SPED 596: Research in Special Education

SPED 596: Research in Special Education. Week 6 (7/29-8/04).

Presentation. Review Research Sampling.

Steps in the Research/Scientific Process.

[Audio] This slide outlines a commonly used process for designing and conducting a research project. You should be working this week to define your conceptual model/framework..

[Audio] Conceptual models/frameworks are how researchers thing about their work. Conceptual models/frameworks reveal the beliefs assumptions and relationships between concepts that drives a researcher's view of a socially important issue or problem. On the next few slides are a review of conceptual models/frameworks examples..

[Audio] This is a conceptual model/framework for Person Centered Planning Functional Assessment & Wraparound supports. As you can observe at the center of the conceptual model/framework is a person. Wrapping around that person are social/behavioral supports (for example social emotional learning) academic support (in other words a tiered systems of supports such as response to intervention) and supports from outside of the school or service provider (for example social work mental health). For research addressing issues of student support researchers would consider the social/behavioral and academic needs of the students then seeks to investigate the availability of supports for each of the student's needs..

[Audio] On this slide are six guiding principles to creating an inclusive school. All instruction is guided by General Education All school resources are configured to benefit all students School Proactively addresses social development and citizenship School is data-based learning organization School has open boundaries in relation to its families and its community District supports school-centered approach and extensive systems-change activities required to implement a school-wide model To research topics and issues associated with school inclusion researchers would evaluate any potential responses or solutions using these principles. For example when considering adding additional programs/classes one would consider the extent to which each principle was upheld as part of the decision making process..

[Audio] This slide shows a conceptual model/framework for Universal Design for Learning (U-D-L--). The purpose of U-D-L is to design learning environments to meet the needs of all learners. To accomplish this goal activities lessons and projects are designed with three major features in mind. The major features of U-D-L include: Providing Multiple Means of Representation Providing Multiple Means of Action & Expression Providing Multiple Means of Engagement.

Research Sampling.

[Audio] 11-1 Compare and contrast the viewpoints of researchers who work within the postpositivist constructivist pragmatic transformative and Indigenous paradigms in relation to sampling strategies and generalizability. Definition Selection and Ethics Sampling Strategies: Alternative Paradigms The rationale for using a sampling strategy is: "The simplest rationale for sampling is that it may not be feasible because of time or financial constraints or even physically possible to collect data from everyone involved in an evaluation. Sampling strategies provide systematic transparent processes for choosing who will actually be asked to provide data." Sampling refers to the method used to select a given number of people (or things) from a population. In most research studies it is simply not feasible to collect data from every individual in a setting or population. Sampling is one area where great divergence can be witnessed when comparing the various research paradigms. Researchers who function within the postpositivist paradigm see the ideal sampling strategy as some form of probability sampling. Researchers within the constructivist paradigm tend to use a theoretical or purposive approach to sampling. An important aspect of sampling in the constructivist paradigm: make clear the criteria that were used to select the sample and to clearly describe the characteristics of the members of the sample. Researchers within the transformative paradigm could choose either a probability or theoretical-purposive approach to sampling depending on their choice of quantitative qualitative or mixed methods. Researchers within the pragmatic paradigm can utilize methods from the other paradigms if it seems that these approaches are appropriate to obtaining the answers to the designated research questions. In the Indigenous paradigm building relationships and following cultural protocols is the first step in making decisions about who will provide data in the study. All sampling decisions must be made within the constraints of ethics and feasibility. Although randomized probability samples are set forth as the ideal in the postpositivist paradigm they are not commonly used in educational and psychological research..

[Audio] 11-2 Explain the concepts of external validity and transferability in sampling decisions. External Validity (Generalizability) or Transferability External validity refers to the ability of the researcher (and user of the research results) to extend the findings of a particular study beyond the specific individuals and setting in which that study occurred. Within the postpositivist paradigm the external validity depends on the design and execution of the sampling strategy. Generalizability is a concept that is linked to the target population—that is the group to which we want to generalize findings. In the constructivist paradigm every instance of a case or process is viewed as both an exemplar of a general class of phenomena and particular and unique in its own way. The researcher's task is to provide sufficient thick description about the case so that the readers can understand the contextual variables operating in that setting. The burden of generalizability then lies with the readers who are assumed to be able to generalize subjectively from the case in question to their own personal experiences. Guba and Lincoln (2005) label this type of generalizability transferability..

[Audio] 11-3 Describe challenges in the definition of specific populations in terms of conceptual and operational definitions identifying a person's racial or ethnic status identifying persons with a disability heterogeneity within populations cultural issues and recruitment strategies. Defining the Population and Sample Research constructs can be defined in two ways. Conceptual definitions are those that use other constructs to explain the meaning and operational definitions are those that specify how the construct will be measured. An operational definition of the population in the postpositivist paradigm is called the experimentally accessible population defined as the list of people who fit the conceptual definition. For example the experimentally accessible population might be all the first-grade students in your school district whose names are entered into the district's database. This would be called your sampling frame. Examples of sampling frames include (a) the student enrollment (b) a list of clients who receive services at a clinic (c) professional association membership directories or (d) city phone directories. If the lists are not accurate systematic error can occur because of differences between the true population and the study population. When the accessible population represents the target population this establishes population validity. The researcher must also acknowledge that the intended sample might differ from the obtained sample. The size and effect of nonresponse or attrition should be reported and explained in all approaches to research to address the effect of people not responding choosing not to participate being inaccessible or dropping out of the study. This effect represents a threat to the internal and external validity (or credibility and transferability) of the study's findings..

