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343 results on '"Li, Yu-Fen"'

3. Empirical Likelihood Based Summary ROC Curve for Meta-Analysis of Diagnostic Studies

Author

Tzeng, ShengLi, Chen, Chun-Shu, Li, Yu-Fen, and Chen, Jin-Hua

Subjects
Statistics - Methodology
Abstract

Objectives: This study provides an effective model selection method based on the empirical likelihood approach for constructing summary receiver operating characteristic (sROC) curves from meta-analyses of diagnostic studies. Methods: We considered models from combinations of family indices and specific pairs of transformations, which cover several widely used methods for bivariate summary of sensitivity and specificity. Then a final model was selected using the proposed empirical likelihood method. Simulation scenarios were conducted based on different number of studies and different population distributions for the disease and non-disease cases. The performance of our proposal and other model selection criteria was also compared. Results: Although parametric likelihood-based methods are often applied in practice due to its asymptotic property, they fail to consistently choose appropriate models for summary under the limited number of studies. For these situations, our proposed method almost always performs better. Conclusion: When the number of studies is as small as 10 or 5, we recommend choosing a summary model via the proposed empirical likelihood method.

Published
2018

5. Distance for Functional Data Clustering Based on Smoothing Parameter Commutation

Author

Tzeng, ShengLi, Hennig, Christian, Li, Yu-Fen, and Lin, Chien-Ju

Subjects
Statistics - Methodology, Statistics - Applications, Statistics - Machine Learning
Abstract

We propose a novel method to determine the dissimilarity between subjects for functional data clustering. Spline smoothing or interpolation is common to deal with data of such type. Instead of estimating the best-representing curve for each subject as fixed during clustering, we measure the dissimilarity between subjects based on varying curve estimates with commutation of smoothing parameters pair-by-pair (of subjects). The intuitions are that smoothing parameters of smoothing splines reflect inverse signal-to-noise ratios and that applying an identical smoothing parameter the smoothed curves for two similar subjects are expected to be close. The effectiveness of our proposal is shown through simulations comparing to other dissimilarity measures. It also has several pragmatic advantages. First, missing values or irregular time points can be handled directly, thanks to the nature of smoothing splines. Second, conventional clustering method based on dissimilarity can be employed straightforward, and the dissimilarity also serves as a useful tool for outlier detection. Third, the implementation is almost handy since subroutines for smoothing splines and numerical integration are widely available. Fourth, the computational complexity does not increase and is parallel with that in calculating Euclidean distance between curves estimated by smoothing splines.

Published
2016
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14. On summary ROC curve for dichotomous diagnostic studies: an application to meta-analysis of COVID-19.

Author

Tzeng, ShengLi, Chen, Chun-Shu, Li, Yu-Fen, and Chen, Jin-Hua

Subjects
RECEIVER operating characteristic curves, CHEMILUMINESCENCE immunoassay, COVID-19, COVID-19 testing, SENSITIVITY & specificity (Statistics)
Abstract

In a systematic review of a diagnostic performance, summarizing performance metrics is crucial. There are various summary models in the literature, and hence model selection becomes inevitable. However, most existing large-sample-based model selection approaches may not fit in a meta-analysis of diagnostic studies, typically having a rather small sample size. Researchers need to effectively determine the final model for further inference, which motivates this article to investigate existing methods and to suggest a more robust method for this need. We considered models covering several widely-used methods for bivariate summary of sensitivity and specificity. Simulation studies were conducted based on different number of studies and different population sensitivity and specificity. Then final models were selected using several existing criteria, and we compared the summary receiver operating characteristic (sROC) curves to the theoretical ROC curve given the generating model. Even though parametric likelihood-based criteria are often applied in practice for their asymptotic property, they fail to consistently choose appropriate models under the limited number of studies. When the number of studies is as small as 10 or 5, our suggestion is best in different scenarios. An example for summary ROC curves for chemiluminescence immunoassay (CLIA) used in COVID-19 diagnosis is also illustrated. [ABSTRACT FROM AUTHOR]

Published
2023
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15. Sirolimus treatment for tuberous sclerosis complex prior to epilepsy: Evidence from a registry-based real-world study

