Regression analysis of current status data in the presence of a cured subgroup and dependent censoring
This paper discusses regression analysis of current status data, a type of failure time data where each study subject is observed only once, in the presence of dependent censoring. Furthermore, there may exist a cured subgroup, meaning that a proportion of study subjects are not susceptible to the f...
Saved in:
| Published in | Lifetime data analysis Vol. 23; no. 4; pp. 626 - 650 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.10.2017
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | This paper discusses regression analysis of current status data, a type of failure time data where each study subject is observed only once, in the presence of dependent censoring. Furthermore, there may exist a cured subgroup, meaning that a proportion of study subjects are not susceptible to the failure event of interest. For the problem, we develop a sieve maximum likelihood estimation approach with the use of latent variables and Bernstein polynomials. For the determination of the proposed estimators, an EM algorithm is developed and the asymptotic properties of the estimators are established. Extensive simulation studies are conducted and indicate that the proposed method works well for practical situations. A motivating application from a tumorigenicity experiment is also provided. |
|---|---|
| AbstractList | This paper discusses regression analysis of current status data, a type of failure time data where each study subject is observed only once, in the presence of dependent censoring. Furthermore, there may exist a cured subgroup, meaning that a proportion of study subjects are not susceptible to the failure event of interest. For the problem, we develop a sieve maximum likelihood estimation approach with the use of latent variables and Bernstein polynomials. For the determination of the proposed estimators, an EM algorithm is developed and the asymptotic properties of the estimators are established. Extensive simulation studies are conducted and indicate that the proposed method works well for practical situations. A motivating application from a tumorigenicity experiment is also provided. This paper discusses regression analysis of current status data, a type of failure time data where each study subject is observed only once, in the presence of dependent censoring. Furthermore, there may exist a cured subgroup, meaning that a proportion of study subjects are not susceptible to the failure event of interest. For the problem, we develop a sieve maximum likelihood estimation approach with the use of latent variables and Bernstein polynomials. For the determination of the proposed estimators, an EM algorithm is developed and the asymptotic properties of the estimators are established. Extensive simulation studies are conducted and indicate that the proposed method works well for practical situations. A motivating application from a tumorigenicity experiment is also provided.This paper discusses regression analysis of current status data, a type of failure time data where each study subject is observed only once, in the presence of dependent censoring. Furthermore, there may exist a cured subgroup, meaning that a proportion of study subjects are not susceptible to the failure event of interest. For the problem, we develop a sieve maximum likelihood estimation approach with the use of latent variables and Bernstein polynomials. For the determination of the proposed estimators, an EM algorithm is developed and the asymptotic properties of the estimators are established. Extensive simulation studies are conducted and indicate that the proposed method works well for practical situations. A motivating application from a tumorigenicity experiment is also provided. |
| Author | Liu, Yeqian Hu, Tao Sun, Jianguo |
