Sampling Concepts and Designs

Study Notes

Sampling: process of selecting a portion of a population to represent the whole
Population: the complete group of individuals that share specific characteristics
Sample: a subset of the population that is selected for study
Target population: the entire population that the researcher is interested in
Accessible population: the portion of the target population directly available to the researcher
Eligibility criteria: characteristics used to define who is included in the study population
Representative sample: sample closely mirroring the characteristics of the population
Sampling bias: systematic over- or under-representation of a population segment
Strata: mutually exclusive groups within a population based on a characteristic
Elements: individual units within the sample and population

Non-probability sampling: non-random methods
- Convenience sampling: selecting the most readily available individuals
- Quota sampling: dividing the population into strata and then taking a convenience sample from each stratum
- Consecutive sampling: recruiting all eligible participants over a specific period or until a sample size is reached
- Purposive sampling: researchers carefully select participants based on specific criteria
Probability sampling: random selection methods
- Simple random sampling: the most basic method, where each element has an equal chance of being selected
- Stratified random sampling: the population is divided into strata, and then random samples are selected from each stratum
- Systematic sampling: selecting every kth element from an ordered list

Sample size: the number of participants included in a study
Larger sample size: improves representativeness and reduces sampling error
Power analysis: a statistical method used to determine the optimal sample size for a study

Response rate: the proportion of people who participate in a study compared to the number sampled
Nonresponse (response) bias: differences between those who participate and those who decline participation

Data collection: the process of gathering measurable data
Types of data:
- Self-report: participants provide information about themselves
- Observational: observing and recording behaviors or events
- Biophysiologic measures: obtaining data directly from the body (in vivo) or through laboratory analysis (in vitro)

Question forms:
- Closed-ended: participants select from predefined response options
- Open-ended: participants provide their own answers
Instruments:
- Interview schedule: questions asked face-to-face or by phone
- Questionnaire: respondents complete the instrument themselves

Methods of structured observation: category systems, checklists, rating scales
Observational sampling: selecting specific times or intervals for observation

In vivo: measurements taken directly from a living organism
In vitro: measurements taken from biomaterials extracted from a living organism and analyzed in a laboratory

Measurement of variables: assigning numbers to represent the amount of a specific attribute present
Obtained score: the actual data value for a participant
True score: the ideal score that would be obtained with a flawless instrument
Error: factors that distort measurement
Factors that contribute to measurement error:
- Situational contaminants: environmental factors that influence measurement
- Transitory personal factors: temporary individual characteristics that affect measurement
- Response-set biases: consistent patterns in responding that influence measurement
- Administration variations: differences in how the instrument is administered

Reliability: consistency and accuracy of an instrument in measuring the target attribute
- Test-retest reliability: stability of measurement over time
- Inter-rater reliability: agreement between different observers
- Internal consistency: the consistency of individual items within an instrument
Validity: the extent to which an instrument measures what it is intended to measure
- Face validity: judgment based on whether the instrument appears to measure the intended construct
- Content validity: the extent to which the instrument includes a representative sample of items for the construct
- Criterion validity: the relationship between the instrument and an external criterion
- Construct validity: evidence that the instrument measures the theoretical construct it is designed to measure