Can one assess whether missing data are missing at random in medical studies?
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Predicting lung cancer prior to surgical resection in patients with lung nodulesCombining Fourier and lagged k-nearest neighbor imputation for biomedical time series data.Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels.What impact do assumptions about missing data have on conclusions? A practical sensitivity analysis for a cancer survival registry.Semiparametric approach for non-monotone missing covariates in a parametric regression modelTrajectories of musculoskeletal shoulder pain after spinal cord injury: Identification and predictorsOn weighting approaches for missing data.Allowing for missing outcome data and incomplete uptake of randomised interventions, with application to an Internet-based alcohol trialGeriatric impairments and disability: the cardiovascular health study.Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data.Predictors of drop-out in a multi-centre longitudinal study of participation and quality of life of children with cerebral palsy.A culturally adapted depression intervention for African American adults experiencing depression: Oh Happy Day.Bayesian networks for clinical decision support in lung cancer care.Risk factors for onset of disability among older persons newly diagnosed with heart failure: the Cardiovascular Health StudyDepression socialization within friendship groups at the transition to adolescence: the roles of gender and group centrality as moderators of peer influence.Including all individuals is not enough: lessons for intention-to-treat analysis.Longitudinal multiple imputation approaches for body mass index or other variables with very low individual-level variability: the mibmi command in StataThe use of missingness screens in clinical epidemiologic research has implications for regression modeling.A structural equation model of the developmental origins of blood pressureRisk-stratified imputation in survival analysis.Validation of a short form Wisconsin Upper Respiratory Symptom Survey (WURSS-21).Parent Engagement and School Readiness: Effects of the Getting Ready Intervention on Preschool Children's Social-Emotional Competencies.Defining Cancer Subtypes With Distinctive Etiologic Profiles: An Application to the Epidemiology of Melanoma.Long-term trajectories of patients with neck pain and low back pain presenting to chiropractic care: A latent class growth analysis.A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome.Aboriginal and Torres Strait Islander oral health and its impact among adults: A cross-sectional study.Longitudinal associations among fathers' perception of coparenting, partner relationship quality, and paternal stress during early childhood.MCAR is not necessary for the complete cases to constitute a simple random subsample of the target sample.Modeling a Predictive Energy Equation Specific for Maintenance Hemodialysis.Outlying observations and missing values: how should they be handled?Validation studies for population-based intervention coverage indicators: design, analysis, and interpretationA contribution on the nature and treatment of missing data in large market surveys
P2860
Q30610197-00099276-AD80-47A7-BCC7-85E234938F88Q31007505-A29C220C-4FE5-4890-9DFF-D6E647BE11D8Q31133061-9095BC36-7D22-4E93-AE4B-D4250D9BDBB6Q31159860-D5611731-C4F4-479D-9C92-94D0FDC3D796Q33769814-F1D110E4-8DAB-4FE2-A4D4-436143170A00Q33782222-7E8F7FB0-0E32-4B2F-B03C-C19D46CA10B6Q33943154-CF36D8A3-6574-4D82-8788-63897590567DQ34030891-9D030A11-7902-479D-8734-7EFF45762FF1Q34157375-A414AC4C-56AC-491E-B3EC-C2936FF28656Q34297674-92893954-17E0-463B-83B3-2B7449B2C8BEQ34306654-2D6369C4-E61F-47BB-81EC-9C709508052BQ35039815-D35F3F69-784D-4216-9656-D0CF7F5C3B2BQ35064151-675C1C4C-B193-4AF2-9383-2FD1C6104FD6Q35188799-8BA27D88-66FF-4A4B-96B1-FD8E7FD4ADFEQ35963902-53F3657A-8040-45B4-96A9-0C07F3D3E009Q36191875-6C2249E1-8B13-4E34-9C08-0012060CA1C9Q36249532-F090A57B-680D-4FD3-9D56-0107CF934E1FQ36744346-2002F92A-DD13-4A55-B0DF-A46087F32DA5Q37146249-BCEA43AE-8AFA-4F69-BD18-F75E20F1C87AQ37253974-AE8F7140-7D61-48D0-9DCD-6876000E3B42Q37356135-81D383AB-40FD-43EB-A5E0-47C08E058E8CQ37666667-93AD7A9C-02E2-45E2-A385-AEAFBC1407EDQ38731109-F9ABAEF6-1ADB-4527-861C-E9621D387770Q40058072-F548FAC6-F7F8-450E-B14D-F1EF9C86DACDQ40196067-B300B86F-A8CC-4983-8D4C-3E26E6FFA225Q40386911-F6C6B3BB-73FD-4F76-8236-E2BFE2C49218Q42628273-8CB397DE-8F31-479F-A8C5-46B0E8154C30Q44192397-91D82B45-DBE9-4BE3-BDC8-0DA49C6FED93Q47351135-7E3E3EAF-EF5C-4438-9938-85412FBE0F19Q51896280-843CA8CD-EF00-45B6-A8FA-8C8F4A9B2CEDQ57946172-EDD5051F-0A1C-4FA2-8A51-F01458A8CA2CQ58137896-DDB7F4A2-5CA9-4136-8FA6-831C0307FF36
P2860
Can one assess whether missing data are missing at random in medical studies?
description
2006 nî lūn-bûn
@nan
2006 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
name
Can one assess whether missing data are missing at random in medical studies?
@ast
Can one assess whether missing data are missing at random in medical studies?
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type
label
Can one assess whether missing data are missing at random in medical studies?
@ast
Can one assess whether missing data are missing at random in medical studies?
@en
prefLabel
Can one assess whether missing data are missing at random in medical studies?
@ast
Can one assess whether missing data are missing at random in medical studies?
@en
P2860
P1476
Can one assess whether missing data are missing at random in medical studies?
@en
P2093
Gail E Tudor
Richard F Potthoff
P2860
P304
P356
10.1191/0962280206SM448OA
P577
2006-06-01T00:00:00Z