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Related Concept Videos

Longitudinal Studies01:26

Longitudinal Studies

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Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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Sputum culture and sensitivity is a medical procedure used to diagnose bacterial infections in the respiratory tract and select the most appropriate antibiotics for treatment. This process involves analyzing sputum samples of thick and opaque secretions produced in the lungs and airways. These samples are collected from patients and then sent to the laboratory for analysis.
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Longitudinal Research02:20

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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A urine culture and sensitivity test is a diagnostic procedure used to identify urinary tract bacterial infections and determine the most effective antibiotics for treatment. This test is generally preferred when a patient shows manifestations of a urinary tract infection, such as frequent or painful urination, cloudy or foul-smelling urine, or lower abdominal pain.Purpose of the TestThe primary goals of a urine culture and sensitivity test are to:Determine the specific bacteria causing the...
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According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
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In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data
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Measurement error correction and sensitivity analysis in longitudinal dietary intervention studies using an external

Juned Siddique1, Michael J Daniels2, Raymond J Carroll3

  • 1Department of Preventive Medicine, Northwestern University, Chicago, Illinois.

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|February 7, 2019
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Summary
This summary is machine-generated.

This study introduces a statistical method to correct measurement errors in self-reported dietary data from lifestyle interventions. The approach uses biomarker data to improve the accuracy of dietary intake assessments in research.

Keywords:
24-hour dietary recallMultiple imputationrecovery biomarkersodium intake

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Area of Science:

  • Nutritional epidemiology
  • Biostatistics
  • Behavioral science

Background:

  • Self-reported dietary intake is prone to measurement error in lifestyle intervention trials.
  • Accurate dietary assessment is crucial for evaluating intervention effectiveness on weight and eating behaviors.

Purpose of the Study:

  • To develop a statistical framework for correcting measurement error in longitudinal self-reported dietary data.
  • To integrate intervention data with external biomarker validation studies.
  • To address limitations of cross-sectional validation studies in capturing time-varying or group-specific measurement error.

Main Methods:

  • A statistical framework combining intervention data with external biomarker validation data.
  • Utilizing multiple imputation for missing, error-corrected dietary intake data.
  • Employing sensitivity analyses to evaluate the impact of unverifiable assumptions about the measurement error process.

Main Results:

  • The proposed methods were applied to self-reported sodium intake data from the PREMIER study.
  • The framework allows for more accurate estimation of treatment effects by accounting for dietary measurement error.

Conclusions:

  • The developed statistical framework provides a robust method for correcting measurement error in longitudinal dietary data.
  • This approach enhances the reliability of findings from lifestyle intervention trials evaluating dietary changes.
  • Sensitivity analyses are essential for understanding the robustness of conclusions to assumptions about measurement error.