| Author_xml | – sequence: 1 givenname: Yeqian surname: Liu fullname: Liu, Yeqian organization: Department of Mathematical Sciences, Middle Tennessee State University – sequence: 2 givenname: Tao surname: Hu fullname: Hu, Tao email: hutaomath@foxmail.com organization: School of Mathematical Sciences, Capital Normal University – sequence: 3 givenname: Jianguo surname: Sun fullname: Sun, Jianguo organization: Department of Statistics, University of Missouri |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27696128$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9kUtr3DAURkVJaB7tD-imCLLpxo0efkjLENImECiEdC30uJ568EiOrr1Ifn1lZgIlkK4kwTkX3e87I0cxRSDkC2ffOWPdJXKmVVMx3lZaKlG9fCCnvOlEpUWtj8pdKlZ1qmMn5Axxy4qjW_2RnIiu1S0X6pT0D7DJgDikSG204zMOSFNP_ZIzxJnibOcFabCzpUOk8x-gU-Ehelgxu4IQKC5uk9MylRmBBpgghtX2EDHlIW4-kePejgifD-c5-f3j5vH6trr_9fPu-uq-8rVUcwVSQWCuV9I3oHjobR2CFq5tylP7VtWNE8xa7WSwXEOQTmlbO8e9Fazr5Dn5tp875fS0AM5mN6CHcbQR0oKGK9lIVXZnBb14g27TkksEhdK1aLgoKRXq64Fa3A6CmfKws_nZvCZYgG4P-JwQM_TGDyWzkuec7TAazszaldl3ZUpXZu3KvBSTvzFfh__PEXsHpzVWyP98-l3pLybTp-E |
| CitedBy_id | crossref_primary_10_1080_02331888_2020_1783541 crossref_primary_10_1080_03610918_2022_2118780 crossref_primary_10_1177_09622802221111559 crossref_primary_10_1007_s10985_020_09510_4 crossref_primary_10_1007_s40304_021_00274_3 crossref_primary_10_1002_bimj_202000288 crossref_primary_10_1002_bimj_202000254 crossref_primary_10_1007_s10985_020_09507_z crossref_primary_10_1007_s10985_021_09515_7 crossref_primary_10_1016_j_spl_2019_108621 crossref_primary_10_1111_biom_13202 crossref_primary_10_1002_pst_2048 crossref_primary_10_1002_sim_8910 crossref_primary_10_1080_00949655_2024_2383987 crossref_primary_10_1007_s00180_024_01528_8 crossref_primary_10_1007_s10651_022_00549_0 crossref_primary_10_1007_s11749_024_00961_7 |
| Cites_doi | 10.1006/jmva.2000.1975 10.1198/016214506000000311 10.1002/9781118032985 10.1198/jasa.2009.tm07494 10.1080/01621459.1158113 10.1016/S0167-7152(01)00105-5 10.1111/j.0006-341X.2002.00510.x 10.1093/biomet/92.3.573 10.1080/01621459.1997.10474050 10.1214/aos/1032894452 10.1007/BF00985261 10.1214/aos/1030741085 10.1198/jasa.2009.tm08033 10.1007/978-1-4757-2545-2 10.2307/2529885 10.1002/bimj.201100131 10.1111/j.1467-9469.2005.00415.x 10.2307/2532047 10.1214/aos/1176325486 10.1198/016214505000001122 10.1002/sim.2001 10.1186/2051-1426-1-18 10.1007/978-1-4612-5254-2 10.1080/01621459.1996.10476939 10.1093/biomet/85.2.289 10.1111/j.2517-6161.1982.tb01203.x 10.1002/sim.3715 10.1111/j.1467-9868.2007.00589.x 10.1093/biomet/91.2.331 |
| ContentType | Journal Article |
| Copyright | Springer Science+Business Media New York 2016 Lifetime Data Analysis is a copyright of Springer, 2017. |
| Copyright_xml | – notice: Springer Science+Business Media New York 2016 – notice: Lifetime Data Analysis is a copyright of Springer, 2017. |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7WY 7WZ 7X7 7XB 87Z 88C 88E 88I 8AO 8C1 8FE 8FG 8FI 8FJ 8FK 8FL ABJCF ABUWG AFKRA AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG FYUFA F~G GHDGH GNUQQ HCIFZ K60 K6~ K9. L.- L6V M0C M0S M0T M1P M2P M7S PHGZM PHGZT PJZUB PKEHL PPXIY PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PRINS PTHSS Q9U 7X8 |
| DOI | 10.1007/s10985-016-9382-z |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) ProQuest ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest_Health & Medical Collection ProQuest Central (purchase pre-March 2016) ABI/INFORM Global (Alumni Edition) Healthcare Administration Database (Alumni) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest Pharma Collection Public Health Database ProQuest SciTech Collection ProQuest Technology Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni Edition) ProQuest Materials Science & Engineering ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central Business Premium Collection Technology Collection ProQuest One Community College ProQuest Central Korea Business Premium Collection (Alumni) Health Research Premium Collection ABI/INFORM Global (Corporate) Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection ProQuest Health & Medical Complete (Alumni) ABI/INFORM Professional Advanced ProQuest Engineering Collection ABI/INFORM Global (OCUL) Health & Medical Collection (Alumni Edition) Healthcare Administration Database (Proquest) PML(ProQuest Medical Library) Science Database Engineering Database ProQuest Central Premium ProQuest One Academic ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection ProQuest Central Basic MEDLINE - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) ProQuest Business Collection (Alumni Edition) ProQuest