDA receptor encephalitis usually include steroids, intravenous immunoglobulin, plasma exchange, plasmapheresis, rituximab, cyclophosphamide and tumor resection. Objective: We aimed to compare the efficacy of the treatments including intravenous immunoglobulin, plasma exchange, plasmapheresis, rituximab or cyclophosphamide for male anti- NMDA receptor encephalitis patients without tumor and to discuss potential biomarkers for this disease. Method: The Fisher exact test and the contingency table analysis were used to analyze the treatment efficacy for 43 male and 76 female patients. In addition, a hierarchical tree method was adopted to analyze the difference in the treatment efficacy between male and female patients. Results: The p-values of testing whether the efficacy rate of plasmapheresis (or plasma exchange) for the male patient is greater than a threshold are significantly different from the p-values for the other two treatments. In addition, the hierarchical tree method shows that the treatment strategy associating with early recovery is different for male and female patients. Conclusion: The results revealed that the efficacy rate of plasmapheresis (or plasma exchange) is not inferior to that of intravenous immunoglobulin and rituximab (or cyclophosphamide) for male patients without tumor. In addition, B-cell attracting C-X-C motif chemokine 13 (CXCL13) and microRNA let-7b have the potential to be the treatment response biomarkers for anti-NMDA receptor encephalitis. They may not be useful prognostic biomarkers for this encephalitis unless they are not biomarkers for other autoimmune encephalitides.
Approximate Tolerance Limits Under Log-Location-Scale Regression Models in the Presence of Censoring
(2010-08-01)
Emura, Takeshi
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Wang, Hsiuying
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統計學研究所
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Institute of Statistics
For a product manufactured in large quantities, tolerance limits play a fundamental role in setting limits on the process capability. Existing methodologies for setting tolerance limits in life test experiments focus primarily on one-sample problems. In this study, we extend tolerance limits in the presence of covariates in life test experiments. A method constructing approximate tolerance limits is proposed under log-location-scale regression models, a class of models used widely in reliability and life test experiments. The method is based on an application of the large sample theory of maximum likelihood estimators, which is modified by a bias-adjustment technique to enhance small sample accuracy. The proposed approximate tolerance limits are shown asymptotically to have nominal coverage probability under the assumption of "independent censoring." This includes Type I and Type II censoring schemes. Simulation studies are conducted to assess finite sample properties under the log-location-scale regression models. The method is illustrated with two datasets. R codes for implementing the proposed method are available online on the Technometrics web site, as supplemental materials.
Bayesian ranking responses in multiple-response questions
(2014-01-01)
Wang, Hsiuying
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Huang, Wei Heng
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交大名義發表
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統計學研究所
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National Chiao Tung University
Questionnaires are important surveying tools that are used in numerous studies. Analyses of multiple-response questions are not as well established in detail compared with single-response questions. Wang has proposed several methods for ranking responses in multiple-response questions under the frequentist set-up. However, prior information may exist for ranks of responses in numerous situations. Therefore, establishing a methodology that combines updated survey data and past information for ranking responses is an essential issue in questionnaire data analysis. This study develops Bayesian ranking methods based on several Bayesian multiple-testing procedures to rank responses by controlling the posterior expected false discovery rate. Moreover, a simulation is conducted to compare these approaches, and a real data example is presented to show the effectiveness of the methods proposed.
Closed Form Prediction Intervals Applied for Disease Counts
(2010-08-01)
Wang, Hsiuying
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統計學研究所
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Institute of Statistics
The prediction interval is an important tool in medical applications for predicting the number of times a disease will occur in a population. The performance of the existing prediction intervals, however, is unsatisfactory when the true proportion is near a boundary. Since the true proportion can be very small in real applications, in this article, we propose improved prediction intervals with better coverage probability than the existing methods. Their predictive distributions are compared in terms of the Kullback-Leibler distance and the intervals are compared using a hearing screening medical example.
Comparison of p control charts for low defective rate
(2009-10-01)
Wang, Hsiuying
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統計學研究所
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Institute of Statistics
It is well known that the conventional p control chart constructed by the normal approximation for the binomial distribution suffers a serious inaccuracy in the monitor process when the true rate of nonconforming items is small. A similar problem also arises in the binomial confidence interval estimation. Adjusted confidence intervals are established in the literature to improve the coverage probability when the binomial proportion is small. In this paper, a new p control chart based on an adjusted confidence interval is established, which can substantially improve the existing control charts when the nonconforming rate is small. (C) 2009 Elsevier B.V. All rights reserved.
Confidence intervals for a bounded mean in exponential families
(2014-03-04)
Wang, Hsiuying
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統計學研究所
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Institute of Statistics
Setting confidence bounds or intervals for a parameter in a restricted parameter space is an important issue in applications and is widely discussed in the recent literature. In this article, we focus on the distributions in the exponential families, and propose general forms of the truncated Pratt interval and rp interval for the means. We take the Poisson distribution as an example to illustrate the method and compare it with the other existing intervals. Besides possessing the merits from the theoretical inferences, the proposed intervals are also shown to be competitive approaches from simulation and real-data application studies.
