chapter 13 choosing a sample Flashcards
1st step in planning a study is finding the _______ population
target
Target population must be Identified, which can be stated as the _______ population
accessible
target population»_space; _______
accessible population
When the differences between the target and accessible population are too great, i.e., geographic differences like climate or socioeconmic characteristics, it may be necessary to get more _______ target population
restricted population
SELECTION CRITERIA: 2 types. Inclusion criteria and ______ criteria
exclusion
once we identified a target population, we have to plan for subject _______ , inviting individuals to participate.
recruitment
the ______ sample of people may be less than predicted/requested
FINAL
t/f, A flow chart that details how participants pass through various stages of a study should be included in a research report. This is an example of “reporting subject participation”.
t
Sample size is directly related to ________ of the study
POWER
With a small sample, power tends to be low and a study may not succeed in demonstrating the desired effects. t/f
t
larger sample = probably more POWER of a study, true or false
true
Probability samples are created through a process of ______ sampling/selection.
random
random selection/sampling
every unit in the population has an equal chance, or probability of being chosen
nonprobability samples
made by non random methods, usually used more in clinical research
sample values
statistics
population values
parameters
difference between sample values and population values
sampling error, sampling variation
the essence of random sampling is that these sampling differences are due to ______ and are not a function of any human bias, conscious or unconscious.
chance
Random selection/sampling gives the greatest possibility of a samples validity, t/f
t
sampling bias: conscious vs unconscious
conscious: the people selected for a sample overrepresent or underrepresent certain population attributes that are related to the phenomenom of the study
unconscious: u pick people who look handicap for a handicap study
Probability sampling :
every member of a population has an equal opp, or probability, of being selected
a truly RANDOM SAMPLE is unbiased in that each selection is independent and no one member of the population has any more chance of being chosen than any other member, t/f
t
There are many different types of sampling, examples?
Probability methods
simple, systematic, stratified random, cluster, disproportional
non probability methods
convenience, quota, purposive, snowball
Non probability sampling methods examples
- Convenience Sampling - use of available participants e.g.,
college students or community volunteers who respond to the flyers;
Most frequently used sampling method - Purposive Sampling – used when specific expertise /
experience of participants is needed
▪ often used in qualitative studies - Quota Sampling – incorporate a stratification but lack of a
randomization - Snowball Sampling – used when it is difficulty to find subjects
▪ to recruit via communication of “word-of-mouth”
Convenience Sampling NP
use of available participants e.g.,
college students or community volunteers who respond to the flyers;
Most frequently used sampling method
Purposive Sampling NP
used when specific expertise /
experience of participants is needed
▪ often used in qualitative studies
Quota Sampling NP –
incorporate a stratification but lack of a
randomization
Snowball Sampling NP
– used when it is difficulty to find subjects
▪ to recruit via communication of “word-of-mouth”
simple random P
each member has an equal chances of being selected
systematic sampling P
Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling
stratified random sampling P
a population divides into strata or subsets, and then the random sample is taken from each stratum in proportion to its size. For example, if the entire population is 60% female and 40% male, then the sample would be 60% female and 40% male.
cluster sampling P
researchers divide a population into smaller groups known as clusters. They then randomly select among these clusters to form a sample. Cluster sampling is a method of probability sampling that is often used to study large populations, particularly those that are widely geographically dispersed
Disproportional sampling P
a form of stratified random sampling, a sampling technique where the sample size for each group, or stratum, is not proportional to the size of that group in the overall population. Instead, the sample size for each group is based on specific research needs. These strata are oversampled to provide stronger representation, and weights are used to adjust data to correct this
