Sampling Strategies for Internal Validation Samples for Exposure Measurement–Error Correction: A Study of Visceral Adipose Tissue Measures Replaced by Waist Circumference Measures.

Statistical correction for measurement error in epidemiologic studies is possible, provided that information about the measurement error model and its parameters are available. Such information is commonly obtained from a randomly sampled internal validation sample. It is however unknown whether ran...

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Publicado en:American Journal of Epidemiology Vol. 190; no. 9; pp. 1935 - 1948
Autores principales: Nab, Linda, Smeden, Maarten van, Mutsert, Renée de, Rosendaal, Frits R, Groenwold, Rolf H H
Formato: equations & formulas research tables/charts Journal Article
Publicado: Oxford University Press / USA Sep2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2021
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      pub: Oxford University Press / USA
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        10.1093/aje/kwab114
        152287115
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        atl: Sampling Strategies for Internal Validation Samples for Exposure Measurement–Error Correction: A Study of Visceral Adipose Tissue Measures Replaced by Waist Circumference Measures.
      aug:
        au:
          Nab, Linda
          Smeden, Maarten van
          Mutsert, Renée de
          Rosendaal, Frits R
          Groenwold, Rolf H H
      sug:
        subj:
          Adipose Tissue
          Waist Circumference
          Internal Validity
          Measurement Error
          Bias (Research)
          Human
          Epidemiological Research
          Random Sample
          Simulations
          Regression
          Calibration
          Descriptive Statistics
          Sample Size
          Stratified Random Sample
      ab: Statistical correction for measurement error in epidemiologic studies is possible, provided that information about the measurement error model and its parameters are available. Such information is commonly obtained from a randomly sampled internal validation sample. It is however unknown whether randomly sampling the internal validation sample is the optimal sampling strategy. We conducted a simulation study to investigate various internal validation sampling strategies in conjunction with regression calibration. Our simulation study showed that for an internal validation study sample of 40% of the main study's sample size, stratified random and extremes sampling had a small efficiency gain over random sampling (10% and 12% decrease on average over all scenarios, respectively). The efficiency gain was more pronounced in smaller validation samples of 10% of the main study's sample size (i.e. a 31% and 36% decrease on average over all scenarios, for stratified random and extremes sampling, respectively). To mitigate the bias due to measurement error in epidemiologic studies, small efficiency gains can be achieved for internal validation sampling strategies other than random, but only when measurement error is nondifferential. For regression calibration, the gain in efficiency is, however, at the cost of a higher percentage bias and lower coverage.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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