[Audio] 11-4 Explain the importance of intersectionality in sampling. Identification of Sample Members Examples of errors in identification of sample members can readily be found in research with racial and ethnic minorities and persons with disabilities. Identification of Race and Ethnicity in Populations Investigators who examine racial or ethnic groups and differences between those groups frequently do so without a clear sense of what race or ethnicity means in a research context. Researchers who use categorization and assume homogeneity of condition are avoiding the complexities of participants' experiences and social locations. Race as a biogenetic variable should not serve as a proxy variable for actual causal variables such as poverty unemployment or family structure. Heterogeneity is recognized as a factor that contributes to difficulty in classifying people as African American or Latino. Stanfield recognizes that many people are not pure racially but people are viewed as belonging to specific racial groups in many research studies. Blum (2008) makes clear that use of broad categories of race can hide important differences in communities. Race is sometimes used as a substitute for ethnicity which is usually defined in terms of a common origin or culture resulting from shared activities and identity based on some mixture of language religion race and ancestry. C D Lee (2003) suggests that the contextual nature of race and ethnicity must be considered in the study of ethnic and race relations. Labels obscure important dimensions of diversity within the groups. This has implications for sampling and must be attended to if the results are to be meaningful. The A-P-A Joint Task Force of Divisions 17 and 45's (2017) Guidelines on Multicultural Education Training Research Practice and Organizational Change for Psychologists provide detailed insights into working with four of the major racial/ethnic minority groups in the United States. Diversity within the major groups requires that researchers be responsive to differences in culture and history. The A-P-A Task Force on Race and Ethnicity Guidelines in Psychology (2019) developed Guidelines on Race and Ethnicity in Psychology: Promoting Responsiveness and Equity as a rationale for using a transformative lens in research. "Intersectionality proposes that all people are positioned within socially created categories of oppression and domination such as race culture gender and class that are located within a historical context." Researchers need to be responsive to the heterogeneity within groups and avoid overaggregation that can obscure important differences when making a sampling plan. A transformative lens prompts researchers to ask: What are the dimensions of diversity that are used as a basis of discrimination and oppression in this context? Additional characteristics that are relevant in particular contexts are social class gender sexuality ability and country of origin. With national boundaries eroding people cross boundaries more frequently than ever before resulting in questions about citizenship and nationality. Political instability and factors such as war violence drought and famine have led to millions of people seeking refuge who are essentially stateless. Researchers need to be aware of the status of immigrant and refugee groups in their communities and implications for how they sample in their studies. The APA's Division 27 Society for Community Research and Action released a policy statement that calls for psychologists to resist injustice directed against immigrants and to focus on the systems of oppression oppressors and those being oppressed..

[Audio] 11-4 Explain the importance of intersectionality in sampling. Identification of Sample Members People With Disabilities The federal legislation Individuals with Disabilities Education Act enacted in 1975 and most recently amended in 2015 through Public Law 114–95 the Every Student Succeeds Act includes the following categories of disabilities: Intellectual disabilities. Hearing impairments (including deafness). Speech or language impairments. Visual impairments (including blindness). Serious emotional disturbance. Orthopedic impairments. Autism. Traumatic brain injury. Other health impairments. Specific learning disabilities. Conceptual definitions of these categories can be found in the I-D-E-A legislation. Imagine the diversity of individuals who would be included in a category such as emotional disturbance which is defined in the federal legislation as individuals who are unable to build or maintain satisfactory interpersonal relationships exhibit inappropriate types of behaviors or feelings have a generally pervasive mood of unhappiness or depression have a tendency to develop physical symptoms or fears associated with school problems or have been diagnosed with schizophrenia. Psychologists have struggled for years with finding ways to accurately classify people with such characteristics. A second example of issues that complicate categorizing individuals with disabilities can be seen in the federal definition for people with learning disabilities: General. Specific learning disability means a disorder in one or more of the basic psychological processes involved in understanding or in using language spoken or written that may manifest itself in the imperfect ability to listen think speak read write spell or to do mathematical calculations including conditions such as perceptual disabilities brain injury minimal brain dysfunction dyslexia and developmental aphasia. Disorders not included. Specific learning disability does not include learning problems that are primarily the result of visual hearing or motor disabilities of intellectual disability of emotional disturbance or of environmental cultural or economic disadvantage. The definition indicates several areas in which the learning disability can be manifest. This list alone demonstrates the heterogeneity that is masked when participants in studies are simply labeled "learning disabled." There are the complications that arise in moving from this conceptual definition to the operational definition. How are people identified as having a learning disability? How reliable and valid are the measures used to establish that a student has a learning disability? Many researchers in the area of learning disabilities identify their participants through school records of Individualized Education Programs (IEPs). The Center for Parent Information and Resources (www.parentcenterhub.org) maintains a website that includes information on the identification of children with learning disabilities that is geared to professionals and parents. Cultural issues also come into play in the definition of people with disabilities. For example people who are Deaf use a capital D in writing the word Deaf when a person is considered to be culturally Deaf. The A-P-A (2022) developed Guidelines for Assessment and Intervention With Persons With Disabilities which serves the following goal: The goal of these Guidelines for Assessment and Intervention with Persons with Disabilities is to help psychologists psychology students and psychology training programs conceptualize design and implement effective fair and ethical psychological assessments and interventions with persons with disabilities. The Guidelines emphasize issues of equity and intersectionality that are important for researchers to consider..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Dimensions of Diversity The strategy chosen for selecting samples varies based on the logistics ethics and paradigm of the researcher. An important consideration in choosing a sample is to determine the dimensions of diversity that are important to that particular study. Questions to consider for reflection about salient dimensions of diversity in sampling for focus groups include the following: What sampling strategies are appropriate to provide a fair picture of the diversity within important target populations? What are the dimensions of diversity that are important in gender groups? How can one address the myth of homogeneity in selected cultural groups—for example all women are the same all Deaf people are the same and so on? What is the importance of considering such a concept in the context in which you do research/evaluation?.

