Required Readings: Yegidis, B. L., Weinbach, R. W., M 617231

Required Readingsyegidis B L Weinbach R W Myers L L 2018

Research methods for social workers (8th ed.). New York, NY: Pearson. Chapter 9, “Sampling Issues and Options” (pp. ).

Social Work Research: Program Evaluation Discussion 1: Sampling Structures Probability and nonprobability are the two general categories of sampling. Probability sampling uses random selection, whereas nonprobability sampling does not. For example, if you wanted to study the effects of divorce on the psychological development of adolescents, you could gather a population of a certain number of adolescents whose parents were divorced. Then, out of that population, you could randomly select 25 of those people. If you wanted to use nonprobability sampling, you would choose specific people who had met predetermined criteria.

For this Discussion, consider how samples would be chosen for both probability and nonprobability sampling structures. By Day 3 Post your explanation of the following: Using your research problem and the refined question you developed in Week 4, develop two sampling structures: probability and nonprobability. Explain who would be included in each sample and how each sample would be selected. Be specific about the sampling structures you chose, evaluating both strengths and limitations of each.

Paper For Above instruction

The process of selecting appropriate samples is fundamental to the integrity and validity of research studies, especially within social work research. When aiming to understand complex social phenomena, such as the impact of divorce on adolescent psychological development, it is crucial to carefully choose sampling strategies that align with the research objectives. Two primary categories of sampling are probability sampling and nonprobability sampling, each with distinct methods, advantages, and limitations.

Probability Sampling

Probability sampling involves the random selection of participants from a well-defined population, ensuring each individual has a known, non-zero chance of being chosen. This sampling method provides a high level of representativeness and enables generalization of findings to the larger population. For the research problem related to the effects of divorce on adolescents, a probability sample could be constructed using stratified random sampling. First, a comprehensive sampling frame, such as a database of adolescents aged 12-18 whose parents are divorced, would be developed. The population would then be stratified based on key variables such as age, gender, and socioeconomic status to ensure diversity within the sample. Randomly selecting participants from each stratum would help ensure that the sample accurately reflects the population's characteristics.

The strengths of probability sampling include the ability to generalize findings to the broader population, reduction of selection bias, and statistical rigor. It allows researchers to make inferences about the entire population based on the sampled data. However, the limitations involve higher costs, time-consuming procedures, and the necessity for a complete and accurate sampling frame, which can sometimes be difficult to obtain in social work contexts. Additionally, it may not be feasible in settings where a comprehensive list of the target population is unavailable.

Nonprobability Sampling

Nonprobability sampling does not involve random selection and does not give each individual in the population a known chance of inclusion. Instead, participants are selected based on specific criteria or availability. For the same research problem, a nonprobability approach such as purposive sampling could be employed. The researcher could identify adolescents who meet particular criteria—such as those currently experiencing significant psychological distress due to parental divorce—and seek them out through clinics, support groups, or community organizations. This approach enables the researcher to focus on individuals most relevant to the specific research questions.

The strengths of nonprobability sampling include cost-effectiveness, ease of access to hard-to-reach populations, and the ability to target specific subgroups with particular characteristics. Its usability in exploratory or qualitative research is also notable. Nonetheless, this method has notable limitations, including potential bias, limited generalizability, and challenges in assessing the representativeness of the sample. Since participants are not randomly selected, findings may not reflect the broader population, and the research may be susceptible to selection bias.

Evaluation of the Sampling Strategies

Choosing between probability and nonprobability sampling depends on the research aims, resources, and the nature of the population. Probability sampling offers the advantage of representative samples and enables statistical generalizations but requires extensive resources and a complete sampling frame. It is ideal for studies aiming to produce findings applicable to the entire population.

In contrast, nonprobability sampling is more practical, flexible, and suited for exploratory, qualitative, or specialized research where the goal is in-depth understanding rather than broad generalization. However, its limitations in terms of bias and representativeness must be acknowledged, and researchers should exercise caution when interpreting and generalizing findings obtained via nonprobability methods.

In conclusion, both sampling strategies have vital roles within social work research. The choice hinges on the specific research question, the population under study, available resources, and the desired level of inference. Carefully considering the strengths and limitations of each approach ensures the research’s validity, reliability, and applicability to social work practice.

References

• Yegidis, B. L., Weinbach, R. W., & Myers, L. L. (2018). Research methods for social workers (8th ed.). Pearson.
• Plummer, S.-B., Makris, S., & Brocksen, S. M. (Eds.). (2014). Social work case studies: Foundation year. Laureate International Universities Publishing.
• Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
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