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I hope it will be simplified and powerful presentation for all. Rather than adding large texts, here you can find image and graphical presentation. Happy Reading
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Chapter 8 Sampling Sampling Sampling involves decisions about who or what will be tested, observed, or interviewed in your study (Morse, 2007) Key questions to address: Who should and should not be included? How many should be included? Probability Probability is the likelihood that an event or a condition will occur You can express probability in terms of the chance the event will occur or in percentages Levels of Significance Levels of significance are the difference that will be accepted as too large to be attributed to chance These levels are set by the researcher at the outset of a study Probability Samples Probability samples are formed to ensure that each subject has an equal chance of being included so an unbiased sample can be used Probability Samples A sampling design explains how the subjects are chosen and should include: Number of subjects How they will be assessed, screened, and selected Inclusion and exclusion criteria Probability Samples Random selection is accomplished by having: Identification of all possible participants Every potential participant is given an equal chance of being selected Probability Samples Variations of random sampling include: Stratified: randomly select from each stratum Cluster: sample groups rather than individuals Multistage: sample from multiple sets of clusters Nonprobability Sampling Reasons why researchers use nonprobability samples are: Limited resources for developing an accurate sampling frame or purchase lists of potential subjects Information needed to identify all potential subjects is not available Nonprobability Sampling Reasons why researchers use nonprobability samples are: Limited number of subjects Subjects are difficult to find or difficult to persuade to participate in study Subjects do not complete study Experimental mortality Nonprobability Sampling Types of nonprobability samples include: Quota sampling: select a specified number of participants from each group Convenience sampling: enroll those who are available Snowball network or referral sampling: begin with known individuals and ask them to refer others who meet selection criteria Tracking and Reporting Sample Development In order to improve the reporting of randomized controlled trials (RCTs), the Consolidated Standards of Reporting Trials (CONSORT) were developed A flow diagram that can be used for tracking sample development CONSORT Flow Diagram Source: Altman, D.G., Schulz, K.F., Moher, D., Egger, M.. Davidoff, F., Elbourne, D., Gøtzsche, P.C., & Lang, T. (2001). The revised CONSORT statement for reporting randomized trials: Explanation and elaboration. Annuals of Internal Medicine; 134(8), 663-694. Example of Flowchart Source: Buchbinder, R., Osborne, R.H., Ebeling, P. R., Wark, J.D., Mitchell, P.M., Wriedt, C., Graves, S.D., Staples, M.P., & Murphy, B. (2009). A randomized trial of vertebroplasty for painful osteoporotic vertebral factures. The New England Journal of Medicine, 361 ...
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T8 audit sampling
1.
Michael Cain, FCA
Audit & Accounting Technical Director Nexia International – Australia and New Zealand Chartered Accountants Audit Conference ASA 530 – Audit Sampling and Other Means of Testing charteredaccountants.com.au
2.
Sampling Experiment
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Sampling Experiment
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Sampling Experiment –
Same Birthday?
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Factors that influence
sample size for tests of controls
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Sample size estimation
for attribute sampling
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Reliability factors for
assessing required confidence level
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Factors that influence
sample size for substantive testing
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Illustration of DUS
with systematic selection
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Illustration of DUS
with systematic selection
50.
Evaluation of sample
results for substantive testing
51.
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