Cross-ratio estimation for bivariate failure times with left truncation
Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased...
Ausführliche Beschreibung
Autor*in: |
Hu, Tianle [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2013 |
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Schlagwörter: |
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Anmerkung: |
© Springer Science+Business Media New York 2013 |
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Übergeordnetes Werk: |
Enthalten in: Lifetime data analysis - Springer US, 1995, 20(2013), 1 vom: 23. Mai, Seite 23-37 |
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Übergeordnetes Werk: |
volume:20 ; year:2013 ; number:1 ; day:23 ; month:05 ; pages:23-37 |
Links: |
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DOI / URN: |
10.1007/s10985-013-9263-7 |
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Katalog-ID: |
OLC2067136720 |
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520 | |a Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. | ||
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10.1007/s10985-013-9263-7 doi (DE-627)OLC2067136720 (DE-He213)s10985-013-9263-7-p DE-627 ger DE-627 rakwb eng 510 004 VZ Hu, Tianle verfasserin aut Cross-ratio estimation for bivariate failure times with left truncation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. Bivariate survival Cross-ratio Left truncation Pseudo-partial likelihood Right censoring Lin, Xihong aut Nan, Bin aut Enthalten in Lifetime data analysis Springer US, 1995 20(2013), 1 vom: 23. Mai, Seite 23-37 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:20 year:2013 number:1 day:23 month:05 pages:23-37 https://doi.org/10.1007/s10985-013-9263-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 20 2013 1 23 05 23-37 |
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10.1007/s10985-013-9263-7 doi (DE-627)OLC2067136720 (DE-He213)s10985-013-9263-7-p DE-627 ger DE-627 rakwb eng 510 004 VZ Hu, Tianle verfasserin aut Cross-ratio estimation for bivariate failure times with left truncation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. Bivariate survival Cross-ratio Left truncation Pseudo-partial likelihood Right censoring Lin, Xihong aut Nan, Bin aut Enthalten in Lifetime data analysis Springer US, 1995 20(2013), 1 vom: 23. Mai, Seite 23-37 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:20 year:2013 number:1 day:23 month:05 pages:23-37 https://doi.org/10.1007/s10985-013-9263-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 20 2013 1 23 05 23-37 |
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10.1007/s10985-013-9263-7 doi (DE-627)OLC2067136720 (DE-He213)s10985-013-9263-7-p DE-627 ger DE-627 rakwb eng 510 004 VZ Hu, Tianle verfasserin aut Cross-ratio estimation for bivariate failure times with left truncation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. Bivariate survival Cross-ratio Left truncation Pseudo-partial likelihood Right censoring Lin, Xihong aut Nan, Bin aut Enthalten in Lifetime data analysis Springer US, 1995 20(2013), 1 vom: 23. Mai, Seite 23-37 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:20 year:2013 number:1 day:23 month:05 pages:23-37 https://doi.org/10.1007/s10985-013-9263-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 20 2013 1 23 05 23-37 |
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10.1007/s10985-013-9263-7 doi (DE-627)OLC2067136720 (DE-He213)s10985-013-9263-7-p DE-627 ger DE-627 rakwb eng 510 004 VZ Hu, Tianle verfasserin aut Cross-ratio estimation for bivariate failure times with left truncation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. Bivariate survival Cross-ratio Left truncation Pseudo-partial likelihood Right censoring Lin, Xihong aut Nan, Bin aut Enthalten in Lifetime data analysis Springer US, 1995 20(2013), 1 vom: 23. Mai, Seite 23-37 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:20 year:2013 number:1 day:23 month:05 pages:23-37 https://doi.org/10.1007/s10985-013-9263-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 20 2013 1 23 05 23-37 |
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10.1007/s10985-013-9263-7 doi (DE-627)OLC2067136720 (DE-He213)s10985-013-9263-7-p DE-627 ger DE-627 rakwb eng 510 004 VZ Hu, Tianle verfasserin aut Cross-ratio estimation for bivariate failure times with left truncation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. Bivariate survival Cross-ratio Left truncation Pseudo-partial likelihood Right censoring Lin, Xihong aut Nan, Bin aut Enthalten in Lifetime data analysis Springer US, 1995 20(2013), 1 vom: 23. Mai, Seite 23-37 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:20 year:2013 number:1 day:23 month:05 pages:23-37 https://doi.org/10.1007/s10985-013-9263-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 20 2013 1 23 05 23-37 |
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Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. © Springer Science+Business Media New York 2013 |
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Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. © Springer Science+Business Media New York 2013 |
abstract_unstemmed |
Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted. © Springer Science+Business Media New York 2013 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2067136720</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503171438.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2013 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10985-013-9263-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2067136720</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10985-013-9263-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hu, Tianle</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Cross-ratio estimation for bivariate failure times with left truncation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media New York 2013</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bivariate survival</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cross-ratio</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Left truncation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Pseudo-partial likelihood</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Right censoring</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lin, Xihong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Nan, Bin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Lifetime data analysis</subfield><subfield code="d">Springer US, 1995</subfield><subfield code="g">20(2013), 1 vom: 23. 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