Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study.

Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Research Abstract Details 

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Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Abstract Text:

N M Shara,J G Umans,W Wang,B V Howard,H E Resnick,

Missing data are a common problem in epidemiologic studies. This study had two aims: (a) to determine which method for imputing missing renal function data provides estimates closest to those made with complete data and (b) to determine which measure of renal function better estimates cardiovascular disease (CVD) risk. For these analyses, a subset of Strong Heart Study participants with complete data for renal function was identified. Data were randomly dropped from this complete set at three rates: 30, 45, and 60%. Five common techniques for handling missing data were compared: imputation using the mean, adjacent value (AV), single imputation, multiple imputation, and listwise deletion. Differences between the imputed sets and the complete set were determined for each method. Imputation methods were used to fill in missing values for serum creatinine (Scr) in one model and estimated glomerular filtration rate (eGFR) in another. For both Scr and eGFR, the AV method provided the most favorable results in predicting CVD risk, regardless of the rate of missing data.

Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Publishing Authors By Initials

NM Shara,JG Umans,W Wang,BV Howard,HE Resnick,

For similar investigative techniques: epidemiologic methods: statistics as topic: probability: risk: risk factors research abstracts see: investigative techniques: epidemiologic methods: statistics as topic: probability: risk: risk factors research

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Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Kidney international

VOLUME: 71

Page Numbers: 701-5

Journal Abbreviation: Kidney Int.

ISSN: 0085-2538

DAY: 31

MONTH: 01

YEAR: 2007

Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Information

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LANGUAGE: eng

NlmUniqueID: 323470

Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Keywords Mesh Terms:

KEYWORDS: Risk Factors

MESH TERMS: methods

Chemical & Substance for Abstract: Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study. Information

Substance Name: Creatinine

Registry Number: 60-27-5

Grant and Affiliation Information for Assessing the impact of different imputation methods on serial measures of renal function: the Strong Heart Study.

AFFILIATION: Department of Epidemiology and Statistics, MedStar Research Institute, Hyattsville, Maryland, USA. Nawar.Shara@Medstar.Net

Country: United States

AGENCY: United States NIDDK

GRANT: 1 F32 DK075204-01

ACRONYM: DK

MEDLINETA: Kidney Int

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