Respond to at least two colleagues by explaining how that colleague might rule out one of the confounding variables that they identified.

Colleagues Post:

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."

This case study examines the effectiveness of a vocational rehabilitation intervention program in promoting full-time employment for individuals recently paroled. The study utilizes a case study design of 60 participants (30 intervention group and 30 comparison group). The case study involves collecting data on employment status before and after the intervention program. The data is analyzed using appropriate statistical tests to determine the association between the intervention program and the achievement of full-time employment. (Walden, 2022)

What statistical information shows whether the program was effective (or not)?

Compare the percentage of participants employed full-time before and after the intervention. If there is a significant increase in the proportion of participants in full-time employment after completing the program, it suggests the program's effectiveness. The statistical results showed the intervention group which is the first participants were 16.7% not employed, 23.3 % part time employed, and 60% full time employed. The comparison group which is the participates on the waitlist were 55.2% not employed, 24.1% part time employed, and 20.7% full time employed. (Walden University, LLC, 2022).

Review the factors that limit the internal validity of a study (history, maturation, testing, instrumentation, statistical regression, selection bias, and attrition).

There are seven factors that limit the validity of a study. History is a study participant experiences during the course of an experiment that are not part of the experiment itself; therefore, they are extraneous variables (Flannelly, et al, 2018). External events or factors occurring during the study period that can influence the outcome. Maturation is natural changes or developments that participants undergo during the study which may influence their responses or outcomes. This could include physical, social, and psychological changes over time. Testing is shorthand for any form of measuring study outcomes in study participants (Flannelly, et al, 2018). Testing becomes a threat to internal validity if the test itself can affect participants' responses when they are tested again. Instrumentation is the changes in measurement tools or procedures that occur during the study, which can affect the validity of the data collected. Statistical regression is the tendency for individuals who score extremely high or extremely low, relative to the mean or average, on an initial measure of a variable to score closer to the mean of that variable the next time they are measured on it (Flannelly, et al, 2018). Selection bias refers to a potential bias in selecting the participants who will serve in the experimental and control groups (Flannelly, et al, 2018). Attrition is a loss of participants in the experimental and control groups. This can introduce bias if the attrition is related to the study variables. If participants drop out selectively based on their experiences, it can impact the remaining sample and potentially bias the results.

Select and explain which of these factors might limit the ability to draw conclusions regarding cause-and-effect relationships.

Among the factors that can limit the ability to draw conclusions regarding cause-and-effect relationships is selection bias. Selection bias occurs when the process of selecting participants into different groups is not random or representative of the target population. This can introduce differences between groups, making it challenging to establish a relationship between the independent and the dependent variable.

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

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/10.1080/08854726.2017.1421019