Confidence intervals for the mean of a normal distribution with restricted parameter space
(2008)
Wang, Hsiuying
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統計學研究所
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Institute of Statistics
For a normal distribution with known variance, the standard confidence interval of the location parameter is derived from the classical Neyman procedure. When the parameter space is known to be restricted, the standard confidence interval is arguably unsatisfactory. Recent articles have addressed this problem and proposed confidence intervals for the mean of a normal distribution where the parameter space is not less than zero. In this article, we propose a new confidence interval, rp interval, and derive the Bayesian credible interval and likelihood ratio interval for general restricted parameter space. We compare these intervals with the standard interval and the minimax interval. Simulation studies are undertaken to assess the performances of these confidence intervals.
Confidence intervals for the substitution number in the nucleotide substitution models
(2011-09-01)
Wang, Hsiuying
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統計學研究所
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Institute of Statistics
In the nucleotide substitution model for molecular evolution, a major task in the exploration of an evolutionary process is to estimate the substitution number per site of a protein or DNA sequence. The usual estimators are based on the observation of the difference proportion of the two nucleotide sequences. However, a more objective approach is to report a confidence interval with precision rather than only providing point estimators. The conventional confidence intervals used in the literature for the substitution number are constructed by the normal approximation. The performance and construction of confidence intervals for evolutionary models have not been much investigated in the literature. In this article, the performance of these conventional confidence intervals for one-parameter and two-parameter models are explored. Results show that the coverage probabilities of these intervals are unsatisfactory when the true substitution number is small. Since the substitution number may be small in many situations for an evolutionary process, the conventional confidence interval cannot provide accurate information for these cases. Improved confidence intervals for the one-parameter model with desirable coverage probability are proposed in this article. A numerical calculation shows the substantial improvement of the new confidence intervals over the conventional confidence intervals. (C) 2011 Elsevier Inc. All rights reserved.
Constructing Biological Pathways by a Two-Step Counting Approach
(2011-06-01)
Wang, Hsiuying
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Lu, Henry Horng-Shing
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Chueh, Tung-Hung
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統計學研究所
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Institute of Statistics
Networks are widely used in biology to represent the relationships between genes and gene functions. In Boolean biological models, it is mainly assumed that there are two states to represent a gene: on-state and off-state. It is typically assumed that the relationship between two genes can be characterized by two kinds of pairwise relationships: similarity and prerequisite. Many approaches have been proposed in the literature to reconstruct biological relationships. In this article, we propose a two-step method to reconstruct the biological pathway when the binary array data have measurement error. For a pair of genes in a sample, the first step of this approach is to assign counting numbers for every relationship and select the relationship with counting number greater than a threshold. The second step is to calculate the asymptotic p-values for hypotheses of possible relationships and select relationships with a large p-value. This new method has the advantages of easy calculation for the counting numbers and simple closed forms for the p-value. The simulation study and real data example show that the two-step counting method can accurately reconstruct the biological pathway and outperform the existing methods. Compared with the other existing methods, this two-step method can provide a more accurate and efficient alternative approach for reconstructing the biological network.
Constructing exact tolerance intervals for the exponential distribution based on record values
(1970-01-01)
Guo, Baocai
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Zhu, Naifan
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Wang, Wei
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Wang, Hsiuying
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統計學研究所
Recently, with the wide application of tolerance intervals (TIs), especially in quality management, the construction of TIs has attracted increasing attention. However, TIs applied to record data have not been well established as they have been for complete data. In many industrial stress tests, only record data are stored instead of complete data, which leads to the fact that the developments of methods based on record data are as important as those based on complete data. In this paper, we propose the exact two-sided TIs for the exponential distribution based on record values from the frequentist and Bayesian perspectives. The accuracy of each type of TIs is quantified. The results show that the Bayesian approach is superior to the frequentist approach in terms of the accuracy. A real data example is used to illustrate the constructions and implementations of the proposed TIs.
Constructing Tolerance Intervals for the Number of Defectives Using Both High-and Low-Resolution Data
(2017-10-01)
Wang, Hsiuying
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Tsung, Fugee
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統計學研究所
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Institute of Statistics
Defect inspection is important in many industries, such as in the manufacturing and pharmaceutical industries. Existing methods usually use either low-resolution data, which are obtained from less precise measurements, or high-resolution data, which are obtained from more precise measurements, to estimate the number of defectives in a given amount of goods produced. In this study, a novel approach is proposed that combines the two types of data to construct tolerance intervals with a desired average coverage probability. A simulation study shows that the derived tolerance intervals can lead to better performance than a tolerance interval that is constructed based on only the low-resolution data. In addition, a real-data example shows that the tolerance interval based on only the low-resolution data is more conservative than the tolerance intervals based on both high-resolution and low-resolution data.
Control Charts for the Lognormal Mean
(2016-06)
Huang, Wei-Heng
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Wang, Hsiuying
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Yeh, Arthur B.
