3.2 Sampling Flashcards
Define Sampling
Sampling is to draw a subset of the population that truly represents the target population as a whole i.e. infers that the researcher is able to draw conclusions about the target population from the sample or subset of that target population
Explain the importance of sampling in health research
Unnecessary and impractical to study the whole population
Obtain useful and valid information about the population
What are the two main types of sampling?
Probability
Non-probability
Validity
i.e. findings are accurate and indicative, the research measures what it set out to measure
Truth and accuracy of the data and findings.
It refers to
- concepts being investigated
- people or objects being studied
- methods by which data are collected
- findings that are produced
True or False. The extent to which research findings can be generalised to the target population will depend on the extent of sampling error or bias within the study
True
i.e. ↑ error/bias →↓representativeness of findings
Sampling frame
Members of a population eligible to be included in a sample
What is a sampling plan and what is its purpose?
Outlines the process by which the subsets or participants are dawn from target population.
Aim is to minimise sampling error and bias and maximise representativeness of the sample.
No sampling technique can guarantee against sampling errors – we can just aim to minimise them.
What is probability sampling?
Every member of the population has an equal (and independent) chance of recruitment vs. not equal chance.
Intent is to generalise the findings of the sample to the population from which it was taken.
Used when research is investigating a large population and requires a statistical description.
Helps to reduce sampling error, increase internal validity. Reduces bias as everyone has equal chance of recruitment.
What are the 4 types of random sampling?
Simple random sampling
Systematic random sampling,
Stratified random sampling
Cluster random sampling
Internal validity means….
Less bias
Scientific process is used
Study is accurate
Refers to the extent to which changes in the dependent variable (the observed effects) can be attributed to the independent variable, rather than EXTRANEOUS variables.
External validity
Generalisation of findings from sample to population (representativeness of sample)
Refers to the degree to which results of a study are generalisable beyond the immediate study sample and setting to other samples and settings.
True or False. You need internal validity to have external validity.
True
What is simple random sampling?
Establish sampling frame.
Decide on sample size.
Select the required number of units starting at a random point by either lottery method or use of random numbers
e.g. drawing names/numbers out of a hat, or assigning everyone a number and using a random number generator to select
Systematic sampling
Sampling frame is available.
Sample size has been predetermined.
Start at a random point on sampling frame but pick every “nth” unit (the gap)
The gap is determined by sampling frame # / sample size e.g. 25 / 5 = select every 5th persion
Stratified random sampling
Subdived groups. Randomly selected from each group. Represents important characteristics of the population.
Similar to simple random sampling but the population is first subdivided into homogenous subsets (strata) from which the required number of units can be randomly selected.
Stratification reflects the population characteristics significant or crucial to the research question – e.g. gender, age, occupation.
Allows for a greater degree of representativeness of the population.
Sampling ratio =
sample size to population size
Cluster sampling
Utilises simple random sampling of predetermined groups or clusters of individual elements of interest; e.g. villages, hospitals, schools families, health areas
Often used when cannot create a sampling frame that will include all the units of the accessible population.
Example:
Wish to investigate attitudes to GBLTI amongst nursing home employees in WA
List all the nursing homes in WA (this becomes the sampling frame)
Randomly select a number of nursing homes
Interview the employees from each selected nursing home
Does a larger sample size mean less or more sampling error?
Less
Do samples of more diverse populations need to be smaller or larger than samples of more homogenous population?
Larger
Non-probability sampling
The probability of a potential research participant being selected is not known in advance.
The findings cannot be generalised to a larger group of people
Non-randomness of the sampling increases the risk of what?
Bias
When is non-probability sampling commonly used?
Particularly when have limited resources (much less costly and time consuming than probability sampling )
or unable to identify or access all members of population.
Useful in exploratory research and qualitative studies; samples not statistically representative but can give in-depth insights into phenomena
What are the 5 types of non-probability sampling?
*Purposive
*Convenience
*Snowball
Theoretical
Quota
Purposive sampling …
Participants are recruited according to pre-selected criteria relevant to the research aims/questions of a given study.
Designed to recruit thosewho have the required status, experience or knowledge of interest to the researcher.
Typically choice of sample is based on judgement that it has
characteristics typical of the population.
Open to selection bias
