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population
The aggregate of cases in which a researcher is interested

sampling
Selection of a portion of the population (a sample) to represent the entire population

Eligibility criteria
 The characteristics that define the population
  inclusion criteria
  exclusion criteria

strata
Subpopulations of a population (e.g., male/female)

Target population
The entire population of interest

Accessible population
 The portion of the target population that is
 accessible to the researcher, from which a sample is drawn

Representative sample
A sample whose key characteristics closely approximate those of the population—a sampling goal in quantitative research

Sampling Goal for Quantitative Research
is to obtain a sample that represents the population

representative sample is more easily achieved with
 Probability sampling
 Homogeneous populations
 Larger samples

Sampling Problems for Quantitative Research
 sampling error
 sampling bias

sampling bias
 The systematic over or underrepresentation of segments of the population on key variables
 when the sample is not representative

Sampling error
Differences between sample values and population values

sampling designs
 probability sampling
 nonprobability sampling

Probability sampling
Involves random selection of elements: each element has an equal, independent chance of being selected

Nonprobability sampling
Does not involve selection of elements at random
Not all people have an equal chance of being selected

NonProbability Sampling include ?
Convenience sampling
Snowball (network) sampling
Quota sampling
Purposive sampling

Convenience Sampling
a form of non probability sampling
use of the most convenient available people
most widely used approach by quantitative researchers
most vulnerable to sampling bias  may not represent the overall population

snowball sampling
a form of non probability sampling
referrals from other people already in sample
used to identify people with distinctive characteristics
used by both quantitative and qualitative researchers

Quota Sampling
a form of non probability sampling
Convenience sampling within specified strata of the population
Goal is to Enhance the representativeness of sample
Infrequently used, despite being a fairly easy method of enhancing representativeness

Consecutive Sampling
a form of non probability sampling
Involves taking all of the people from an accessible population who meet the eligibility criteria over a specific time interval, or for a specified sample size
 A strong nonprobability approach for “rolling enrollment” type accessible populations

 Risk of bias low unless there are seasonal or temporal fluctuations

Purposive Sampling
a form of non probability sampling
Sample members are handpicked by researcher to achieve certain goals
Used more often by qualitative than quantitative researchers
Can be used in quantitative studies to select experts or to achieve other goals

Types of Probability Sampling
Simple random sampling
Stratified random sampling
Cluster (multistage) sampling
Systematic sampling

Simple Random Sampling
form of probability sampling
Uses a sampling frame – a list of all population elements
Involves random selection of elements from the sampling frame
Not to be confused with random assignment to groups in experiments
Cumbersome; not used in large, national surveys

Stratified Random Sampling
type of probability sampling
 Population is first divided into strata, then random
 selection is done from the stratified sampling frames
 Enhances representativeness
  Can sample proportionately or disproportionately from the strata

Cluster (Multistage) Sampling
type of probability sampling
Successive random sampling of units from larger to smaller units (e.g., states, then zip codes, then households)
Widely used in national surveys
 Larger sampling error than in simple random sampling,
 but more efficient

Sample Size
The number of study participants in the final sample
Sample size adequacy is a key determinant of sample quality in quantitative research.
 Sample size needs can and should be estimated
 through power analysis.

Sampling for Qualitative Research
Selection of sample members guided by desire for informationrich sources
“Representativeness” not a key issue
Random selection not considered productive

Sampling Methods for Qualitative Reserach

Sampling Methods for Qualitative Reserach
Convenience (volunteer) sampling
Snowball sampling
Purposive sampling
Theoretical sampling

Theoretical Sampling
Preferred sampling method in grounded theory research
Involves selecting sample members who best facilitate and contribute to development of the emerging theory

Sample size for Qualitative Research
No explicit, formal criteria
Sample size determined by informational needs
Decisions to stop sampling guided by data saturation
Data quality can affect sample size.

Sampling for Ethnography
Mingling with many members of the culture—a “big net” approach
Informal conversations with 25 to 50 informants
Multiple interviews with smaller number of key informants

Sampling for Phenomenology
Relies on very small samples (often 10 or fewer)
Participants must have experienced phenomenon of interest

Sampling for Grounded Theory
Typically involves samples of 20 to 40 people
Selection of participants who can best contribute to emerging theory (usually theoretical sampling)

