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Survival Analysis, Kaplan-Meier Curves, and Cox Regression: Basic Concepts [PDF]
Indian Journal of Psychological Medicine, 2023 Survival analysis is used to analyze data from patients who are followed for different periods of time and in whom the outcome of interest, a dichotomous event, may or may not have occurred at the time the study is halted; data from all patients are used
Chittaranjan Andrade
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Reconstructing patient level survival data from published Kaplan-Meier curves [PDF]
Contemporary Clinical Trials CommunicationsIntroduction: Individual-level patient data (IPD) are helpful for designing clinical trials, conducting meta-analyses, or methodology research. However, such patient level data are not readily available.
Jaromme Kim +2 more
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IPDfromKM: reconstruct individual patient data from published Kaplan-Meier survival curves [PDF]
BMC Medical Research Methodology, 2021 Background When applying secondary analysis on published survival data, it is critical to obtain each patient’s raw data, because the individual patient data (IPD) approach has been considered as the gold standard of data analysis.
Na Liu, Yanhong Zhou, J. Jack Lee
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KMSubtraction: reconstruction of unreported subgroup survival data utilizing published Kaplan-Meier survival curves [PDF]
BMC Medical Research Methodology, 2022 Background Data from certain subgroups of clinical interest may not be presented in primary manuscripts or conference abstract presentations. In an effort to enable secondary data analyses, we propose a workflow to retrieve unreported subgroup survival ...
Joseph J. Zhao +6 more
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Kaplan-Meier Type Survival Curves for COVID-19: A Health Data Based Decision-Making Tool [PDF]
Frontiers in Public Health, 2021 Countries are recording health information on the global spread of COVID-19 using different methods, sometimes changing the rules after a few days. All of them are publishing the number of new individuals infected, recovered and dead individuals, along ...
J. M. Calabuig +3 more
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Hidden Imputations and the Kaplan-Meier Estimator. [PDF]
Am J Epidemiol, 2020 AbstractThe Kaplan-Meier (KM) estimator of the survival function imputes event times for right-censored and left-truncated observations, but these imputations are hidden and therefore sometimes unrecognized by applied health scientists. Using a simple example data set and the redistribution algorithm, we illustrate how imputations are made by the KM ...
Cole SR, Edwards JK, Naimi AI, Muñoz A.
europepmc +4 more sources
KAPLAN-MEIER AND NELSON-AALEN ESTIMATORS FOR CREDIT SCORING
Media Statistika, 2023 Financial institutions use credit scoring analysis to predict the probability that a customer will default. In this paper, we determine the probability of default using nonparametric survival analysis that are Kaplan-Meier and Nelson-Aalen.
Tatik Widiharih +3 more
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British Journal of Surgery, 2017 Analysis of time-to-event (“survival”) data typically requires two pieces of data that are taken into account simultaneously: i) the time period for which follow-up was available, and ii) the status at the end of the follow-up. The former variable is continuous (time) and the latter categorical, specifying whether the endpoint was the event under study,
Ranstam, J, Cook, J
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Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data
Stats, 2022 Due to the wide availability of functional data from multiple disciplines, the studies of functional data analysis have become popular in the recent literature. However, the related development in censored survival data has been relatively sparse.
Sudaraka Tholkage +2 more
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Using the Kaplan–Meier Estimator to Assess the Reliability of Agricultural Machinery
Agronomy, 2022 Kaplan–Meier analyses can be used in many disciplines, e.g., agricultural engineering. Agricultural machinery and vehicles can be regarded as objects that ‘die’ because, like living creatures, they failed, although after repair they can be used until ...
Karol Durczak +5 more
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