14 Oct Examine a case study involving a quantitative design, determining whether the statistical information supports the program’s efficacy and whether there are limiting factors
Even at the data collection stage, the social work researcher needs to know what type of data analysis will facilitate an answer to the research question. The researcher should understand the purpose of each method of analysis, the characteristics that must be present in the study for the design to be appropriate, and any weaknesses of the design that might limit the usefulness of the results. Only then can the researcher select the appropriate design.
Choosing the appropriate design enables the social work researcher to gather the most relevant information about the relationship being studied. Notice that it is not the statistical test itself that deems the research valid; rather, it is the research design. Social workers must be aware of and adjust any limitations of their chosen design that may impact the validity of the study.
In this Discussion, you examine a case study involving a quantitative design, determining whether the statistical information supports the program’s efficacy and whether there are limiting factors.
Review the Learning Resources on analyzing evaluation data, threats to internal validity, and statistics.
Access the Social Work Case Studies media and navigate to the Chi-Square case study.
As you review the case, consider the confounding variables—that is, factors that might explain the difference between those in the program and those waiting to enter the program.
Post a brief outline of the case study and consider the conclusion that “the vocational rehabilitation intervention program may be effective at promoting full-time employment.”
What statistical information shows whether the program was effective (or not)?
Review the factors that limit the internal validity of a study (history, maturation, testing, instrumentation, statistical regression, selection bias, and attrition).
Select and explain which of these factors might limit the ability to draw conclusions regarding cause-and-effect relationships.
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