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What are Estimates?01:06

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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
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Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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Related Experiment Video

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'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
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National Health and Nutrition Examination Survey, 2015-2018: Sample Design and Estimation Procedures.

Te-Ching Chen, Jason Clark, Minsun K Riddles

    Vital and Health Statistics. Series 2, Data Evaluation and Methods Research
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    PubMed
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    The National Health and Nutrition Examination Survey (NHANES) provides U.S. health estimates using complex sample designs. This report details NHANES 2015-2018 methods for sample weights and variance estimation for reliable public health data.

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    Area of Science:

    • Public Health
    • Biostatistics
    • Survey Methodology

    Background:

    • The National Health and Nutrition Examination Survey (NHANES) is crucial for national health estimates.
    • It targets the noninstitutionalized civilian U.S. population using a complex, four-stage sample design.
    • NHANES sample weights are essential for accurate statistical analysis of health-related data.

    Purpose of the Study:

    • To describe the NHANES 2015-2018 sample design.
    • To detail methods for creating sample weights and variance units for public-use data files.
    • To explain the impact of design changes and provide guidance for data user analysis.

    Main Methods:

    • Utilized a complex, four-stage sample design for NHANES 2015-2018.
    • Developed variance approximation procedures for design-consistent variance estimation.
    • Created sample weights and variance units, including for specialized subsamples like the fasting group.

    Main Results:

    • The report outlines the specific sample design implemented for NHANES 2015-2018.
    • Methods for calculating reliable sample weights and variance units are presented.
    • Guidance is provided on adjusting weights for combined survey cycles or subsamples.

    Conclusions:

    • Accurate estimation relies on understanding and applying the described NHANES sample design and weighting procedures.
    • Variance approximation methods are necessary for complex survey data reliability.
    • This report equips data users with the necessary information for robust analysis of NHANES 2015-2018 data.