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling K M T Collins (2010) divides sampling strategies into probabilistic and purposive. Persons working in the constructivist paradigm prefer the terms theoretical and purposive to describe their sampling. A third category of sampling that is often used but seldom endorsed by proponents of any of the major paradigms is convenience sampling..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Probability-Based Sampling Probability-based sampling is recommended because it is possible to analyze the possible bias and likely error mathematically. Sampling error is defined as the difference between the sample and the population and can be estimated for random samples. Random samples are those in which every member of the population has a known nonzero probability of being included in the sample. Random means that the selection of each unit is independent of the selection of any other unit. Random selection can be done in a variety of ways: Using a lottery procedure drawing well-mixed numbers. Extracting a set of numbers from a list of random numbers. Producing a computer-generated list of random numbers. Simple Random Sampling Simple random sampling means that each member of the population has an equal and independent chance of being selected. The researcher can choose a simple random sample by assigning a number to every member of the population: Using a table of random numbers. Randomly selecting a row or column in that table. Taking all the numbers that correspond to the sampling units in that row or column. Or the researcher could put all the names in a hat and pull them out at random. This sampling strategy requires a complete list of the population. Its advantages are the simplicity of the process and its compatibility with the assumptions of many statistical tests. Disadvantages are that a complete list of the population might not be available or that the subpopulations of interest might not be equally represented in the population. Systematic Sampling For systematic sampling the researcher will take every nth name on the population list. The procedure involves estimating the needed sample size and dividing the number of names on the list by the estimated sample size. The advantage of this sampling strategy is that you do not need to have an exact list of all the sampling units. It is sufficient to have knowledge of how many people (or things) are in the accessible population and to have a physical representation for each person in that group. Systematic sampling strategy can be used to accomplish de facto stratified sampling. One caution in the use of systematic sampling: if the files or invoices are arranged in a specific pattern that could result in choosing a biased sample. Stratified Sampling This type of sampling is used when there are subgroups (or strata) of different sizes that you wish to investigate. The researcher then needs to decide if they will sample each subpopulation proportionately or disproportionately to its representation in the population. Proportional stratified sampling means that the sampling fraction is the same for each stratum. This type of stratification will result in greater precision and reduction of the sampling error especially when the variance between or among the stratified groups is large. The disadvantage of this approach is that information must be available on the stratifying variable for every member of the accessible population. Disproportional stratified sampling is used when there are big differences in the sizes of the subgroups as mentioned previously in gender differences in special education. Disproportional sampling requires the use of different fractions of each subgroup and thus requires the use of weighting in the analysis of results to adjust for the selection bias. The advantage of disproportional sampling is that the variability is reduced within the smaller subgroup by having a larger number of observations for the group. The major disadvantage of this strategy is that weights must be used in the subsequent analyses; however most statistical programs are set up to use weights in the calculation of population estimates and standard errors..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Probability-Based Sampling Cluster Sampling Cluster sampling is used with naturally occurring groups of individuals—for example city blocks or classrooms in a school. This approach is useful when a full listing of individuals in the population is not available but a listing of clusters is. Cluster sampling is also useful when site visits are needed to collect data; the researcher can save time and money by collecting data at a limited number of sites. The disadvantage of cluster sampling is apparent in the analysis phase of the research. Multistage Sampling This method consists of a combination of sampling strategies and is described by K M T Collins (2010) as "choosing a sample from the random sampling schemes in multiple states." The calculations of statistics for multistage sampling become quite complex; researchers need to be aware that too few strata will yield unreliable extremes of the sampling variable. Complex Sampling Designs in Quantitative Research Spybrook and others (2016) discuss sampling issues involved in complex designs like: Cluster randomized trials. Multisite randomized trials. Multisite cluster randomized trials. Cluster randomized trials with treatment at level three. Trials with repeated measures. Cluster randomized trials with repeated measures. The sampling issues arise because these research approaches involve the assignment of groups rather than individuals to experimental and control conditions. This complicates sampling issues because the n of the clusters may be quite small and hence limit the ability of the researcher to demonstrate sufficient power in the analysis phase of the study. Spybrook and colleagues developed a sophisticated analytic procedure that accommodates the small cluster sizes while still allowing larger sample sizes within the clusters to be tested appropriately..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Examples of Sampling in Quantitative Studies Researchers in education and psychology face many challenges in trying to use probability-based sampling strategies. Probability-based sampling is generally easier to do with survey research when a list of people in the population is available. Many professional associations keep lists of their membership and these can usually be sampled for a fee. In Broadus and Evans's (2015) study of attitudes toward addiction they used an online survey company that randomly selected participants from its email databases using the criteria of being over the age of 18 and stratified by gender. Henry and others (2006) conducted an evaluation study of early childhood education in the state of Georgia. They were able to randomly select 4-year-olds receiving early education services either through Head Start (a federal program) or in a Georgia pre-K program (a state program). Thoughtful strategies are needed in applying random sampling principles in research in education and psychology..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Purposeful and Theoretical Sampling Qualitative sampling includes strategies not only for selecting people but also for sampling a wide variety of data sources. It is important that the researcher make clear the sampling strategy and its associated logic to the reader. Extreme or Deviant Cases The criterion for selection of cases might be to choose individuals or sites that are unusual or special in some way. The researcher might choose to study highly successful programs and compare them with programs that have failed. Study of extreme cases might yield information that would be relevant to improving more "typical" cases. The researcher assumes that studying the unusual will illuminate the ordinary. The criterion for selection then becomes the researcher's and users' beliefs about which cases they could learn the most from. Intensity Sampling Intensity sampling is somewhat similar to the extreme-case strategy except there is less emphasis on extreme. The researcher wants to identify sites or individuals in which the phenomenon of interest is strongly represented. Critics of the extreme or deviant-case strategy might suggest that the cases are so unusual that they distort the situation beyond applicability to typical cases. Intensity sampling requires knowledge on the part of the researcher as to which sites or individuals meet the specified criterion. Maximum-Variation Sampling Sites or individuals can be chosen based on the criterion of maximizing variation within the sample. The researcher can identify sites located in isolated rural areas urban centers and suburban neighborhoods to study the effect of total inclusion of students with disabilities. The results would indicate what is unique about each situation as well as what is common across these diverse settings. Homogeneous Sampling In contrast to maximum-variation sampling homogeneous sampling involves identification of cases or individuals that are strongly homogeneous. The researcher seeks to describe the experiences of subgroups of people who share similar characteristics. Homogeneous sampling is the recommended strategy for focus group studies. Researchers who use focus groups have found that groups made up of heterogeneous people often result in representatives of the "dominant" group monopolizing the focus group discussion..