Cluster Sampling in Biostatistics
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Questions and Answers

What is the formula used to calculate the sample size in stratified randomization?

  • Strata size / population size x 500 (correct)
  • Population size x sample size / 360
  • Population size / strata size x 500
  • Strata size x population size / 500
  • In systematic sampling, how is the sampling interval calculated?

  • By dividing the sample members by the population size
  • By dividing the population size by the desired sample size (correct)
  • By dividing the total population by the starting number
  • By dividing the desired sample size by the population size
  • What is one of the advantages of systematic sampling over simple random sampling?

  • It requires a sampling frame
  • It introduces bias in sampling
  • It involves a complex selection process
  • It guarantees a representative sample (correct)
  • In cluster sampling, what defines a cluster?

    <p>A group of sampling units close to each other</p> Signup and view all the answers

    What role does the starting point play in systematic sampling?

    <p>Sets the initial interval</p> Signup and view all the answers

    Why is systematic random sampling preferred over simple random sampling?

    <p>It ensures every individual has an equal chance of selection</p> Signup and view all the answers

    How does cluster sampling differ from simple random sampling?

    <p>Cluster sampling selects units that are close together as groups</p> Signup and view all the answers

    Study Notes

    Cluster Sampling

    • In cluster sampling, the population is divided into groups, usually geographic or organizational, and some of these groups are randomly chosen.
    • There are two types of cluster sampling: pure cluster sampling, where everyone in the chosen clusters is included in the survey, and simple multistage cluster sampling, where there is random sampling within each randomly chosen cluster.

    "30 x 7" Sample

    • The "30 x 7" sample is a commonly used two-stage cluster sampling scheme developed by the WHO to calculate the prevalence of immunized children within +/- 10 percentage points.
    • In this scheme, 30 blocks are randomly selected from all blocks in a county, and then 7 interview sites are randomly selected from each block.

    Advantages of Cluster Sampling

    • Generating a sampling frame for clusters is economical, and the sampling frame is often readily available at the cluster level.
    • Cluster sampling is the most economical form of sampling.
    • It allows for a larger sample for a similar fixed cost.
    • It requires less time for listing and implementation.
    • It is also suitable for surveys of institutions.

    Disadvantages of Cluster Sampling

    • Cluster sampling may not reflect the diversity of the community.
    • Elements in the same cluster may share similar characteristics.
    • It provides less information per observation than an SRS of the same size.
    • Standard errors of the estimates are high compared to other sampling designs with the same sample size.

    Suitable Situations for SRS and Cluster Sampling

    • SRS is suitable for a medical study where the population is all adults over 50 with high blood pressure, and a sampling frame is available.
    • SRS is also suitable for an e-mail survey of students where a list of e-mail addresses for all students is available.
    • Cluster or multistage sampling may be suitable for a study of all hospitals in the U.S. that perform heart bypass surgery.
    • Cluster sampling may be suitable for choosing candidates in an election.
    • Multistage cluster sampling may be suitable for studying medication use for acute stroke among hospitals in Dhaka.

    Non-Probability Sampling

    • Non-probability sampling is a method where the investigator chooses samples from the universe that, in their opinion, are the best representatives of the population.
    • Advantages of non-probability sampling include simplicity, flexibility, and facilitation of the study's purpose.
    • Disadvantages of non-probability sampling include bias, unreliability, and inaccuracy.

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    Description

    Learn about cluster sampling in biostatistics with this quiz. Understand how populations are divided into groups and how samples are randomly chosen within clusters. Discover different types of cluster sampling methods used in surveys.

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