Central Student ProQuest Central Essentials SciTech Premium Collection ProQuest Central China ABI/INFORM Complete ProQuest One Applied & Life Sciences Health Research Premium Collection Health & Medical Research Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Business Premium Collection ABI/INFORM Global Engineering Database ProQuest Science Journals (Alumni Edition) ProQuest One Academic Eastern Edition ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) ProQuest Business Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest One Academic UKI Edition ProQuest Health Management (Alumni Edition) ProQuest One Academic ProQuest One Academic (New) ABI/INFORM Global (Corporate) ProQuest One Business Technology Collection ProQuest One Academic Middle East (New) ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Pharma Collection ProQuest Central ABI/INFORM Professional Advanced ProQuest Health & Medical Research Collection ProQuest Engineering Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea ABI/INFORM Complete (Alumni Edition) ProQuest Public Health ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Science Journals ProQuest Health Management ProQuest SciTech Collection ProQuest Medical Library Materials Science & Engineering Collection ProQuest One Business (Alumni) ProQuest Central (Alumni) Business Premium Collection (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE ProQuest Business Collection (Alumni Edition) MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine Economics Mathematics Statistics |
| EISSN | 1572-9249 |
| EndPage | 650 |
| ExternalDocumentID | 27696128 10_1007_s10985_016_9382_z |
| Genre | Research Support, U.S. Gov't, Non-P.H.S Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural |
| GroupedDBID | --- -52 -5D -5G -BR -EM -Y2 -~C .86 .VR 06D 0R~ 0VY 1N0 1SB 2.D 203 29L 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 3-Y 30V 3V. 4.4 406 408 409 40D 40E 44B 53G 5GY 5QI 5VS 67Z 6NX 78A 7WY 7X7 88E 88I 8AO 8C1 8FE 8FG 8FI 8FJ 8FL 8FW 8TC 8UJ 8VB 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAWTL AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJCF ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACGOD ACHSB ACHXU ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACZOJ ADBBV ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHMBA AHQJS AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ AKVCP ALIPV ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG AQUVI ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BAPOH BBWZM BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ BSONS BVXVI CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 DWQXO EBD EBLON EBS EBU EIOEI EJD EMB EMOBN ESBYG F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC FYUFA GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GROUPED_ABI_INFORM_RESEARCH GXS H13 HCIFZ HF~ HG5 HG6 HMCUK HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K1G K60 K6~ KDC KOV KOW L6V LAK LLZTM M0C M0T M1P M2P M4Y M7S MA- N2Q NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P9R PF0 PQBIZ PQBZA PQQKQ PROAC PSQYO PT4 PT5 PTHSS Q2X QOK QOS QWB R4E R89 R9I RHV RIG RNI ROL RPX RRX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCLPG SDD SDH SDM SHX SISQX SJYHP SMT SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SV3 SZN T13 T16 TEORI TH9 TN5 TSG TSK TSV TUC U2A U9L UG4 UKHRP UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z7U Z81 Z83 Z8U Z8W Z92 ZL0 ZMTXR ZWQNP ~8M ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ACSTC ADHKG AEZWR AFDZB AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT CGR CUY CVF ECM EIF NPM 7XB 8FK ABRTQ K9. L.- PJZUB PKEHL PPXIY PQEST PQGLB PQUKI PRINS PUEGO Q9U 7X8 |
| ID | FETCH-LOGICAL-c438t-e38ed0bf83c5e81dfa4dd92b655e89c6845b20aa9b3da19ed3b89a4bb1ca20773 |
| IEDL.DBID | U2A |
| ISSN | 1380-7870 1572-9249 |
| IngestDate | Fri Jul 11 09:39:15 EDT 2025 Sat Aug 23 14:35:02 EDT 2025 Thu Apr 03 06:58:53 EDT 2025 Thu Apr 24 22:56:15 EDT 2025 Tue Jul 01 01:43:34 EDT 2025 Fri Feb 21 02:25:29 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Interval censoring Cure rate model EM algorithm Bernstein polynomial |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c438t-e38ed0bf83c5e81dfa4dd92b655e89c6845b20aa9b3da19ed3b89a4bb1ca20773 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| PMID | 27696128 |
