Read my post and explain how I might rule out one of the confounding variables that they identified by utilizing and citing references. I have also attached Chi-square case study to utilize

Outline the study:

• Define the two groups in the study: 30 individuals who completed the new program (intervention group) and 30 individuals that did not receive the vocational program and remained on the waitlist (comparison group).
• Describe the details of the intervention provided to the treatment group, including type of intervention, frequency, and number of participants: The intervention provided was a vocational rehabilitation program. 30 participants received the intervention, while 30 remained on the waitlist for the same program. Those on the waitlist were to be enrolled in the program after the first group completed the program. The frequency of the program was not provided.
• Provide the outcomes (the categories) of the treatment program that were tallied: Employment data was collected through a survey and tallied as "none", "part-time", or "full-time" employment.
• State the organization of the research design: Group design, where two or more groups were compared and at least one group was a control group.
• Indicate whether randomization occurred: No randomization, we are assuming it was a first-come, first-served assignment.
• Identify the type of variables that were used: categorical variable was employment status in the categories of "none", "part-time", or "full-time".

Explain the outcome

• Was the null hypothesis supported (no differences between group) or rejected? The null hypothesis was rejected. In other words, the vocation group may be effective in encouraging full-time employment for recently paroled inmates.
• What statistical value supports your decision? The Pearson Chi-Square test produced a p-value of 0.003. The p-value is lower than the alpha-level of 0.05. Therefore, the value is statistically significant. As a result, we can reject the null hypothesis.
• Does the resultprovethat the treatmentcausedthe outcome? No, the result does not prove a causal relationship. The value cannot prove that the independent variable caused the change. Additionally, this was not a true experiment because there was no randomization in groups and there was no effort to control for confounding variables.

Offer alternative explanations:

• Maturation can confound results (Flannelly et al., 2018). In this case, maturation could account for some of the change among the recently paroled inmates. Leaving jail/prison and re-entering typical society may yield various social, familial, and psychological changes. Perhaps familial pressures, social norms, etc. led the individuals to acquire jobs rather than solely the vocational program.
• Selection is a requirement of all true experiments (Flannelly et al., 2018). In this study, randomization was not utilized and so the results are confounded. Since the groups were determined based on a first come first-served basis, perhaps individual in group one were more motivated to obtain employment.

References

Flannelly, K. J., Flannelly, L. T., & Jankowski, K. R. B. (2018). Threats to the internal. validity of experimental and quasi-experimental research in healthcare.Journal of Health Care Chaplaincy,24(3), 107-130. https://doi.org/10.1080/08854726.2017.1421019Links to an external site.

Walden University, LLC. (2022). Social work case studies. [Interactive media]. https://waldenu.instructure.com