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Purposeful and Theoretical Sampling Typical-Case Sampling If the researcher's goal is to describe a typical case in which a program has been implemented this is the sampling strategy of choice. Typical cases can be identified by recommendations of knowledgeable individuals or by review of extant demographic or programmatic data that suggest that this case is indeed average. Stratified Purposeful Sampling This is a combination of sampling strategies such that subgroups are chosen based on specified criteria and a sample of cases is then selected within those strata. The cases might be divided into highly successful average and failing schools and the specific cases can be selected from each subgroup. Critical-Case Sampling Patton (2002) describes critical cases as those that can make a point quite dramatically or are for some reason particularly important in the scheme of things. If a program of inclusion can be deemed to be successful in that community it suggests that it would be possible to see that program succeed in other communities in which the parents are not so satisfied with the separate education of their children with disabilities. Snowball or Chain Sampling Snowball sampling is used to help the researcher find out who has the information that is important to the study. The researcher starts with key informants who are viewed as knowledgeable about the program or community. The researcher asks the key informants to recommend other people to whom the researcher should talk based on their knowledge of who should know a lot about the program in question. The list grows (like a snowball) as names are added through the referral of informants..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Purposeful and Theoretical Sampling Criterion Sampling The researcher must set up a criterion and then identify cases that meet that criterion. For example a huge increase in referrals from a regular elementary school to a special residential school for students with disabilities might lead the researcher to set up a criterion of "cases that have been referred to the special school within the last 6 months." Theoretical Sampling Guided by an evolving theory (one that emerges throughout the data collection and analysis) with the aim to develop categories and to integrate those categories in ways that reveal their relationship to a theory being developed. They include not only the sampling of the data source but also the sampling of the concepts to pursue in the research. Theoretical sampling is an ongoing process that might start with a researcher who wants to study the meaning of a theoretical construct such as creativity or anxiety. The researcher may start with the theoretical construct of anxiety in terms of social stresses that create anxiety and therefore have an initial sampling strategy that focuses on individuals who "theoretically" should exemplify that construct. As the theory of anxiety evolves the researcher may decide that there are other contexts or individuals or data sources that need to be included. Confirming and Disconfirming Cases The researcher is interested in emerging theory that is always being tested against data that are systematically collected. The "constant comparative method" requires the researcher to seek verification for hypotheses that emerge throughout the study. The application of the criterion to seek negative cases suggests that the researcher should consciously sample cases that fit (confirming) and do not fit (disconfirming) the theory that is emerging. Opportunistic Sampling Researchers seldom establish the final definition and selection of sample members prior to the beginning of the study. When opportunities present themselves to the researcher during the course of the study the researcher should make a decision on the spot as to the relevance of the activity or individual in terms of the emerging theory. Opportunistic sampling involves decisions made regarding sampling during the course of the study..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Purposeful and Theoretical Sampling Purposeful Random Sampling In qualitative research samples tend to be relatively small because of the depth of information that is sought from each site or individual. Random sampling strategies can be used to choose those who will be included in a very small sample. Sampling Politically Important Cases The rationale for sampling politically important cases rests on the perceived credibility of the study by the persons expected to use the results. if a program has been implemented in a number of regions a random sample might (by chance) omit the region in which the legislator who controls funds for the program resides. The researcher might choose purposively to include that region in the sample to increase the perceived usefulness of the study results. Researchers working in political environments should be aware that sampling may require attention to factors related to political credibility beyond concerns for scientific validity. Case Study Sampling Stake (2006) provides direction for choosing the sample for case study research that depends on the purpose of the case study as well as on logistics likely receptiveness and available resources. Three approaches to case studies: Intrinsic case studies are conducted when a particular case is of specific interest such that the case is in essence already decided before the research begins. Instrumental case studies are undertaken to gain an understanding of a phenomenon with the goal of enhancing ability to generalize to other cases for example improving race relations. Collective case study (also known as multiple case study) is an approach in which several cases are selected to study because of a desire to understand the phenomenon in a broader context. For each of these three types of case studies sampling decisions still need to be made with regard to persons specific locations events timing subgroups and dimensions..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Examples of Qualitative Research Sampling Lowrey and others conducted a narrative inquiry that used the following sampling strategies to recruit teachers from the United States and Canada: Efforts included the following: (a) posting a study flyer in professional groups on social media (b) sending emails to colleagues at higher education institutions centers like the School Integrated Framework for Transformation (S-W-I-F-T) school network and state/ provincial boards of education (c) distributing fliers at an annual tash conference and during a professional development event hosted by the U-D-L I-R-N and (d) posting a call for participation on the UDL IRN and C-A-S-T websites. To be considered for this study the participants needed to meet the following inclusion criteria: First all participants were to be general education teachers. Second they were to work in a district that went through a district-wide implementation of U-D-L-. Third they were to be practicing UDL-aligned teaching for at least 1 year. Finally they were to have at least one student with a severe ID included in their class. Nelson and others identified the sample for their study of adolescent recovery from substance abuse using a purposeful sampling strategy of self-identified alumni of the treatment program..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Convenience Sampling Convenience sampling means that the persons participating in the study were chosen because they were readily available. Much psychological research has been conducted using undergraduate students in psychology classes because they are available. The researcher must acknowledge the limitations of the sample and not attempt to generalize the results beyond the given population pool..