| PQID | 1942512276 |
| PQPubID | 26261 |
| PageCount | 25 |
| ParticipantIDs | proquest_miscellaneous_1835389610 proquest_journals_1942512276 pubmed_primary_27696128 crossref_citationtrail_10_1007_s10985_016_9382_z crossref_primary_10_1007_s10985_016_9382_z springer_journals_10_1007_s10985_016_9382_z |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2017-10-01 |
| PublicationDateYYYYMMDD | 2017-10-01 |
| PublicationDate_xml | – month: 10 year: 2017 text: 2017-10-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York – name: United States |
| PublicationSubtitle | An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data |
| PublicationTitle | Lifetime data analysis |
| PublicationTitleAbbrev | Lifetime Data Anal |
| PublicationTitleAlternate | Lifetime Data Anal |
| PublicationYear | 2017 |
| Publisher | Springer US Springer Nature B.V |
| Publisher_xml | – name: Springer US – name: Springer Nature B.V |
| References | MaSCure model with current status dataStat Sin20091923324924878871153.62076 KalbfleischJDPrenticeRLThe statistical analysis of failure time data2002HobokenWiley10.1002/97811180329851012.62104 FinkelsteinDMSchoenfeldDAAnalysis of multiple tumor data from a rodent carcinogenicity experimentBiometrics19894521923099944710.2307/25320470715.62229 FangHLiGSunJMaximum likelihood estimation in a semiparametric logistic/proportional-hazards mixture modelScand J Stat2005325975213680210.1111/j.1467-9469.2005.00415.x1087.62109 OthusMLiYTiwariRA class of semiparametric mixture cure survival models with dependent censoringJ Am Stat Assoc200710412411250275024710.1198/jasa.2009.tm0803306444380 RossiniAJTsiatisAAA semiparametric proportional odds regression model for the analysis of current status dataJ Am Stat Assoc199691713721139573810.1080/01621459.1996.104769390869.62082 LouisTAFinding the observed information matrix when using the EM algorithmJ R Stat Soc Ser B1982402262336762130488.62018 Zhou Q, Tao Hu, Sun J (2016) A sieve semiparametric maximum likelihood approach for regression analysis of bivariate interval-censored failure time data. J Am Stat Assoc. doi:10.1080/01621459.1158113 SunJThe statistical analysis of interval-censored failure time data2006New YorkSpringer1127.62090 ZhangZSunJSunLStatistical analysis of current status data with informative observation timesStat Med20052413991407213456610.1002/sim.2001 LiuHaoShenYuA semiparametric regression cure model for interval censored dataJ Am Stat Assoc200910411681178275024210.1198/jasa.2009.tm0749406444373 ChenCLuTChenMHsuCSemiparametric transformation models for current status data with informative censoringBiom J201254641656296776510.1002/bimj.20110013106089951 HuangJRossiniAJSieve estimation for the proportional odds failure time regression model with interval censoringJ Am Stat Assoc199792960967148212610.1080/01621459.1997.104740500889.62082 HuangXWolfeRA frailty model for informative censoringBiometics200258510520192554810.1111/j.0006-341X.2002.00510.x1210.62129 ShenXOn methods of sieves and penalizationAnn Stat19972525552591160441610.1214/aos/10307410850895.62041 LuWYingZOn semiparametric transformation cure modelsBiometrika200491331343208130510.1093/biomet/91.2.3311079.62115 PollardDConvergence of stochastic processes1984New YorkSpringer10.1007/978-1-4612-5254-20544.60045 BurnhamKPAndersonDRModel selection and multimodel inference: a practical information-theoretic approach2002New YorkSpringer1005.62007 ChenTStatistical issues and challenges in immuno-oncologyJ Immunother Cancer201311810.1186/2051-1426-1-18 LinDOakesDYingZAdditive hazards regression with current status dataBiometrika199885289298164911510.1093/biomet/85.2.2890938.62121 FletcherRPractical methods of optimization19872New YorkWiley0905.65002 ChenMTongXSunJA frailty model approach for regression analysis of multivariate current status dataStat Med20092834243426274437210.1002/sim.3715 JewellNPvan der LaanMJGeneralizations of current status data with applicationsLifetime Data Anal1995110110910.1007/BF009852610822.62093 LiYTiwariRGuhaSMixture cure survival models with dependent censoringJ R Stat Soc Series B200769285306232375410.1111/j.1467-9868.2007.00589.x