Chapter 7 Flashcards
Nonprobability sampling
Sample elements are chosen non randomly.
Produces biased sample
Each element of the population may not be included in the sample.
Restricts generalizations made about study findings
Types
Convenience: The most common type of sampling. A non probability method of selecting a sample that includes subjects who are available in a convenient way to the researcher.
Quota: a number standard
Purposive: specific to characteristics of the study
Snowball Sampling: word of mouth
Nonprobability Sampling Procedures Advantages/Disadvantages
Advantages
Time
Money
Disadvantages
Nonrandom
Not able to generalize findings
Sampling frame
Members of the population who are available and accessible to the researcher
Representativeness
Members of the sample are similar to the population in major characteristics of interest
Sampling error
Differences between the sample and the population that are due to the way the sample was drawn
Selection bias
Differences between the sample and the population that are due to manipulation by the researcher
Inclusion criteria
Objective attributes that are necessary Clinical Demographic Geographic Temporal
Exclusion criteria
Attributes that may affect the outcome
Co-morbid conditions
Behavioral (high potential for attrition)
Probability Sampling
A sampling process used in quantitative research in which every member of the available population has an equal probability of being selected for the sample.
Allows researcher to estimate the chance
Helps with inferential statistics (quantitative) with greater confidence
Gives the ability to generalize the findings
Allows researcher to estimate the chance
Probability Sampling Types
Simple random: name out of hat
Stratified random
Cluster random: limited sample size
Systematic random: pick every 10th person
Simple Random Sampling (probability)
Type of probability sampling
Importance of this sampling:
Equal chance of selection
Independent chance of selection
Time consuming
Advantages of Simple Random Sampling
Little knowledge of population is needed.
Most unbiased of probability method
Easy to analyze data and compute errors
Advantages of Simple Random Sampling
Complete listing of population is necessary.
It is time consuming to use.
Stratified Random Sampling
Type of probability sampling
Population is divided into subgroups or strata.
Strengthens probability/control for participants
Simple random sample taken from each strata
Advantages
Increases probability of being representative
Ensures adequate number of cases for strata
Disadvantages
Requires accurate knowledge of population
May be costly to prepare stratified lists
Statistics are more complicated
Cluster Random Stratified Sampling
Large groups or clusters (to a characteristic), not people, are selected from population.
Simple, stratified or systematic random sampling may be used during each phase of sampling.
Advantages
Saves time and money
Arrangements made with small number sampling units
Characteristics of clusters or population can be estimated.
Disadvantages
Causes a larger sampling error
Requires each member assignment of population to cluster
Uses a more complicated statistic analysis
Systematic Random Sampling
Type of probability sampling
Every kth element is selected.
Advantages
Easy to draw sample
Economical
Time-saving technique
Disadvantages
Samples may be biased.
After first sample is chosen, no longer equal chance
Qualitative Sampling
Purposeful method
Primary concern: ability to inform the question
Researcher often involved in recruitment and selection
Criteria may be used for inclusion and exclusion
Redundancy and Saturation
When is the point at which no new information is being generated?
Factors affecting power analysis
Biggest effect: sample size Level of accuracy required Number of variables to be studied Variability in the population Magnitude of effect Independence of the data
Power analysis
Helps to determine sample size May prevent type II error Helps to detect statistical significance Low power; type II error high External funding sources require it. Helps determine the optimum sample size
Population
Entire set of subjects that are of interest to the reader
Common characteristic
Of interest to the researcher
Sample
Subset of the population
Sample represents the population characteristics
Target Population
Entire group of people or objects
People or objects meet designated set of criteria.
Generalization of the findings
Accessible Population
Group of people or objects
Researcher has access to them.
Sampling Concepts/Stratigies
Sampling Frame
Respresentativeness
Sampling error
Selection Bias
Convenience Sampling Advantages/Disadvantages
Advantages Expedited data collection COST-EFFECTIVE Easy sampling Ready availability for data
Disadvantages
Biased
Outliers
Insufficient power
