A Comparison of Semi-Parametric and Nonparametric Methods for Estimating Mean Time to Event for Randomly Left Censored Data

Chowdhury, Farzana; Gulshan, Jahida; Hossain, Syed Shahadat

doi:10.22237/jmasm/1430453760

Cited by 7 publications

(3 citation statements)

References 13 publications

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“…Reliability Function is the probability that a system survives longer that time t, and Cumulative Hazard Function is the accumulation of the hazard (hazard is the event rate at time t conditional on survival until time t or later (R(t) = P (T ≥ t)) over time. First, for Reliability Function, the non-parametric technique (Chowdhury et al, 2015) is called Kaplan-Meier (Kaplan and Meier, 1958), and for Cumulative Hazard, Nelson-Aaalen (Aalen, 1978) . In Eq.…”

Section: Methodsmentioning

confidence: 99%

Time to Event Analysis for Failure Causes in Electrical Power Distribution Systems

Fogliatto

Desuó

Ribeiro

et al. 2020

Anais Do Congresso Brasileiro De Automática 2020

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Electricity is a fundamental resource for modern society. However, some threats are faced by Electrical Power Distribution Systems, which are responsible for delivering electricity to end consumers. Analyzing how much time these hazards will threaten these systems, causing failure events, is an essential area of study. Through statistical methods, it is possible to study this behaviour from time until failure, as well as to observe the influence of variables at this time,providing models to predict when a failure event will occur. In this study, Reliability Analysis Regression techniques are used on real data, constructing a model for all failures and for different groups of failures, using non-parametric and parametric methods to estimate the reliability and cumulative hazard curves. An analysis of the failure causes directly linked to weather events, using six weather variables, is also made.

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Section: Methodsmentioning

confidence: 99%

Time to Event Analysis for Failure Causes in Electrical Power Distribution Systems

Fogliatto

Desuó

Ribeiro

et al. 2020

Anais Do Congresso Brasileiro De Automática 2020

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“…The summary statistics produced by the MLE method are determined from the lognormal distribution that ''best fits'' the entire data set; imposing the distributional assumption on both the censored and uncensored data points. Several authors have examined the comparisons between these three methods, e.g., Annan, et al (2009) and Chowdhury, et al (2015). Helsel (2012) lists over 15 other papers comparing these and other methods for addressing censored data.…”

Section: Methodsmentioning

confidence: 99%

Evaluating Concentrations of Pesticides and Heavy Metals in the U.S. Peanut Crop in the Presence of Detection Limits

Blair

Lamb

2017

Peanut Science

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The concentration of mercury, cadmium, lead, and arsenic along with glyphosate and an extensive array of pesticides in the U.S. peanut crop was assessed for crop years 2013-2015. Samples were randomly selected from various buying points during the grading process. Samples were selected from the three major growing regions in order to attain a representative sample of U.S. peanut production. Samples were sent to an independent laboratory for testing. Appropriate statistical techniques were used to account for censored data due to test results below detection limits. Descriptive statistics and confidence intervals for the population mean concentration are presented where possible. For heavily censored data, the probability of a random sample from the population testing below the detection limit is estimated. Overall, concentrations were found to be low relative to health standards and consistent across crop years.

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“…Moreover, Çolak et al 31 compared the performance of parametric, semi-parametric, and nonparametric receiver operating characteristic (ROC) models using acute coronary syndrome data. Chowdhury et al 32 compared semi-parametric and nonparametric methods for estimating mean time to event for randomly left-censored data. Wey et al 33 compared parametric, semi-parametric, and nonparametric survival models with stacked survival models.…”

Section: Introductionmentioning

confidence: 99%

Comparison of parametric and semi-parametric models with randomly right-censored data by weighted estimators: Two applications in colon cancer and hepatocellular carcinoma datasets

Yenılmez

Yılmaz

Kantar

et al. 2021

Stat Methods Med Res

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In this study, parametric and semi-parametric regression models are examined for random right censorship. The components of the aforementioned regression models are estimated with weights based on Cox and Kaplan–Meier estimates, which are semi-parametric and nonparametric methods used in survival analysis, respectively. The Tobit based on weights obtained from a Cox regression is handled as a parametric model instead of other parametric models requiring distribution assumptions such as exponential, Weibull, and gamma distributions. Also, the semi-parametric smoothing spline and the semi-parametric smoothing kernel estimators based on Kaplan–Meier weights are used. Therefore, estimates are obtained from two models with flexible approaches. To show the flexible shape of the models depending on the weights, Monte Carlo simulations are conducted, and all results are presented and discussed. Two empirical datasets are used to show the performance of the aforementioned estimators. Although three approaches gave similar results to each other, the semi-parametric approach was slightly superior to the parametric approach. The parametric approach method, on the other hand, yields good results in medium and large sample sizes and at a high censorship level. All other findings have been shared and interpreted.

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A Comparison of Semi-Parametric and Nonparametric Methods for Estimating Mean Time to Event for Randomly Left Censored Data

Cited by 7 publications

References 13 publications

Time to Event Analysis for Failure Causes in Electrical Power Distribution Systems

Time to Event Analysis for Failure Causes in Electrical Power Distribution Systems

Evaluating Concentrations of Pesticides and Heavy Metals in the U.S. Peanut Crop in the Presence of Detection Limits

Comparison of parametric and semi-parametric models with randomly right-censored data by weighted estimators: Two applications in colon cancer and hepatocellular carcinoma datasets

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