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Volumn 7, Issue 6, 2010, Pages 634-642

Analysis of progression-free survival data using a discrete time survival model that incorporates measurements with and without diagnostic error

Author keywords

[No Author keywords available]

Indexed keywords

ANALYZER; ARTICLE; CANCER SURVIVAL; DATA ANALYSIS; DIAGNOSTIC ERROR; DISCRETE TIME SURVIVAL MODEL; INFORMATION PROCESSING; KIDNEY CANCER; MEASUREMENT ERROR; PRIORITY JOURNAL; PROGRESSION FREE SURVIVAL; SENSITIVITY AND SPECIFICITY; SIMULATION;

EID: 78650364861     PISSN: 17407745     EISSN: 17407753     Source Type: Journal    
DOI: 10.1177/1740774510384887     Document Type: Article
Times cited : (12)

References (13)
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  • 3
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    • Bross, I.1
  • 7
    • 0000534255 scopus 로고
    • Errors of measurement in statistics
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  • 8
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  • 9
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    • Palmgren, J.1
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    • Random effects models in latent class analysis for evaluating accuracy of diagnostic tests
    • Qu Y., Tan M., Kutner MH Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. Biometrics 1996 ; 52: 797-810.
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    • A randomized trial of bevacizumab, an anti-vascular endothelial growth factor antibody, for metastatic renal cancer
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.