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DOI | 10.1111/biom.12638 |
Combining Item Response Theory with Multiple Imputation to Equate Health Assessment Questionnaires | |
Gu, Chenyang1; Gutman, Roee2 | |
通讯作者 | Gu, Chenyang |
来源期刊 | BIOMETRICS
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ISSN | 0006-341X |
EISSN | 1541-0420 |
出版年 | 2017 |
卷号 | 73期号:3页码:990-998 |
英文摘要 | The assessment of patients’ functional status across the continuum of care requires a common patient assessment tool. However, assessment tools that are used in various health care settings differ and cannot be easily contrasted. For example, the Functional Independence Measure (FIM) is used to evaluate the functional status of patients who stay in inpatient rehabilitation facilities, the Minimum Data Set (MDS) is collected for all patients who stay in skilled nursing facilities, and the Outcome and Assessment Information Set (OASIS) is collected if they choose home health care provided by home health agencies. All three instruments or questionnaires include functional status items, but the specific items, rating scales, and instructions for scoring different activities vary between the different settings. We consider equating different health assessment questionnaires as a missing data problem, and propose a variant of predictive mean matching method that relies on Item Response Theory (IRT) models to impute unmeasured item responses. Using real data sets, we simulated missing measurements and compared our proposed approach to existing methods for missing data imputation. We show that, for all of the estimands considered, and in most of the experimental conditions that were examined, the proposed approach provides valid inferences, and generally has better coverages, relatively smaller biases, and shorter interval estimates. The proposed method is further illustrated using a real data set. |
英文关键词 | Data augmentation Data fusion Hamiltonian Monte Carlo Item Response Theory Missing data Multiple imputation Predictive mean matching Statistical matching |
类型 | Article |
语种 | 英语 |
国家 | USA |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000411878000030 |
WOS关键词 | CATEGORICAL VARIABLES ; SURVEY NONRESPONSE ; MISSING-DATA ; ADJUSTMENTS ; MODELS |
WOS类目 | Biology ; Mathematical & Computational Biology ; Statistics & Probability |
WOS研究方向 | Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology ; Mathematics |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/197879 |
作者单位 | 1.Harvard Med Sch, Dept Hlth Care Policy, Boston, MA 02115 USA; 2.Brown Univ, Dept Biostat, Providence, RI 02912 USA |
推荐引用方式 GB/T 7714 | Gu, Chenyang,Gutman, Roee. Combining Item Response Theory with Multiple Imputation to Equate Health Assessment Questionnaires[J],2017,73(3):990-998. |
APA | Gu, Chenyang,&Gutman, Roee.(2017).Combining Item Response Theory with Multiple Imputation to Equate Health Assessment Questionnaires.BIOMETRICS,73(3),990-998. |
MLA | Gu, Chenyang,et al."Combining Item Response Theory with Multiple Imputation to Equate Health Assessment Questionnaires".BIOMETRICS 73.3(2017):990-998. |
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