Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research
出版年份 2012 全文链接
标题
Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research
作者
关键词
-
出版物
BMC Medical Research Methodology
Volume 12, Issue 1, Pages -
出版商
Springer Nature
发表日期
2012-12-06
DOI
10.1186/1471-2288-12-184
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Alternative analyses for handling incomplete follow-up in the intention-to-treat analysis: the randomized controlled trial of balloon kyphoplasty versus non-surgical care for vertebral compression fracture (FREE)
- (2012) Jonas Ranstam et al. BMC Medical Research Methodology
- Multiple imputation for estimating hazard ratios and predictive abilities in case-cohort surveys
- (2012) Helena Marti et al. BMC Medical Research Methodology
- A review of the reporting and handling of missing data in cohort studies with repeated assessment of exposure measures
- (2012) Amalia Karahalios et al. BMC Medical Research Methodology
- Analyzing repeated data collected by mobile phones and frequent text messages. An example of Low back pain measured weekly for 18 weeks
- (2012) Iben Axén et al. BMC Medical Research Methodology
- Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
- (2012) Shaun R Seaman et al. BMC Medical Research Methodology
- Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study
- (2011) Andrea Marshall et al. BMC Medical Research Methodology
- Imputation of missing values of tumour stage in population-based cancer registration
- (2011) Nora Eisemann et al. BMC Medical Research Methodology
- Performance of logistic regression modeling: beyond the number of events per variable, the role of data structure
- (2011) Delphine S. Courvoisier et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Multiple imputation for estimation of an occurrence rate in cohorts with attrition and discrete follow-up time points: a simulation study
- (2010) Noémie Soullier et al. BMC Medical Research Methodology
- Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study
- (2010) Andrea Marshall et al. BMC Medical Research Methodology
- A short screening instrument for mental health problems: The Symptom Checklist-27 (SCL-27) in Poland and Germany
- (2010) Jochen Hardt et al. INTERNATIONAL JOURNAL OF PSYCHIATRY IN CLINICAL PRACTICE
- Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example
- (2010) Mirjam J. Knol et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- The use and reporting of multiple imputation in medical research - a review
- (2010) A. Mackinnon JOURNAL OF INTERNAL MEDICINE
- Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values
- (2010) Ian R. White et al. STATISTICS IN MEDICINE
- Multiple imputation of missing dual-energy X-ray absorptiometry data in the National Health and Nutrition Examination Survey
- (2010) Nathaniel Schenker et al. STATISTICS IN MEDICINE
- Multiple imputation using chained equations: Issues and guidance for practice
- (2010) Ian R. White et al. STATISTICS IN MEDICINE
- Impact of non-normal random effects on inference by multiple imputation: A simulation assessment
- (2009) Recai M. Yucel et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
- The Effect of Auxiliary Variables and Multiple Imputation on Parameter Estimation in Confirmatory Factor Analysis
- (2009) Jin Eun Yoo EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT
- Multiple Imputation Methods for Treatment Noncompliance and Nonresponse in Randomized Clinical Trials
- (2008) L. Taylor et al. BIOMETRICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More