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Probabilistic Sampling Methods for Survey Research

Learn about probability sampling plans, techniques like simple random sampling, and the benefits of stratification in research. Explore how to handle nonresponse bias in participant selection.

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Probabilistic Sampling Methods for Survey Research

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  1. Ch. 9: Survey Research and Subject Recruitment

  2. Selecting the Research Participants • Typically use opportunity samples if goal is simply to learn about human nature. • But what if you want to generalize results from the sample to a population? • Need way of selecting a sample that is representative of the population.

  3. Requirements for a Probability Sampling Plan • Sample values must be unbiased. • There is stability in the samples.

  4. Simple Random Sampling • Sample is selected from an undivided population. • Sample is chosen using a process that gives every sampling unit an equal chance of being selected. • Requires knowledge of the existence of all the units in the population.

  5. Examples of Random Sampling Strategies • Throwing dice • Using a table of random digits • Spinning a roulette wheel • Drawing capsules from an urn • Using random digit dialing for telephone surveys.

  6. Random Sampling Options • Sampling with replacement • Selected names are placed back in the selection pool. • Sampling without replacement • Selected names are discarded and cannot be reselected.

  7. Other Probability Sampling Plans • Stratified random sampling • Create homogeneous subpopulations based on a known characteristic • Area probability sampling • Divide the population into geographic areas

  8. Point Estimates and Confidence Intervals • Point Estimate: Describes some particular characteristic of the population. • Interval Estimate: Indicates how much the point estimates are likely to be in error. • Confidence Interval: Probability that a point estimate is within plus-or-minus some specified interval.

  9. Benefits of Stratification: If Simple Random Sampling Is Used

  10. Benefits of Stratification: If Stratified Random Sampling Is Used

  11. Nonresponse Bias • Error due to nonparticipation or nonresponse. • Possible consequences of this bias: • Smaller effective sample size • Inaccurate estimates of population values

  12. Example of a Nonresponse Bias

  13. Better educated Higher social class Higher IQ scores Higher need for social approval More sociable More arousal-seeking More unconventional More often women Less authoritarian Characteristics of Typical Volunteer Subjects

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