Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Chapter 13: Boundary Setting in Experimental-Type Designs A deductive action process

2 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Purposes  To select a subgroup that can accurately represent the population  To draw accurate conclusions about the population by studying a smaller group of elements (representativeness/external validity)

3 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Sequence 1.Define population by specifying criteria a. Inclusion criteria b. Exclusion criteria 2.Develop sampling plan a. Probabilityb. Nonprobability 3.Determine sample size 4.Implement sampling procedures 5.Compare critical values of sample to population

4 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Defining a Population  The research question contains the basic lexical (word) identification of the population  Population parameters (characteristics) are clarified in the literature

5 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Probability (Random) Sampling  Sampling logic based on probability theory  The two basic principles of probability theory as applied to sampling are  The parameters of the population are known  Every member or element has an equal probability or chance of being selected for the sample

6 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Sampling Error  The difference between the values obtained from the sample and the values that actually exist in the population  The degree to which the sample is actually representative of the population  The larger the sampling error, the less representative the sample is of the population and the more limited is the external validity (representativeness) of the study  Random sampling is designed to reduce sampling error

7 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Steps to Compare the Sample to the Population State the hypothesis of no difference (null hypothesis) Select level of significance (probability that defines how rare the sample data must be before the researcher can “fail to accept” the null hypothesis); typically set at 0.05 (means that researcher is 95% confident that the null hypothesis should not be accepted) Compute a statistical value (involves using a formula) Compare statistical value with a critical value; indicates how high the computed sample statistic must be at a given level of significance to fail to accept the null hypothesis Accept or fail to accept the null hypothesis

8 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Steps to Compare the Sample to the Population Accepting the null hypothesis = researcher may want to demonstrate that sample values mirror or represent the population from which the sample was selected Failing to accept the null hypothesis = computed sample value > the critical value; researcher wants to demonstrate that a particular intervention changed the sample significantly from the values represented in the population

9 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Causes of Sampling Error  Random error: those that occur by chance  Systematic error or “systematic bias”: a basic flaw in the sampling process characterized by scores of subjects that systematically differ from the population

10 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Types of Random Sampling  Simple random sampling  With or without replacement  Systematic sampling  Stratified random sampling  Cluster sampling

11 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Nonprobability Sampling  Sample members are not chosen on the basis of equal chance to be selected from a larger group  Used when the parameters of the population are not known or when it is not feasible or ethical to conduct random sample selection  Limits external validity

12 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Types of Nonprobability Sampling  Convenience  Purposive  Quota  Snowball

13 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. Steps to Compare Sample to Population  State hypothesis  Select level of significance  Compute calculated statistical value  Obtain a critical value  Accept or fail to accept null hypothesis

14 Copyright © 2011, 2005, 1998, 1993 by Mosby, Inc., an affiliate of Elsevier Inc. How Big? Considerations for Determining Sample Size  What data analytical procedures will be used?  What is the statistical level of significance? (usually chosen at 0.05 or 0.01 level)  What is the statistical power? (.80 acceptable)  What is the desired effect size?