145 related articles for article (PubMed ID: 25140216)
1. Selection of Variables that Influence Drug Injection in Prison: Comparison of Methods with Multiple Imputed Data Sets.
Haji-Maghsoudi S; Haghdoost AA; Baneshi MR
Addict Health; 2014; 6(1-2):36-44. PubMed ID: 25140216
[TBL] [Abstract][Full Text] [Related]
2. Influence of pattern of missing data on performance of imputation methods: an example using national data on drug injection in prisons.
Haji-Maghsoudi S; Haghdoost AA; Rastegari A; Baneshi MR
Int J Health Policy Manag; 2013 Jun; 1(1):69-77. PubMed ID: 24596839
[TBL] [Abstract][Full Text] [Related]
3. The development and validation of prognostic models for overall survival in the presence of missing data in the training dataset: a strategy with a detailed example.
Royle KL; Cairns DA
Diagn Progn Res; 2021 Aug; 5(1):14. PubMed ID: 34344484
[TBL] [Abstract][Full Text] [Related]
4. Prevention of Disease Complications through Diagnostic Models: How to Tackle the Problem of Missing Data?
Baneshi M; Faramarzi H; Marzban M
Iran J Public Health; 2012; 41(1):66-72. PubMed ID: 23113124
[TBL] [Abstract][Full Text] [Related]
5. How should variable selection be performed with multiply imputed data?
Wood AM; White IR; Royston P
Stat Med; 2008 Jul; 27(17):3227-46. PubMed ID: 18203127
[TBL] [Abstract][Full Text] [Related]
6. Variable selection for multiply-imputed data with application to dioxin exposure study.
Chen Q; Wang S
Stat Med; 2013 Sep; 32(21):3646-59. PubMed ID: 23526243
[TBL] [Abstract][Full Text] [Related]
7. Multiple imputation in survival models: applied on breast cancer data.
Baneshi MR; Talei AR
Iran Red Crescent Med J; 2011 Aug; 13(8):544-9. PubMed ID: 22737525
[TBL] [Abstract][Full Text] [Related]
8. Covariate Selection for Multilevel Models with Missing Data.
Marino M; Buxton OM; Li Y
Stat (Int Stat Inst); 2017; 6(1):31-46. PubMed ID: 28239457
[TBL] [Abstract][Full Text] [Related]
9. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
10. Propensity score analysis with partially observed covariates: How should multiple imputation be used?
Leyrat C; Seaman SR; White IR; Douglas I; Smeeth L; Kim J; Resche-Rigon M; Carpenter JR; Williamson EJ
Stat Methods Med Res; 2019 Jan; 28(1):3-19. PubMed ID: 28573919
[TBL] [Abstract][Full Text] [Related]
11. A flexible approach for variable selection in large-scale healthcare database studies with missing covariate and outcome data.
Lin JJ; Hu L; Huang C; Jiayi J; Lawrence S; Govindarajulu U
BMC Med Res Methodol; 2022 May; 22(1):132. PubMed ID: 35508974
[TBL] [Abstract][Full Text] [Related]
12. Prognostic models for identifying risk of poor outcome in people with acute ankle sprains: the SPRAINED development and external validation study.
Keene DJ; Schlüssel MM; Thompson J; Hagan DA; Williams MA; Byrne C; Goodacre S; Cooke M; Gwilym S; Hormbrey P; Bostock J; Haywood K; Wilson D; Collins GS; Lamb SE
Health Technol Assess; 2018 Nov; 22(64):1-112. PubMed ID: 30474592
[TBL] [Abstract][Full Text] [Related]
13. Multiple imputation of multiple multi-item scales when a full imputation model is infeasible.
Plumpton CO; Morris T; Hughes DA; White IR
BMC Res Notes; 2016 Jan; 9():45. PubMed ID: 26809812
[TBL] [Abstract][Full Text] [Related]
14. Variable Selection in the Presence of Missing Data: Imputation-based Methods.
Zhao Y; Long Q
Wiley Interdiscip Rev Comput Stat; 2017; 9(5):. PubMed ID: 29085552
[TBL] [Abstract][Full Text] [Related]
15. Multiple imputation using chained equations for missing data in survival models: applied to multidrug-resistant tuberculosis and HIV data.
Mbona SV; Ndlovu P; Mwambi H; Ramroop S
J Public Health Afr; 2023 Aug; 14(8):2388. PubMed ID: 37753435
[TBL] [Abstract][Full Text] [Related]
16. A simple pooling method for variable selection in multiply imputed datasets outperformed complex methods.
Panken AM; Heymans MW
BMC Med Res Methodol; 2022 Aug; 22(1):214. PubMed ID: 35927610
[TBL] [Abstract][Full Text] [Related]
17. Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis.
Eekhout I; van de Wiel MA; Heymans MW
BMC Med Res Methodol; 2017 Aug; 17(1):129. PubMed ID: 28830466
[TBL] [Abstract][Full Text] [Related]
18. Factors Influencing Drug Injection History among Prisoners: A Comparison between Classification and Regression Trees and Logistic Regression Analysis.
Rastegari A; Haghdoost AA; Baneshi MR
Addict Health; 2013; 5(1-2):7-15. PubMed ID: 24494152
[TBL] [Abstract][Full Text] [Related]
19. Does the missing data imputation method affect the composition and performance of prognostic models?
Baneshi MR; Talei AR
Iran Red Crescent Med J; 2012 Jan; 14(1):31-6. PubMed ID: 22737551
[TBL] [Abstract][Full Text] [Related]
20. Imputation and variable selection in linear regression models with missing covariates.
Yang X; Belin TR; Boscardin WJ
Biometrics; 2005 Jun; 61(2):498-506. PubMed ID: 16011697
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