LamKFXueHA semiparametric regression cure model with current status dataBiometrika200592573586220264710.1093/biomet/92.3.5731152.62336 FarewellVTThe use of mixture models for the analysis of survival data with longterm survivorsBiometrics1982381041104610.2307/2529885 Van der VarrtAWWellnerJAWeak convergence and empirical processes1996New YorkSpringer10.1007/978-1-4757-2545-2 ZengDYinGIbrahimJGSemiparametric transformation models for survival data with a cure fractionJ Am Stat Assoc2006101670684225618210.1198/0162145050000011221119.62381 LorentzGGBernstein polynomials19531TorontoUniversity Toronto Press0051.05001 ChenMIbrahimJSinhaDBayesian inference for multivariate survival data with a cure fractionJ Multivar Anal200280101126188983610.1006/jmva.2000.19751003.62091 HuangJEfficient estimation for the proportional hazard model with interval censoringAnn Stat199624540568139497510.1214/aos/10328944520859.62032 ChangISWenCCWuYJA profile likelihood theory for the correlated gamma-frailty model with current status family dataStat Sin2007171023104624086451133.62021 ChenXFanYTsyrennikovVEfficient estimation of semiparametric multivariate copula modelsJ Am Stat Assoc200610112281240232830910.1198/0162145060000003111120.62312 LiCTaylorJMGJudyPSIdentifiability of cure modelsStat Probab Lett200154389395186138410.1016/S0167-7152(01)00105-50999.62075 Rondeau V, Schaffner E, Corbiere F, Gonzalez J and Pelissier S (2011) Cure frailty models for survival data: application to recurrences for breast cancer and to hospital readmissions for colorectal cancer. Stat Methods Med Res 1–18 ShenXWongWHConvergence rate of sieve estimatesAnn Stat199422580615129253110.1214/aos/11763254860805.62008 NP Jewell (9382_CR15) 1995; 1 JD Kalbfleisch (9382_CR16) 2002 Y Li (9382_CR19) 2007; 69 D Zeng (9382_CR34) 2006; 101 Hao Liu (9382_CR21) 2009; 104 H Fang (9382_CR8) 2005; 32 KF Lam (9382_CR17) 2005; 92 R Fletcher (9382_CR11) 1987 Z Zhang (9382_CR35) 2005; 24 M Chen (9382_CR5) 2009; 28 VT Farewell (9382_CR9) 1982; 38 M Othus (9382_CR26) 2007; 104 M Chen (9382_CR3) 2002; 80 C Chen (9382_CR6) 2012; 54 AW Varrt Van der (9382_CR33) 1996 J Huang (9382_CR13) 1997; 92 9382_CR28 DM Finkelstein (9382_CR10) 1989; 45 X Shen (9382_CR31) 1994; 22 T Chen (9382_CR7) 2013; 1 C Li (9382_CR18) 2001; 54 S Ma (9382_CR25) 2009; 19 D Lin (9382_CR20) 1998; 85 W Lu (9382_CR24) 2004; 91 D Pollard (9382_CR27) 1984 KP Burnham (9382_CR1) 2002 GG Lorentz (9382_CR22) 1953 X Chen (9382_CR4) 2006; 101 J Sun (9382_CR32) 2006 TA Louis (9382_CR23) 1982; 40 IS Chang (9382_CR2) 2007; 17 J Huang (9382_CR12) 1996; 24 AJ Rossini (9382_CR29) 1996; 91 X Shen (9382_CR30) 1997; 25 X Huang (9382_CR14) 2002; 58 9382_CR36 |
| References_xml | – reference: Van der VarrtAWWellnerJAWeak convergence and empirical processes1996New YorkSpringer10.1007/978-1-4757-2545-2 – reference: KalbfleischJDPrenticeRLThe statistical analysis of failure time data2002HobokenWiley10.1002/97811180329851012.62104 – reference: FarewellVTThe use of mixture models for the analysis of survival data with longterm survivorsBiometrics1982381041104610.2307/2529885 – reference: ChenTStatistical issues and challenges in immuno-oncologyJ Immunother Cancer201311810.1186/2051-1426-1-18 – reference: Rondeau V, Schaffner E, Corbiere F, Gonzalez J and Pelissier S (2011) Cure frailty models for survival data: application to recurrences for breast cancer and to hospital readmissions for colorectal cancer. Stat Methods Med Res 1–18 – reference: FangHLiGSunJMaximum likelihood estimation in a semiparametric logistic/proportional-hazards mixture modelScand J Stat2005325975213680210.1111/j.1467-9469.2005.00415.x1087.62109 – reference: BurnhamKPAndersonDRModel selection and multimodel inference: a practical information-theoretic approach2002New YorkSpringer1005.62007 – reference: ShenXOn methods of sieves and penalizationAnn Stat19972525552591160441610.1214/aos/10307410850895.62041 – reference: HuangJEfficient estimation for the proportional hazard model with interval censoringAnn Stat199624540568139497510.1214/aos/10328944520859.62032 – reference: HuangJRossiniAJSieve estimation for the proportional odds failure time regression model with interval censoringJ Am Stat