[Audio] 11-5 Describe and give examples of strategies for designing and selecting samples including probability based theoretical-purposive and convenience sampling as well as for sampling for complex designs such as mixed methods designs and those using hierarchical linear modeling. Sampling Strategies: Types of Sampling Mixed Methods Sampling Mixed methods researchers cannot escape the complexities in sampling for either quantitative or qualitative research; rather their challenges are magnified by having both sets of issues plus the complexity of mixed methods to deal with. These design options influence the sampling strategies for mixed methods which include: Identical sampling. Parallel sampling. Nested sampling. Multilevel sampling. James and others (2022) provide an example of integrating transformative considerations in a mixed methods study with a focus on diversity and engaging typically excluded populations. Their study was designed to develop and revise a conceptual model of emergency department use by Deaf and hard-of-hearing adults in the United States. James and others established a community-based advisory board that informed them about the diversity within the population. They described their contribution to the mixed methods literature as follows: The method described in this paper contributes to M-M-R methodology in four primary ways: (1) centering the transformative paradigm throughout a M-M-R study; (2) including transformative considerations in joint displays; (3) providing a structure to improve reporting in mixed methods community-based participatory research (MMCBPR) designs; and (4) increasing transparency in M-M-R reporting..

[Audio] 11-6 Discuss the importance of sampling bias access issues and sample size. Sampling Bias Sampling bias is important because it can invalidate the findings of a study or reduce the researcher's ability to generalize the results. Bias can arise for a number of reasons: Nonresponse to the instrument or items on an instrument. Incorrect representation in the sample of the population. Incorrect sampling frame. Self-selection bias. In the constructivist spirit bias in sampling takes on a different meaning. The researchers' intent is not to select a sample from a population in order to establish the margin of error in order to generalize from the sample to the population. The exercise of interacting with participants and using a peer reviewer are also designed to make visible any biases that might exist in the sample. Qualitative researchers are encouraged to examine the difference who and what is included in the study makes as well as who conducts the study. The idea of "thick description" in writing applies to the sampling process the participants in the study and the choice of elements that are sampled so that readers can have the necessary information to judge the findings for themselves. Roulston and Shelton (2015) suggest that qualitative researchers (and their readers) ask themselves the following questions to illuminate any possible biases and the complexities of constructing knowledge: Are authors transparent about their theoretical allegiances? Do authors discuss how the epistemologies and theoretical paradigms that they use are implicated in the design of a study? Given the theoretical assumptions of a study what research designs methods and strategies are appropriate to shed light on the phenomenon under examination? What methods were overlooked? Why? The concept of bias in sampling is quite different in a constructivist paradigm than in a postpositivist one..

