LDR | | 02089nam u200625 4500 |
001 | | 000000485524 |
005 | | 20230213151844 |
008 | | 230117s2021 |||||||||||||||||c||eng d |
020 | |
▼a 9798352972243 |
035 | |
▼a (MiAaPQ)AAI29703356 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 616 |
100 | 1 |
▼a Wang, Xianling. |
245 | 10 |
▼a Latent Variable Models for Analyses of Diagnostic Tests and Regressionanalyses With Hierarchical Missing Covariates. |
260 | |
▼a [S.l.]:
▼b University of Pittsburgh.,
▼c 2021. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2021. |
300 | |
▼a 75 p. |
500 | |
▼a Source: Dissertations Abstracts International, Volume: 84-05, Section: A. |
500 | |
▼a Advisor: Yabes, Jonathan Guerrero;Tang, Lu;McKennan, Christopher Gordon;Kang, Chaeryon;Tang, Gong. |
502 | 1 |
▼a Thesis (Ph.D.)--University of Pittsburgh, 2021. |
506 | |
▼a This item must not be sold to any third party vendors. |
590 | |
▼a School code: 0178. |
650 | 4 |
▼a Clinical medicine. |
650 | 4 |
▼a Disease. |
650 | 4 |
▼a Diagnostic tests. |
650 | 4 |
▼a Item response theory. |
650 | 4 |
▼a Breast cancer. |
650 | 4 |
▼a Patients. |
650 | 4 |
▼a Quality of life. |
650 | 4 |
▼a Growth models. |
650 | 4 |
▼a Electronic health records. |
650 | 4 |
▼a Medical prognosis. |
650 | 4 |
▼a Quantitative psychology. |
650 | 4 |
▼a Maximum likelihood method. |
650 | 4 |
▼a Tumors. |
650 | 4 |
▼a Chemotherapy. |
650 | 4 |
▼a Parameter estimation. |
650 | 4 |
▼a Information science. |
650 | 4 |
▼a Medicine. |
650 | 4 |
▼a Oncology. |
650 | 4 |
▼a Psychology. |
690 | |
▼a 0632 |
690 | |
▼a 0723 |
690 | |
▼a 0564 |
690 | |
▼a 0992 |
690 | |
▼a 0621 |
710 | 20 |
▼a University of Pittsburgh. |
773 | 0 |
▼t Dissertations Abstracts International
▼g 84-05A. |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0178 |
791 | |
▼a Ph.D. |
792 | |
▼a 2021 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T16620235
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 202302
▼f 2023 |
990 | |
▼a ***1012033 |
991 | |
▼a E-BOOK |