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http://hdl.handle.net/1942/42983
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DC Field | Value | Language |
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dc.contributor.author | BURZYKOWSKI, Tomasz | - |
dc.date.accessioned | 2024-05-22T09:38:21Z | - |
dc.date.available | 2024-05-22T09:38:21Z | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-05-15T09:24:18Z | - |
dc.identifier.citation | Seminars in Orthodontics, 30 (1) , p. 29 -36 | - |
dc.identifier.uri | http://hdl.handle.net/1942/42983 | - |
dc.description.abstract | Censoring occurs when we do not observe exactly the value that we are interested in, but we only learn about some bounds for it. For instance, an observation is right-censored (left-censored) when it is smaller (larger) than the true value. Censoring is most often encountered when observing a time to event, i.e., the time that elapses between a welldefined starting moment until a particular event of interest (for example, the age until the first dental caries). However, it may apply to any measurement or observation. For instance, left- and right-censoring applies to diagnostic assays with, respectively, a lower and an upper limit of detection. The presence of censored observations has important consequences for the statistical analysis. This is because, in such a case, the use of classical statistics (such as, e.g., the sample mean) or statistical models (such as, e.g., linear regression) will result in biased results. Analysis of data that include censored observations requires the use of methods that take explicitly into account censoring. Collectively, in medicine, these methods are referred to as survival analysis. In this article, we provide a review of the basic (parametric and non-parametric) statistical methods of survival analysis. | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER INC | - |
dc.rights | 2024 Elsevier Inc. All rights reserved. | - |
dc.subject.other | Censoring | - |
dc.subject.other | Kaplan -Meier estimator | - |
dc.subject.other | Logrank test | - |
dc.subject.other | Accelerated failure -time model | - |
dc.subject.other | Proportional -hazards model | - |
dc.title | Survival analysis: Methods for analyzing data with censored observations | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 36 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 29 | - |
dc.identifier.volume | 30 | - |
local.format.pages | 8 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Burzykowski, T (corresponding author), Hasselt Univ, Data Sci Inst, Agoralaan D, B-3590 Diepenbeek, Belgium. | - |
dc.description.notes | tomasz.burzykowski@uhasselt.be | - |
local.publisher.place | 525 B STREET, STE 1900, SAN DIEGO, CA 92101-4495 USA | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1053/j.sodo.2024.01.008 | - |
dc.identifier.isi | 001198958500001 | - |
dc.contributor.orcid | Burzykowski, Tomasz/0000-0003-3378-975X | - |
local.provider.type | wosris | - |
local.description.affiliation | [Burzykowski, Tomasz] Hasselt Univ, Data Sci Inst, Agoralaan D, B-3590 Diepenbeek, Belgium. | - |
local.description.affiliation | [Burzykowski, Tomasz] Med Univ Bialystok, Dept Biostat & Med Informat, Szpitalna 37, PL-15295 Bialystok, Poland. | - |
local.uhasselt.international | no | - |
item.fullcitation | BURZYKOWSKI, Tomasz (2024) Survival analysis: Methods for analyzing data with censored observations. In: Seminars in Orthodontics, 30 (1) , p. 29 -36. | - |
item.fulltext | With Fulltext | - |
item.contributor | BURZYKOWSKI, Tomasz | - |
item.accessRights | Open Access | - |
crisitem.journal.issn | 1073-8746 | - |
crisitem.journal.eissn | 1558-4631 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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Survival analysis_ Methods for analyzing data with censored observations.pdf Restricted Access | Published version | 833.34 kB | Adobe PDF | View/Open Request a copy |
SurvivalAnalysis_3_clean_to_submit.pdf | Peer-reviewed author version | 568.03 kB | Adobe PDF | View/Open |
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