[Audio] 11-6 Discuss the importance of sampling bias access issues and sample size. Access Issues Accessibility to a sample or population is an important factor to consider when making decisions about sampling designs. For some populations such as users of illegal drugs people experiencing homelessness or undocumented immigrants it might not be possible to obtain a complete listing of the members of the population thus making it difficult to use the probability-based sampling strategies. The likelihood of a population being accessible or willing to respond to mail phone or online surveys should also be considered. When working with communities of color Indigenous communities and immigrant groups researchers should be aware of the importance of history in determining willingness to participate in a research study. Because of a history of broken trust members of these communities may be unwilling to participate in research because they do not trust the government. One useful strategy is to identify organizations that were viewed as having credibility in the various communities..

[Audio] 11-6 Discuss the importance of sampling bias access issues and sample size. Access Issues Access in Educational Settings Accessing samples in educational settings can be a long process to finally reach agreement with the appropriate persons. Identification of the appropriate persons who have the power to grant access is a complex issue in itself. Early contacts can be helpful to ascertain procedures test the waters and cultivate advocates for your later more formal requests. Researchers should be aware of complications from real life that can present obstacles to sampling as it is ideally conceived. Researchers need to adjust their sampling plans to allow for working with intact groups. Researchers who wish to use stratified sampling should also be aware of the complexities of subdividing the sample on the basis of gender race or ethnicity disability or ability levels within a school setting. There are the logistical and ethical obstacles to using stratification. Options for issues that complicate sampling with special education populations: Selecting individuals from the general population. Comparisons across disability categories. Cross-unit comparisons that involve the comparison of students with disabilities in one school or school district with students in another school or school district. Longitudinal studies that allow comparisons with one group at two or more points in time..

[Audio] 11-6 Discuss the importance of sampling bias access issues and sample size. Access Issues Access to Records The researcher needs to be concerned with the accessibility of the records for research purposes. Researchers might want to sample the desired records on a pilot basis to ensure that the records contain the information required for the study and that they are appropriately organized for the research study. The researcher must also be able to demonstrate how the confidentiality of the records will be protected. The researcher can then consider the feasibility and appropriateness of alternative means of achieving access to the archival information like: Asking the agency to provide the records with identifying information deleted. Asking if an employee of the agency could be paid to code the information from the records without names. Determining if it is possible to obtain a computer printout with codes in place of personal identification information..

[Audio] 11-6 Discuss the importance of sampling bias access issues and sample size. Sample Size The optimum sample size is directly related to the type of research you are undertaking. Rules of Thumb Quantitative Research Rules of Thumb K M T Collins and others (2007) calculated the size of samples needed for correlational causal comparative and experimental research in order to find a "medium . . . one-tailed and/or two-tailed statistically significant relationship or difference with .80 power at the 5% level of significance." The recommended sample sizes for multiple regression and survey research come from Gall and others (2015). Qualitative Research Rules of Thumb The sample size decisions are more dynamic in qualitative research than in quantitative research. The number of observations is not determined in the former type of research prior to data collection. A researcher makes a decision as to the adequacy of the observations on the basis of having identified the salient issues and finding that the themes and examples are repeating instead of extending. Sample size is integrally related to length of time in the field. Qualitative researchers are often challenged by these questions: How do you know you have enough data? How do you know when it is time to stop? Sometimes researchers stop collecting data when their time and money run out especially in program evaluation studies. Researchers need to plan carefully to ensure that they maximize the time and money available to them in order to do the best study within the constraints of the context. Charmaz's (2014) advice reflects a perspective that is less bound by these constraints and is more situated in the concept of "saturation.".

[Audio] 11-6 Discuss the importance of sampling bias access issues and sample size. Sample Size Formulaic Determination of Sample Size Myors and Murphy's (2023) book describes the logic and procedure for selection of sample size when the researcher is conducting a quantitative study of treatment effectiveness. The ability to detect statistically significant differences is determined in part by the amount of variability in one's dependent measure within the sample: Less variability = greater sensitivity. More variability = less sensitivity Sample size has a direct relationship with variability: Larger sample sizes = less variability Smaller sample sizes = more variability Putting the logic of these two statements together it is easier to obtain statistical significance if you have a larger sample. There is one sticking point: Larger samples = more costly Smaller samples = less costly Another important concept that enters the discussion of sample size calculation is the power of a statistical test. Power in one sense is the quantification of the sensitivity. Sensitivity or power in statistical language is described in terms of probability of finding a difference when there really is one there. If one claims that they do have a real difference but they really do not this is called a Type I error. Researchers establish a level of Type I error that they are willing to live with and this is called an alpha level (α). If one claims that they do not have a real difference but they really do this is a Type II error (or beta or β). Assumptions that underlie the use of simplistic formulas: The data must be from a simple random sample. The formula is not correct for any sampling designs that are more complex than a simple random sample. There are no correct methods for data that are haphazardly collected with bias of unknown size. Outliers can have a large effect on the confidence interval; therefore extreme values should be corrected or removed before conducting the analysis. Small sample sizes and nonnormality in the population can change the confidence level. Gall and others (2015) present the following formula for estimating the size of sample needed: N equals 2 seconds squared times 4 tons squared over D N = number of people needed in each group s = standard deviation of your dependent variable t = t-test value needed to get your desired alpha level D = estimated difference between experimental and control groups Much educational and psychological research is doomed to failure before any data are collected because of insufficient power to detect the effects of an intervention. Sample size is also influenced by the willingness of the people chosen to participate in the study..

