Wildemuth chapter 13
sampling for extensive studies – conclusion to draw from your research will hold apply to a particular set of people or organizations
a sample was collected to study and plan to generalize your findings to all the people organizations representative sample
practice of sampling is intended to achieve greater efficiency/if done properly results in a more accurate findings because you can control your data collection procedures and other aspects of the procedure preferably
– Design your sampling procedures carefully/the selection of particular people organizations to participate will these does set of rules that reply to a carefully defined population
Went to selected a probability sample from the population of interest it needs to be reviewed subsequently
probability sampling: concepts and definitions: the population is the collection of elements but which we wish to make an inference – an element is an object in which a measurement is taken
the sampling frame is a list of all agile eligible elements in the population
Probability sample has two specific characteristics first every element of the fibrillation of interest has a known nonzero probability of being selected into the sample
the second important characteristic elements be selected randomly at some point in the process
does not mean haphazard selection Newmont line selection based on the theory of probability that will help you avoid bias in your sample
Procedures for selecting a probability sample
first define your population of interest then define more carefully those who have you something within the past year three times within the year different definition I fear population of interest will depend on your goal
Compromise the definition of the study population to make your sampling plan possible to carry out
define your target population and actual study population
Unit of analysis – could be individuals or could be groups or organizations that unit of analysis you are making clear which elements are eligible for inclusion
Identify or construct the sampling frame – list of elements in the study of population
matches the definition of your study population – missing some portion?
May be complete the contact information or inaccurate or duplications this list is flawed – you will be implicitly redefining your population
Finally select particular animal elements from the sampling frame – identifying specific people – probability sample you use
simple random sampling single sampling frame all the elements in it will have equal chance of being selected, generate a set of random numbers, work through the random numbers and to get the sample size you need
Systematic sampling
extremely tedious and error-prone instead use systematic sampling – random numbers chosen to select the first element from their every and element is selected and varies based on the size of the sample
should not be used if the frames order has some type of pattern it could introduce bias into the sample
Stratified sampling
population is divided into strata 1st/elements a random list sampled from each stratum – may be possible to use a smaller's sample size take your research more efficient
Define the strata – selective variable to divide your population
second decide in the number of strata
finally decide in the sample size
Cluster sampling
sampling units are groups begin the sampling procedure by randomly selecting a sample of clusters
in single stage cluster sampling you would then include in your sample all the elements within the selected clusters
minimize the cost of collecting data from a geographically widespread sample
Nonprobability sampling: concepts and definitions
Not possible to select a random sample from the population which interested? Not possible to identify create a valid sampling frame? Some type of nonprobability sample will need to be defined
Quota sampling
quota for each level of each characteristic/recruiting people until you have met your quota – resemble stratified sampling/no random selection of elements
Purposeful purposive sampling
Judgment sample relies on expert judgment of the person selecting the sample
based on their individual characteristics, a sample that is representative of the population in terms of both central tendency in range of characteristics – include both a typical staff member and more extreme cases/potential for bias
Snowball sampling
particularly sensitive or when eligible belt members may be particularly difficult to identify – ask each participant for suggestions for additional people
forward to five more people
Convenient sampling
try to recruit people because they are available
characteristics of the people who are eligible for study participation
Sample size
as efficient as possible – recruit and collect data from a small sample as possible
don't use a standard method parens (local tradition, at least enough, data availability, intuition, experience, negotiations) – confidence interval around the estimate – area can tolerate any parameter estimates – no fix criteria for setting acceptable confidence interval balance the importance of the accuracy
Special case usability testing special case five or six users can identify 80% of the usability problems homes there are – larger sample size significant portion of the usability problems
The effects of nonresponse in a sample
some of the participants you selected will not accept your invitation response rates only 63% – oversample to increase the number/will not necessary help avoided by a sample
Use appropriate data/use wording/well-designed questionnaires are study procedures = gift certificates cash other items
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