Assoc199792960967148212610.1080/01621459.1997.104740500889.62082 – reference: ChenXFanYTsyrennikovVEfficient estimation of semiparametric multivariate copula modelsJ Am Stat Assoc200610112281240232830910.1198/0162145060000003111120.62312 – reference: LiCTaylorJMGJudyPSIdentifiability of cure modelsStat Probab Lett200154389395186138410.1016/S0167-7152(01)00105-50999.62075 – reference: MaSCure model with current status dataStat Sin20091923324924878871153.62076 – reference: ChenMIbrahimJSinhaDBayesian inference for multivariate survival data with a cure fractionJ Multivar Anal200280101126188983610.1006/jmva.2000.19751003.62091 – reference: ZhangZSunJSunLStatistical analysis of current status data with informative observation timesStat Med20052413991407213456610.1002/sim.2001 – reference: HuangXWolfeRA frailty model for informative censoringBiometics200258510520192554810.1111/j.0006-341X.2002.00510.x1210.62129 – reference: JewellNPvan der LaanMJGeneralizations of current status data with applicationsLifetime Data Anal1995110110910.1007/BF009852610822.62093 – reference: ChenMTongXSunJA frailty model approach for regression analysis of multivariate current status dataStat Med20092834243426274437210.1002/sim.3715 – reference: LamKFXueHA semiparametric regression cure model with current status dataBiometrika200592573586220264710.1093/biomet/92.3.5731152.62336 – reference: SunJThe statistical analysis of interval-censored failure time data2006New YorkSpringer1127.62090 – reference: ChenCLuTChenMHsuCSemiparametric transformation models for current status data with informative censoringBiom J201254641656296776510.1002/bimj.20110013106089951 – reference: LiYTiwariRGuhaSMixture cure survival models with dependent censoringJ R Stat Soc Series B200769285306232375410.1111/j.1467-9868.2007.00589.x – reference: ChangISWenCCWuYJA profile likelihood theory for the correlated gamma-frailty model with current status family dataStat Sin2007171023104624086451133.62021 – reference: ZengDYinGIbrahimJGSemiparametric transformation models for survival data with a cure fractionJ Am Stat Assoc2006101670684225618210.1198/0162145050000011221119.62381 – reference: RossiniAJTsiatisAAA semiparametric proportional odds regression model for the analysis of current status dataJ Am Stat Assoc199691713721139573810.1080/01621459.1996.104769390869.62082 – reference: ShenXWongWHConvergence rate of sieve estimatesAnn Stat199422580615129253110.1214/aos/11763254860805.62008 – reference: PollardDConvergence of stochastic processes1984New YorkSpringer10.1007/978-1-4612-5254-20544.60045 – reference: FinkelsteinDMSchoenfeldDAAnalysis of multiple tumor data from a rodent carcinogenicity experimentBiometrics19894521923099944710.2307/25320470715.62229 – reference: LuWYingZOn semiparametric transformation cure modelsBiometrika200491331343208130510.1093/biomet/91.2.3311079.62115 – reference: FletcherRPractical methods of optimization19872New YorkWiley0905.65002 – reference: Zhou Q, Tao Hu, Sun J (2016) A sieve semiparametric maximum likelihood approach for regression analysis of bivariate interval-censored failure time data. J Am Stat Assoc. doi:10.1080/01621459.1158113 – reference: LiuHaoShenYuA semiparametric regression cure model for interval censored dataJ Am Stat Assoc200910411681178275024210.1198/jasa.2009.tm0749406444373 – reference: LinDOakesDYingZAdditive hazards regression with current status dataBiometrika199885289298164911510.1093/biomet/85.2.2890938.62121 – reference: LorentzGGBernstein polynomials19531TorontoUniversity Toronto Press0051.05001 – reference: OthusMLiYTiwariRA class of semiparametric mixture cure survival models with dependent censoringJ Am Stat Assoc200710412411250275024710.1198/jasa.2009.tm0803306444380 – reference: LouisTAFinding the observed information matrix when using the EM algorithmJ R Stat Soc Ser B1982402262336762130488.62018 – volume: 80 start-page: 101 year: 2002 ident: 9382_CR3 publication-title: J Multivar Anal doi: 10.1006/jmva.2000.1975 – volume: 17 start-page: 1023 year: 2007 ident: 9382_CR2 publication-title: Stat Sin – volume: 101 start-page: 1228 year: 2006 ident: 9382_CR4 publication-title: J Am Stat Assoc doi: 10.1198/016214506000000311 – volume-title: The statistical analysis of failure time