scholarly journals A multivariate normal regression model for survival data subject to different types of dependent censoring

2020 ◽  
Vol 144 ◽  
pp. 106879 ◽  
Author(s):  
Negera Wakgari Deresa ◽  
Ingrid Van Keilegom
Keyword(s):  
Regression Model ◽  
Survival Data ◽  
Dependent Censoring ◽  
Multivariate Normal ◽  
Normal Regression ◽  
Different Types ◽  
Data Subject

scholarly journals Flexible parametric model for survival data subject to dependent censoring

2019 ◽  
Vol 62 (1) ◽  
pp. 136-156 ◽  
Author(s):  
Negera Wakgari Deresa ◽  
Ingrid Van Keilegom
Keyword(s):  
Survival Data ◽  
Parametric Model ◽  
Dependent Censoring ◽  
Flexible Parametric Model ◽  
Data Subject

Influence diagnostics in a multivariate normal regression model with general parameterization

2010 ◽  
Vol 7 (6) ◽  
pp. 644-654 ◽  
Author(s):  
Alexandre G. Patriota ◽  
Artur J. Lemonte ◽  
Mário de Castro
Keyword(s):  
Regression Model ◽  
Multivariate Normal ◽  
Normal Regression ◽  
Influence Diagnostics

Modeling Random Effects for Censored Data by a Multivariate Normal Regression Model

Biometrics ◽  
1999 ◽  
Vol 55 (2) ◽  
pp. 497-506 ◽  
Author(s):  
John P. Klein ◽  
Corey Pelz ◽  
Mei-jie Zhang
Keyword(s):  
Regression Model ◽  
Random Effects ◽  
Censored Data ◽  
Multivariate Normal ◽  
Normal Regression

scholarly journals Bias correction in a multivariate normal regression model with general parameterization

2009 ◽  
Vol 79 (15) ◽  
pp. 1655-1662 ◽  
Author(s):  
Alexandre G. Patriota ◽  
Artur J. Lemonte
Keyword(s):  
Regression Model ◽  
Bias Correction ◽  
Multivariate Normal ◽  
Normal Regression

scholarly journals Withdrawal Properties of Self-Tapping Screws in Japanese larch (Larix kaempferi (Lamb.) Carr.) Cross Laminated Timber

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 524
Author(s):  
Junhua Xu ◽  
Shuangbao Zhang ◽  
Guofang Wu ◽  
Yingchun Gong ◽  
Haiqing Ren
Keyword(s):  
Regression Model ◽  
Engineering Design ◽  
Wood Species ◽  
Japanese Larch ◽  
Effective Length ◽  
Larix Kaempferi ◽  
Cross Laminated Timber ◽  
The World ◽  
Different Types ◽  
Length Increment

With the increasing popularity of cross-laminated timber (CLT) constructions around the world, there have been attempts to produce CLT using local wood species in different countries, such as Japanese larch (Larix kaempferi (Lamb.) Carr.) in China. Thus, the need to investigate the connection performance also increases to support the design and construction of CLT buildings using local wood species. In this study, the withdrawal properties of three different types of self-tapping screws (STS), with a diameter of 6 mm, 8 mm, and 11 mm, were tested with Japanese larch CLT. The results revealed that the withdrawal strength of STS increased with increasing density and effective length, but decreased with an increasing diameter. With a density increment of 0.05 g/cm3, the withdrawal strength increased by an average of 9.4%. With an effective length increment of 24 mm, the withdrawal strength increased by an average of 1.4%. An empirical regression model was adopted to predict the withdrawal strength of Japanese larch CLT based on the results, which can be used for potential engineering design of CLT connections using STS.

scholarly journals Are "Clean" Cosmetic Products Really Clean? A Pilot Study on the Validity of Cosmetic Labeling

2021 ◽  
Author(s):  
Jeannie H. Phan ◽  
Khine K. Kyaw ◽  
Julia K. Tan ◽  
Emily Q. Lam ◽  
Cheng-Kuan Lin
Keyword(s):  
Public Education ◽  
Regression Model ◽  
Reproductive Toxicity ◽  
Data Availability ◽  
Cosmetic Products ◽  
Health Concerns ◽  
Different Types ◽  
Labeling System ◽  
Inform Decision Making ◽  
Beauty Products