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統計學研究所
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Institute of Statistics
Among a set of tools that form the core of statistical process control, statistical control charts are most commonly used for controlling, monitoring, and improving processes. The conventional control charts are based on the assumption that the distribution of the quality characteristic to be monitored follows the normal distribution. However, in real applications, many process distributions may follow a positively skewed distribution such as the lognormal distribution. In this study, we discuss the construction of several control charts for monitoring the mean of the lognormal distribution. A real example is used to demonstrate how these charts can be applied in practice. Copyright (c) 2015 John Wiley & Sons, Ltd.
Coverage probability of prediction intervals for discrete random variables
(2008-09-15)
Wang, Hsiuying
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統計學研究所
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Institute of Statistics
Prediction interval is a widely used tool in industrial applications to predict the distribution of future observations. The exact minimum coverage probability and the average coverage probability of the conventional prediction interval for a discrete random variable have not been accurately derived in the literature. In this paper, procedures to compute the exact minimum confidence levels and the average confidence levels of the prediction intervals for a discrete random variable are proposed. These procedures are illustrated with examples and real data applications. Based on these procedures, modified prediction intervals with the minimum coverage probability or the average coverage probability close to the nominal level can be constructed. (c) 2008 Elsevier B.V. All rights reserved.
Efficacies of treatments for anti-NMDA receptor encephalitis
(2016-01-01)
Wang, Hsiuying
;
統計學研究所
;
Institute of Statistics
Treatments for anti-N-methyl-D-aspartate (NMDA) receptor encephalitis include immunotherapy with steroids, intravenous immunoglobulin, plasma exchange, or plasmapheresis as first-line treatments, immunotherapy with rituximab or cyclophosphamide as second-line treatments, and tumor removal. In this systematic review, we evaluated previous studies and examined the association between certain microRNAs and anti-NMDA receptor encephalitis to investigate the performance of different treatment combinations. The efficacies of different combinations of treatments classified into the following four categories were compared: (I) intravenous immunoglobulin administration, (II) plasmapheresis or plasma exchange, (III) treatment with rituximab or cyclophosphamide and (IV) tumor removal. Statistical analyses showed that treatment combinations including at least two of these categories resulted in higher efficacy rates than treatment with a single form of therapy. These findings suggest that if a patient is not recovering, converting to other therapies is more likely to result in early recovery than continuing on the original therapy.
Efficacies of treatments for anti-NMDA receptor encephalitis
(2016-01-01)
Wang, Hsiuying
;
統計學研究所
;
Institute of Statistics
Treatments for anti-N-methyl-D-aspartate (NMDA) receptor encephalitis include immunotherapy with steroids, intravenous immunoglobulin, plasma exchange, or plasmapheresis as first-line treatments, immunotherapy with rituximab or cyclophosphamide as second-line treatments, and tumor removal. In this systematic review, we evaluated previous studies and examined the association between certain microRNAs and anti-NMDA receptor encephalitis to investigate the performance of different treatment combinations. The efficacies of different combinations of treatments classified into the following four categories were compared: (I) intravenous immunoglobulin administration, (II) plasmapheresis or plasma exchange, (III) treatment with rituximab or cyclophosphamide and (IV) tumor removal. Statistical analyses showed that treatment combinations including at least two of these categories resulted in higher efficacy rates than treatment with a single form of therapy. These findings suggest that if a patient is not recovering, converting to other therapies is more likely to result in early recovery than continuing on the original therapy.
Exact average coverage probabilities and confidence coefficients of confidence intervals for discrete distributions
(2009-06-01)
Wang, Hsiuying
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統計學研究所
;
Institute of Statistics
For a confidence interval (L(X),U(X)) of a parameter theta in one-parameter discrete distributions, the coverage probability is a variable function of theta. The confidence coefficient is the infimum of the coverage probabilities, inf (theta) P (theta) (theta a(L(X),U(X))). Since we do not know which point in the parameter space the infimum coverage probability occurs at, the exact confidence coefficients are unknown. Beside confidence coefficients, evaluation of a confidence intervals can be based on the average coverage probability. Usually, the exact average probability is also unknown and it was approximated by taking the mean of the coverage probabilities at some randomly chosen points in the parameter space. In this article, methodologies for computing the exact average coverage probabilities as well as the exact confidence coefficients of confidence intervals for one-parameter discrete distributions are proposed. With these methodologies, both exact values can be derived.
Exact two-sided tolerance interval controlling tail proportions for sample variances
(1970-01-01)
Guo, Baocai
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Zhu, Naifan
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Wang, Wei
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Song, Yurong
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Wang, Hsiuying
Tolerance intervals (TIs) for variances are useful when we are interested in the precision of the quality characteristic. They can provide a deeper understanding of the process variability corresponding to process improvement and deterioration. In this paper, we consider the exact two-sided TI for sample variances that simultaneously controls the proportions in each of the two tails of the distribution. The minimum number of subgroups required to achieve a specified level of precision is also computed. Moreover, we minimize the width of the TI through adjusting the tolerance factors, and the performance of the adjusted TI shows some improvement, especially when the amount of reference data is small. Finally, a real application is used to illustrate the construction and implementation of the proposed TIs.