[Audio] 11-7 Explain the ethical standards for the protection of study participants and procedures for ethical review in terms of various types of ethical review boards including institutional review boards and community-based review boards. Ethics and Protection of Study Participants There are specific implications for ethical behavior related to the protection of people who participate in the studies. Most novice researchers encounter serious questions about the ethics of their planned research within the context of their institutions' institutional review boards (IRBs) human subjects committees ethical review boards or community-based ethical review boards. In the United States an I-R-B is a committee mandated by the National Research Act Public Law 93–348. Institutional I-R-Bs are encouraged or mandated (if federally funded) to have members who are nonscientists in order to include a more community-based appraisal of the ethics of a piece of research. Community-based review boards can also ensure that culturally relevant research strategies are used and that the community actually benefits from the research. Community-based review boards are recommended when working with marginalized populations such as the L-G-B-T-Q plus community or older people. Researchers who work in Indigenous communities should also be aware of the need to obtain approval from a tribal ethics review board. I-R-Bs need to approve all research that is conducted that involves human subjects. Certain exemptions to I-R-B approval are relevant to research conducted with schoolchildren. Common exemptions in educational and psychological research include: Research that is conducted in established or commonly accepted educational settings involving normal education practices such as instructional strategies or classroom management techniques. Research that involves the use of educational tests if unique identifiers are not attached to the test results..

[Audio] 11-7 Explain the ethical standards for the protection of study participants and procedures for ethical review in terms of various types of ethical review boards including institutional review boards and community-based review boards. Ethics and Protection of Study Participants Informed Consent Informed consent needs to be obtained from the participants before collecting data. H-H-S (2018 p 13) provides this guidance for constructing an informed consent form: A statement that the study involves research an explanation of the purposes of the research and the expected duration of the subject's participation a description of the procedures to be followed and identification of any procedures that are experimental. A description of any reasonably foreseeable risks or discomforts to the subject. A description of any benefits to the subject or to others that may reasonably be expected from the research. A disclosure of appropriate alternative procedures or courses of treatment if any that might be advantageous to the subject. A statement describing the extent if any to which confidentiality of records identifying the subject will be maintained. For research involving more than minimal risk an explanation as to whether any compensation and an explanation as to whether any medical treatments are available if injury occurs and if so what they consist of or where further information may be obtained. An explanation of whom to contact for answers to pertinent questions about the research and research subjects' rights and whom to contact in the event of a research-related injury to the subject. A statement that participation is voluntary refusal to participate will involve no penalty or loss of benefits to which the subject is otherwise entitled and the subject may discontinue participation at any time without penalty or loss of benefits to which the subject is otherwise entitled..

[Audio] 11-7 Explain the ethical standards for the protection of study participants and procedures for ethical review in terms of various types of ethical review boards including institutional review boards and community-based review boards. Ethics and Protection of Study Participants Marginalized Populations and Informed Consent Informed Consent and Children: parents are usually the people who have legal authority to give permission for research participation for their children under the age of 18. However ethical practice calls for getting "assent" from children by explaining the study to them in language that is understandable to them and getting their agreement to participate. Informed Consent and Older People: older people may need special care in terms of ascertaining if they consent to participate in research. Informed Consent and People With Mental Illness: people with mental illness vary in terms of their abilities to provide informed consent. Indigenous and Postcolonial Peoples and Research Ethics: Indigenous and postcolonial peoples contribute critically important insights into ethics not only for research in their own communities but also as a way of understanding broader ethical issues in the surrounding world..

[Audio] 11-7 Explain the ethical standards for the protection of study participants and procedures for ethical review in terms of various types of ethical review boards including institutional review boards and community-based review boards. Ethics and Protection of Study Participants Confidentiality and Anonymity Confidentiality means that the privacy of individuals will be protected in that the data they provide will be handled and reported in such a way that the data cannot be associated with the research participants personally. Anonymity means that no uniquely identifying information is attached to the data and thus no one not even the researcher can trace the data back to the individual providing them. Confidentiality and anonymity promises can sometimes be more problematic than anticipated. What happens when the courts demand to see your research data even after you have promised confidentiality to the participants? A Certificate of Confidentiality might provide an avenue to protect participants..

