Characteristics of Quantitative Data Collection Techniques

Population

Is the entire group of interest

Sample

is a subset of population elements; cases/elements that represent the population.

Eligibility criteria

Researchers specify population characteristics through

Inclusion Criteria

to determine whether a person qualifies as a member of a population.

Exclusion Criteria

it excludes someone as a member of a population.

Sampling Bias

Failure to reach representativeness

Strata

segment of a population based on shared characteristics

Probability Sampling

a process in which each element of the population has an equal chance of being chose for the sample. There is random selection

Simple Random Sampling

Sammpling by chance, either by lottery or by the use of a table of random numbers

Sampling frame

a list of population elements

Stratified Random Sampling

involves taking certain areas of the population, dividing the areas into sections and then taking a random sample from each section.

Systematic Random Sampling

involves selecting every kth case from a list, such as every 10th person on a patient list or every 25th person on a student roster.

(Multistage) Cluster Random Sampling

involves selecting broad groups (clusters) rather than selecting individuals.

Non-Probability Sampling

elements are selected by non-random methods.

Quota Sampling

identify strata of the population and then determine how many participants are needed from each stratum to meet a quota.

Purposive or Judgmental

subjects are hand-picked to be included in the sample based on the researcher’s knowledge of the population.

Evaluating (Non-) Probability Sampling

Probability sampling is the best method of obtaining representative samples.

Power Analysis

to estimate sample size.

G*Power

free software for power analysis.

Qualitative

to discover meaning and to uncover multiple realities, not to generalize to a target population

to select settings with high potential for information richness.

A key step in Qualitative sampling

Sampling

is emergent and capitalizes on early learning to guide subsequent actions.

Convenience Sampling

utilizes readily available informants.

Snowball Sampling

asking early informants to refer other study participants.

Maximum Variation Sampling

involves purposefully selecting persons or settings with variations on dimensions of interest

Typical Case Sampling

involves selecting cases that illustrate or highlight what is typical, average, normal or representative.

Extreme (Deviant) Case Sampling

provides opportunities for learning from the most unusual and extreme informants.

Criterion Sampling

involves selecting cases that meet a predetermined criterion of importance

Sampling confirming and disconfirming cases.

Theoretical Sampling

is used in grounded theory.

Sampling in Ethnography

• May begin by adopting a “big net” approach.

• Often rely on a small pool of key informants.

• May also sample non-human – event, records or artifacts.

Sampling in Phenomenology

• Often rely on a small pool key informant (can be 1- or fewer).

• May also recruit people with demographic or other differences who have shared a common experience – to explore diversity of individuals experiences.

Sampling in Grounded Theory

• Uses theoretical sampling.

• Select informants who can best

contribute to the evolving theory.

Adequacy

refers to the sufficiency and quality of data the sample yielded.

Appropriateness

concerns the methods used to select a sample.