data year: 2002 ident: 9382_CR16 doi: 10.1002/9781118032985 – volume: 104 start-page: 1168 year: 2009 ident: 9382_CR21 publication-title: J Am Stat Assoc doi: 10.1198/jasa.2009.tm07494 – ident: 9382_CR36 doi: 10.1080/01621459.1158113 – volume: 54 start-page: 389 year: 2001 ident: 9382_CR18 publication-title: Stat Probab Lett doi: 10.1016/S0167-7152(01)00105-5 – volume: 58 start-page: 510 year: 2002 ident: 9382_CR14 publication-title: Biometics doi: 10.1111/j.0006-341X.2002.00510.x – volume: 92 start-page: 573 year: 2005 ident: 9382_CR17 publication-title: Biometrika doi: 10.1093/biomet/92.3.573 – volume: 92 start-page: 960 year: 1997 ident: 9382_CR13 publication-title: J Am Stat Assoc doi: 10.1080/01621459.1997.10474050 – volume: 24 start-page: 540 year: 1996 ident: 9382_CR12 publication-title: Ann Stat doi: 10.1214/aos/1032894452 – volume: 1 start-page: 101 year: 1995 ident: 9382_CR15 publication-title: Lifetime Data Anal doi: 10.1007/BF00985261 – volume: 25 start-page: 2555 year: 1997 ident: 9382_CR30 publication-title: Ann Stat doi: 10.1214/aos/1030741085 – volume: 19 start-page: 233 year: 2009 ident: 9382_CR25 publication-title: Stat Sin – volume: 104 start-page: 1241 year: 2007 ident: 9382_CR26 publication-title: J Am Stat Assoc doi: 10.1198/jasa.2009.tm08033 – volume-title: Weak convergence and empirical processes year: 1996 ident: 9382_CR33 doi: 10.1007/978-1-4757-2545-2 – volume: 38 start-page: 1041 year: 1982 ident: 9382_CR9 publication-title: Biometrics doi: 10.2307/2529885 – volume-title: Practical methods of optimization year: 1987 ident: 9382_CR11 – volume: 54 start-page: 641 year: 2012 ident: 9382_CR6 publication-title: Biom J doi: 10.1002/bimj.201100131 – ident: 9382_CR28 – volume: 32 start-page: 59 year: 2005 ident: 9382_CR8 publication-title: Scand J Stat doi: 10.1111/j.1467-9469.2005.00415.x – volume-title: Model selection and multimodel inference: a practical information-theoretic approach year: 2002 ident: 9382_CR1 – volume: 45 start-page: 219 year: 1989 ident: 9382_CR10 publication-title: Biometrics doi: 10.2307/2532047 – volume-title: Bernstein polynomials year: 1953 ident: 9382_CR22 – volume: 22 start-page: 580 year: 1994 ident: 9382_CR31 publication-title: Ann Stat doi: 10.1214/aos/1176325486 – volume: 101 start-page: 670 year: 2006 ident: 9382_CR34 publication-title: J Am Stat Assoc doi: 10.1198/016214505000001122 – volume: 24 start-page: 1399 year: 2005 ident: 9382_CR35 publication-title: Stat Med doi: 10.1002/sim.2001 – volume: 1 start-page: 18 year: 2013 ident: 9382_CR7 publication-title: J Immunother Cancer doi: 10.1186/2051-1426-1-18 – volume-title: Convergence of stochastic processes year: 1984 ident: 9382_CR27 doi: 10.1007/978-1-4612-5254-2 – volume: 91 start-page: 713 year: 1996 ident: 9382_CR29 publication-title: J Am Stat Assoc doi: 10.1080/01621459.1996.10476939 – volume-title: The statistical analysis of interval-censored failure time data year: 2006 ident: 9382_CR32 – volume: 85 start-page: 289 year: 1998 ident: 9382_CR20 publication-title: Biometrika doi: 10.1093/biomet/85.2.289 – volume: 40 start-page: 226 year: 1982 ident: 9382_CR23 publication-title: J R Stat Soc Ser B doi: 10.1111/j.2517-6161.1982.tb01203.x – volume: 28 start-page: 3424 year: 2009 ident: 9382_CR5 publication-title: Stat Med doi: 10.1002/sim.3715 – volume: 69 start-page: 285 year: 2007 ident: 9382_CR19 publication-title: J R Stat Soc Series B doi: 10.1111/j.1467-9868.2007.00589.x – volume: 91 start-page: 331 year: 2004 ident: 9382_CR24 publication-title: Biometrika doi: 10.1093/biomet/91.2.331 |
| SSID | ssj0007969 |
| Score | 2.2143009 |
| Snippet | This paper discusses regression analysis of current status data, a type of failure time data where each study subject is observed only once, in the presence of... |
| SourceID | proquest pubmed crossref springer |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 626 |
| SubjectTerms | Algorithms Animals Asymptotic properties Chloroprene - toxicity Computer Simulation Economic models Economics Estimators Failure analysis Female Finance Health Sciences Humans Insurance Life Tables Likelihood Functions Liver Neoplasms, Experimental - chemically induced Male Management Mathematics and Statistics Maximum likelihood estimation Medicine Mice Models, Statistical Operations Research/Decision Theory Polynomials Quality Control Rats Regression Analysis Reliability Safety and Risk Statistics Statistics for Business Statistics for Life Sciences |
