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Chapter 13 Sampling in Quantitative Research

Question #1

Tell whether the following statement is true or false:

The aggregate of cases in which a researcher is interested is called a sample.

Answer to Question #1

False

The aggregate of cases in which a researcher is interested is called a population. A sample is selection of a portion of the population to represent the entire population.

Basic Sampling Concepts in Quantitative Studies #1

Population: the aggregate of cases in which a researcher is interested

Accessible population: the aggregate of cases that conform to designated criteria and that are accessible for a study

Target population: the aggregate of cases about which the researcher would like to generalize

Basic Sampling Concepts in Quantitative Studies #2

Eligibility criteria/inclusive criteria: criteria that specify population characteristics

Cost

Practical constraints

People’s ability to participate

Design considerations

Exclusion criteria

Basic Sampling Concepts in Quantitative Studies #3

Samples and Sampling

Sampling: selection of a portion of the population (a sample) to represent the entire population

Element: basic population unit about which information is collected

Sample: a subset of population elements

Representative sample

Probability sample

Nonprobability sample

Question #2

Tell whether the following statement is true or false:

Researchers usually sample from the target population.

Answer to Question #2

False

Researchers usually sample from the accessible population but should identify the target population to which they want to generalize their results.

Basic Sampling Concepts in Quantitative Studies #4

Staged sample: samples are sometimes selected in multiple phases

Sampling bias: the systematic over- or underrepresentation of segments of the population on key variables

Question #3

Tell whether the following statement is true or false:

Probability sampling involves random selection of elements.

Answer to Question #3

True

Probability sampling involves random selection of elements.

Nonprobability Sampling

Convenience sampling

Snowball sampling

Quota sampling

Consecutive sampling

Purposive sampling

Evaluation of nonprobability sampling

Probability Sampling

Simple random sampling

Stratified random sampling

Multistage sampling

Cluster sampling

Systematic sampling

Evaluation of probability sampling

Sample Size in Quantitative Studies

Power analysis

Estimate sample size

Large samples preferred to small samples

Sample size basics

Factors affecting sample size /requirements in quantitative research

Effect size

Homogeneity of the population

Cooperation and attrition

Subgroup analyses

Implementing a Quantitative Sampling Plan

Steps in sampling

Identify the population

Specify the eligibility criteria

Specify the sampling plan

Recruit the sample

Sample recruitment

Screening instrument

Generalizing from samples

Critical Appraisal of Sampling Plans #1

Sampling Plan

Construct

Internal factors

External factors

Statistical conclusion validity

Critical Appraisal of Sampling Plans #2

Sampling plan should be scrutinized with respect to

Approach used

Study population and eligibility criteria

Number of participants and rationale for sample size

Inclusion of power analysis

Description of main characteristics of sample

Number and characteristics of participants who declined participation/dropped out