Abstract Background As a result of increased demand for environmental and health-conscious cosmetics, retailers have increasingly marketed their products using terms such as “clean” or "non-toxic". Sephora, a popular beauty retailer, implemented a clean seal system to label and promote their products. This study aims to compare the toxicity concerns of clean vs. non-clean products by using the Environmental Working Group (EWG)'s Skin Deep framework. Methods EWG’s Skin Deep Framework was used to rank products based on their cancer, allergy and immunotoxicity, developmental and reproductive toxicity, and use-restriction concerns, with lower scores indicating a cleaner product (ranging 0–10). The distributions of EWG scores among clean and non-clean products were investigated and stratified by different types of products (i.e. fragrance, hair, makeup, or skincare). A multivariable linear regression model was further applied to evaluate the association between EWG scores and clean seals, adjusting by types of products, level of toxicity concerns. Results 356 products were screened, including 180 (50.56%) clean products and 176 (49.44%) non-clean products. Clean products yielded a higher percentage of low hazard ingredients compared to non-clean products. EWG scores are positively correlated with the levels of toxicity concern for cancer, allergy and immunotoxicity, respectively. Clean products are also associated with a lower EWG score by 0.71 in the regression model. Fragrance products are most hazardous, with a 2.42 increase in EWG score. Conclusions Products under the binary “clean beauty” labeling system at Sephora may not necessarily capture the nuances of EWG’s ten-point scoring system and various dimensions of health concerns. It may be insufficient for consumers to solely rely on the presence of the clean seal when purchasing beauty products. Consulting multiple frameworks and sources to inform decision-making is crucial in addressing knowledge gaps. Further research and increased data availability from EWG’s database are necessary as well as public education on the application of Sephora’s clean seal.

scholarly journals Targeted Minimum Loss-Based Estimation of Causal Effects in Right-Censored Survival Data with Time-Dependent Covariates: Warfarin, Stroke, and Death in Atrial Fibrillation

2013 ◽  
Vol 1 (2) ◽  
pp. 235-254 ◽  
Author(s):  
Jordan C. Brooks ◽  
Mark J. van der Laan ◽  
Daniel E. Singer ◽  
Alan S. Go
Keyword(s):  
Survival Data ◽  
Causal Effect ◽  
Estimating Equation ◽  
Dependent Censoring ◽  
Time Dependent ◽  
Causal Effects ◽  
Consistent Estimation ◽  
Censored Survival Data ◽  
Inverse Probability ◽  
Time Dependent Covariates

AbstractCausal effects in right-censored survival data can be formally defined as the difference in the marginal cumulative event probabilities under particular interventions. Conventional estimators, such as the Kaplan-Meier (KM), fail to consistently estimate these marginal parameters under dependent treatment assignment or dependent censoring. Several modern estimators have been developed that reduce bias under both dependent treatment assignment and dependent censoring by incorporating information from baseline and time-dependent covariates. In the present article we describe a recently developed targeted minimum loss-based estimation (TMLE) algorithm for general longitudinal data structures and present in detail its application in right-censored survival data with time-dependent covariates. The treatment-specific marginal cumulative event probability is defined via a series of iterated conditional expectations in a time-dependent counting process framework. The TMLE involves an initial estimator of each conditional expectation and sequentially updates these such that the resulting estimator solves the efficient influence curve estimating equation in the nonparametric statistical model. We describe the assumptions required for consistent estimation of statistical parameters and additional assumptions required for consistent estimation of the causal effect parameter. Using simulated right-censored survival data, the mean squared error, bias, and 95% confidence interval coverage probability of the TMLE is compared with those of the conventional KM and the inverse probability of censoring weight estimating equation, conventional maximum likelihood substitution estimator, and the double robustaugmented inverse probability of censoring weighted estimating equation. We conclude the article with estimation of the causal effect of warfarin medical therapy on the probability of “stroke or death” within a 1-year time frame using data from the ATRIA-1 observational cohort of persons with atrial fibrillation. Our results suggest that a fixed policy of warfarin treatment for all patients would result in 2% fewer deaths or strokes within 1-year as compared with a policy of withholding warfarin from all patients.

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