[Audio] 11-7 Explain the ethical standards for the protection of study participants and procedures for ethical review in terms of various types of ethical review boards including institutional review boards and community-based review boards. Ethics and Protection of Study Participants Confidentiality and Anonymity Transformative researchers suggest that the expectation of confidentiality or anonymity that represents the status quo in research may be misguided. Baez (2002) makes the case that confidentiality protects secrecy and thus hinders transformative political action. Researchers need to be cognizant of the repercussions of revealing the identity of persons who provide data. Several other scholars write about the complexity of confidentiality: Ntseane (2009) conducted a study of poverty reduction in Africa based on data collected from women who owned businesses. Dodd (2009) discussed the real dangers of revealing the identities of youth who are lesbian gay bisexual transgender or queer who had not revealed this to their parents teachers or others in the outside community. Brabeck and Brabeck (2009) collected data from Spanish-speaking women who were abused by their spouses. J A King and others (2004) wrestled with the question of revealing identities when the study they conducted indicated that an incompetent manager was responsible for the failure of a program. Bhattacharya (2007) proposed modifications to I-R-B guidelines that would acknowledge the fluid nature of consenting and ways the researcher could be responsive to potential departures from the traditional form. If a participant does not fully understand the implications of revealing details about their life alternative means might be used to elicit the degree of revelation that is safe and comfortable. Federal legal requirements concerning confidentiality include the following: The Buckley Amendment which prohibits access to children's school records without parental consent. The Hatch Act which prohibits asking children questions about religion sex or family life without parental permission. The National Research Act which requires parental permission for research on children. There are two circumstances in which the I-R-B can choose not to require parental permission: If the research involves only minimal risk (in other words no greater risk than in everyday life) parental permission can be waived. If the parent cannot be counted on to act in the best interests of the child parental permission can be waived. This circumstance usually involves parents who have been abusive or neglectful. The research participants should also be informed that researchers are required by law to inform the appropriate authorities if they learn of any behaviors that might be injurious to the participants themselves or that cause reasonable suspicion that a child an older person or a dependent adult has been abused..

[Audio] 11-7 Explain the ethical standards for the protection of study participants and procedures for ethical review in terms of various types of ethical review boards including institutional review boards and community-based review boards. Ethics and Protection of Study Participants Deception in Research Studies The American Psychological Association (2016) recognizes that deception and invasion of privacy must be given serious consideration in research planning. Deception is an ethical problem that has been debated in the research community for many years. Most professional associations' ethical guidelines for psychologists and educators prohibit the use of deception unless it can be justified and the effect of the deception "undone" after the study is completed. The undoing of deception is supposed to be accomplished by debriefing the research participants after the research study; this means that the researcher explains the real purpose and use of the research. Guba and Lincoln (1989) maintained that the allowance of deception in research settings was one of the main failings of the postpositivist paradigm. They point out that the professional associations' codes of ethics that focus on harm are inadequate to guard against the harm that results from discovering that you have been duped and objectified. They point out the contradiction in using deception to serve the search for "truth" through science. Lincoln (2009) argues that deception cannot be a part of the constructivist paradigm because the goal is to collect and debate the various multiple constructions of the different constituencies affected by an issue. Researchers functioning within the constructivist paradigm are not immune to ethical challenges..

[Audio] 11-8 Examine the sampling definition selection and application of ethical review strategies in research studies using the questions provided. Questions for Critically Analyzing Sampling Strategies All of these questions might not be equally important for research conducted within the different paradigms. What is the population of interest? How was the sample chosen—probability purposeful or convenience sampling? What are the strengths and weaknesses of the sampling strategy? What are the characteristics of the sample? To whom can you generalize or transfer the results? Is adequate information given about the characteristics of the sample? How large is the population? How large is the sample? What is the effect of the sample size on the interpretation of the data? Is the sample selected related to the target population? Who dropped out during the research? Were they different from those who completed the study? In qualitative research was thick description used to portray the sample? In qualitative research what is the effect of using purposive sampling on the transferability to other situations? Are female participants excluded even when the research question affects both men and women? Are male subjects excluded even when the research affects both women and men? Does the researcher report the sample composition by gender and other background characteristics such as race or ethnicity and class? How does the researcher deal with the heterogeneity of the population? Are reified stereotypes avoided and adequate opportunities provided to differentiate effects within race/gender/disability group by other pertinent characteristics (for example economic level)? How did the researcher address ethical issues particular to the characteristics of the participants (for example older age groups children Indigenous communities sexual minorities and people with mental illness)? Did the researcher objectify the human beings who participated in the research study? Did the researcher know the community well enough to make recommendations that will be found to be truly useful for community members? Did the researcher adequately acknowledge the limitations of the research in terms of contextual factors that affect its generalizability or transferability? Whose voices were represented in the research study? Who spoke for those who do not have access to the researchers? Did the researchers seek out those who are silent? To what extent are alternative voices heard? If deception was used in the research did the researcher consider the following issues: Could participant observation interviews or a simulation method have been used to produce valid and informative results? Could the people have been told in advance that deception would occur so they could then consent to waive their right to be informed? How are the privacy and confidentiality of the participants ensured? If you are studying bad behavior have the people agreed to participate in the study? Can you run a pilot group in which you honestly inform people of the type of behavior you are studying and determine if they would agree to participate? If studying bad behavior is the behavior induced? How strongly? How will debriefing and desensitizing (removing any undesirable emotional consequences of the research) be handled? Is the study important enough and well designed enough to justify deception?.