| SummonAdditionalLinks | – databaseName: ProQuest_Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LaxRBEC5ivMSDaDQ6SZQWPClNZqd7ZnpOIiEhCOYgBvY29KM6CDK7cXYv-fVW9TwSCeY49JOpfnzV9VUVwMfoijyqUEnjFEodF1FaXTiJiFpHOgwrlwiyl9XFlf62LJfjg1s_0iqnMzEd1GHl-Y38hJRtvoqLuvqyvpGcNYqtq2MKjSfwlEOXMaWrXs4KV143KaXdQhlmzdWzVXNwnWsM09Yq2SgCmbf_3ksPwOYDQ2m6f85fwPMROIqvg6Rfwg52-_Ds-xx1td-HPUaOQ-DlVxB_4PXAce2EHSOPiFUUfgjIJNiTaNsLZoiKX52gbsQ6uSJ55GqWK2IQ_dYlxw_qI4gpY-5GeNJ-E3XvNVydn_08vZBjUgXptTIbicpgyF00ypdIYDVaHUJTuKqkz8ZXRpckPmsbp4JdNBiUM43Vzi28LfK6Vgew2606fAvC59YEa8vaOcIhSGp5jirEHLGgMRAzyKdf2vox4jgnvvjd3sVKZim0zDJjKbS3GXyam6yHcBuPVT6e5NSOO69v79ZJBh_mYtozbAixHa62VIdgJwE1Qo4ZvBnkO49GDamgMBl8ngR-r_P_TeXw8akcwV7BcCCRAI9hd_Nni-8IzGzc-7Ri_wK4PvL1 priority: 102 providerName: ProQuest |
| Title | Regression analysis of current status data in the presence of a cured subgroup and dependent censoring |
| URI | https://link.springer.com/article/10.1007/s10985-016-9382-z https://www.ncbi.nlm.nih.gov/pubmed/27696128 https://www.proquest.com/docview/1942512276 https://www.proquest.com/docview/1835389610 |
| Volume | 23 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1La9wwEB6aBNr0UNrtI26TRYWeWgy2JdvycRt2E1oSSujC9mT0GJVC8YZ695Jfn5H8aEqaQC4yRiPJePT4xHwzA_DB6Sxx3Bax1Bxj4VIXK5HpGBGFcLQZFjoQZM-L06X4sspXvR93O7DdB5Nk2KlvOLtV0hPNirjiBAuvdmAv91d3msTLbDZuv2UV8tilXHqqXDmaMv_Xxb-H0S2Eecs6Gg6dxXN41qNFNuvU-wIeYTOBJ4MzcTuBp2dj2FV6e3zWW8onsO9RZBeE-SW4C_zZ8V0bpvooJGztmOmCMzHvVbRtmWeLsl8Nox7ZZXBLMujFlBdEy9qtDk4g1IdlQ_bcDTN0Ew40vlewXMy_H5_GfYKF2AguNzFyiTbRTnKTIwFXp4S1VaaLnF4rU0iRkyqVqjS3Kq3Qci0rJbROjcqSsuSvYbdZN3gAzCRKWqXyUmvCJEhX9AS5dQliRmMgRpAMf7o2ffRxnwTjd_03brJXTu0ZZ1459VUEH8cml13ojfuEDwf11f0qbOu0Eh6-ZWURwfuxmtaPN4qoBtdbkiEISqCNUGQEbzq1j6NRQ6rIZASfhnlwo_O7PuXtg6TfwX7mkULgBx7C7ubPFo8I52z0FHbKVUmlPE59uTiZwt7s5MfXOT0_z8-_XUzDzL8GLJL83w |
| linkProvider | Springer Nature |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwEB6VcqAcKiivQAEjwQUUkbXzcA4IIaDa0scBtdLegh_jqhLKLmRXFf1R_EZm8iqoorceI9tjy-OxP8ffzAC8DFYmQfk81lZhnIZJiE0qbYyIaRpoM8xtS5A9zKfH6ZdZNluD34MvDNMqhz2x3aj93PE_8rd02eajWBb5-8WPmLNG8evqkEKjWxZ7-OuMrmzNu91PpN9XUu58Pvo4jfusArFLlV7GqDT6xAatXIaE1oJJvS-lzTP6LF2u04zGb0xplTeTEr2yujSptRNnZFIUiuTegJt08CZsUcVsvOAlRdmm0JsozSy9YnxF7Vz1Ss00uTwuFYHa83_PwUvg9tLDbHve7dyBzR6oig_dyroLa1hvwe2DMcprswUbjFS7QM_3IHzFk45TWwvTRzoR8yBcFwBKsOfSqhHMSBWntSAxYtG6PjnkaoYrohfNyraOJiTDiyFD71I4um23VMH7cHwt0_0A1ut5jY9AuMRob0xWWEu4B9GqBJUPCaKkPhAjSIYprVwf4ZwTbXyvLmIzsxYqZrWxFqrzCF6PTRZdeI-rKm8Peqp6S2-qi3UZwYuxmGyUH15MjfMV1SGYS8CQkGoEDzv9jr1RQyqQOoI3g8L_Ev6_oTy-eijP4db06GC_2t893HsCG5KhSEtA3Ib15c8VPiUgtbTP2tUr4Nt1m8sfYgkxiw |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1ba9VAEB5qBakPovUWrbqCviihyW4umwcRsR5aq0XEwnmLe5kVQXKO5hzE_jR_nTO5VSn2rY9hb8nOzu432W9mAJ4EK5OgfBFrqzDOQhpik0kbI2KWBdoMC9sRZI-K_ePs7Tyfb8Dv0ReGaZXjntht1H7h-B_5LhnbfBTLstgNAy3iw97s5fJ7zBmk-KZ1TKfRL5FD_PWTzLf2xcEeyfqplLM3n17vx0OGgdhlSq9iVBp9YoNWLkdCbsFk3lfSFjk9Vq7QWU7fYkxllTdphV5ZXZnM2tQZmZSlon4vweVS5SnrWDmfjL2krLp0eqnSzNgrpxvV3m2v0kyZK-JKEcA9-fdMPAN0z1zSdmff7DpcG0CreNWvshuwgc02XH0_RXxtt2GLUWsf9PkmhI_4pefXNsIMUU_EIgjXB4MS7MW0bgWzU8XXRlA3Ytm5QTnkaoYrohft2nZOJ9SHF2O23pVwZHl3tMFbcHwh030bNptFg3dBuMRob0xeWksYCNGqBJUPCaKkMRAjSMYprd0Q7ZyTbnyrT-M0sxRqZrixFOqTCJ5NTZZ9qI_zKu-McqoHrW_r0zUaweOpmPSVL2FMg4s11SHISyCRUGsEd3r5TqNRQyqQOoLno8D_6vx_r3Lv_Fd5BFdIUep3B0eH92FLMirpuIg7sLn6scYHhKlW9mG3eAV8vmht-QN0XzXB |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Regression+analysis+of+current+status+data+in+the+presence+of+a+cured+subgroup+and+dependent+censoring&rft.jtitle=Lifetime+data+analysis&rft.au=Liu%2C+Yeqian&rft.au=Hu%2C+Tao&rft.au=Sun%2C+Jianguo&rft.date=2017-10-01&rft.pub=Springer+US&rft.issn=1380-7870&rft.eissn=1572-9249&rft.volume=23&rft.issue=4&rft.spage=626&rft.epage=650&rft_id=info:doi/10.1007%2Fs10985-016-9382-z&rft.externalDocID=10_1007_s10985_016_9382_z |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1380-7870&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1380-7870&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1380-7870&client=summon |