Author

Shen, Yan-Wen, primary, Wang, Yang-Yang, additional, Zhang, Meng-Na, additional, Xu, Yong, additional, Lu, Qian, additional, He, Wen, additional, Chen, Hui-Min, additional, Liu, Li-Ying, additional, Pang, Ling-Yu, additional, Wang, Qiu-Hong, additional, Dun, Shuo, additional, Li, Yu-Fen, additional, Gao, Jing, additional, Han, Fang, additional, and Zou, Li-Ping, additional

Published
2022
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29. Safety Profile of Sirolimus in All Age Groups: A Pooled Analysis of Two 10-Year Cohort Studies Comprising 1738 Patients With Tuberous Sclerosis and/or Lymphangioleiomyomatosis

Author

Zou, Li-Ping, primary, Wang, Yang-Yang, additional, Xu, Kai-Feng, additional, Xu, Wen-Shuai, additional, Zhang, Meng-Na, additional, Tian, Xin-Lun, additional, Pang, Ling-Yu, additional, He, Wen, additional, Wang, Qiu-Hong, additional, Gao, Yang, additional, Liu, Li-Ying, additional, Chen, Xiao-Qiao, additional, Ma, Shu-Fang, additional, Chen, Hui-Min, additional, Dun, Shuo, additional, Yang, Xiao-Yan, additional, Luo, Xiao-Mei, additional, Huang, Lu-Lu, additional, and Li, Yu-Fen, additional

Published
2021
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50. Effects of patient factors on noninvasive liver stiffness measurement using acoustic radiation force impulse elastography in patients with chronic hepatitis C

Author

Chen Sheng-Hung, Li Yu-Fen, Lai Hsueh-Chou, Kao Jung-Ta, Peng Cheng-Yuan, Chuang Po-Heng, Su Wen-Pang, and Chiang I-Ping

Subjects
Liver fibrosis, Cirrhosis, Acoustic radiation force impulse, FibroTest, ActiTest, Chronic hepatitis C, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Abstract Background Previous research has shown variation in the effects of patient factors, including hepatic necroinflammatory activity, on liver stiffness measurement (LSM). This prospective study attempts to identify explanatory factors for LSM in patients with chronic hepatitis C (CHC) using acoustic radiation force impulse (ARFI) technology. Methods A cohort of 127 Taiwanese patients with CHC underwent ARFI LSM and immediate percutaneous liver biopsy. This study compares the concurrent diagnostic performances of LSM and FibroTest using receiver operating characteristic (ROC) curves. Three multiple linear regression models were used to evaluate the significance of concurrent patient factors in explaining LSM. Results To classify METAVIR fibrosis (F) stages, the areas under ROC curves (AUCs) were ARFI LSM, 0.847 (95% confidence interval (CI), 0.779-0.914) and FibroTest, 0.823 (95% CI, 0.748-0.898), for F1 versus F2-4; ARFI LSM, 0.902 (95% CI, 0.835-0.970) and FibroTest, 0.812 (95% CI, 0.735-0.888), for F1-2 versus F3-4; ARFI LSM, 0.831 (95% CI, 0.723-0.939) and FibroTest, 0.757 (95% CI, 0.648-0.865), for F1-3 versus F4. After adjusting for other demographic and biological covariates, biochemical and histological necroinflammatory factors consistently explained LSM. Factors included serum alanine aminotransferase (ALT)/upper limit of normal (ULN) categories (model R2 = 0.661, adjusted R2 = 0.629), ActiTest A scores (R2 = 0.662, adjusted R2 = 0.636), and METAVIR activity (A) grades (R2 = 0.651, adjusted R2 = 0.620). METAVIR F stages, body mass index, and platelet count were also independently associated with LSM. Necroinflammatory degrees, including ALT/ULN, ActiTest A scores, and METAVIR A grades, explained the false positivity of liver fibrosis staging using ARFI LSM. Conclusions The degree of hepatic necroinflammatory activity independently and significantly exaggerated liver fibrosis evaluation using ARFI LSM. However, comparisons with concurrent FibroTest indicate that ARFI LSM may be a promising alternative, or adjunctive single indicator, for liver fibrosis evaluation in patients with CHC.

Published
2012
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