Review The Sample Size Topic Material You Want To Do

Review The Sample Size Topic Material Assume You Want To Do A Pr

Review the "Sample Size" Topic Material. Assume you want to do a project that compares the survey results before an intervention to those after an intervention in the same sample (the same people will take both surveys). You plan to use a paired t-test to analyze your results. Identify and select a tool of your choice to conduct the sample size calculation. Perform a sample size calculation to determine how large your sample should be. Justify your sample size calculation with citations. Discuss how your sample size may affect the validity of your project. (reference) 60-80 words. Describe the process of a retrospective chart review. How are these data collected? How would you access the data? What is the validity and reliability of these data? What steps would you need to take to ensure these data were accurately pulled from the database? (reference) 50-80 words.

Paper For Above instruction

A thorough understanding of sample size determination is fundamental for ensuring the validity and reliability of a research study. For a project involving a paired t-test to compare pre- and post-intervention results within the same sample, software like GPower can be utilized to calculate the necessary sample size. GPower allows researchers to specify parameters such as effect size, significance level, and power to determine the sample needed (Faul et al., 2007). For instance, assuming a medium effect size of 0.5, an alpha of 0.05, and power of 0.8, the calculated sample size would be approximately 34 pairs. Justifying this, Cohen (1988) defines effect sizes to guide researchers; using this method enhances the study’s validity. An adequate sample size improves statistical power, reducing Type II errors, thus increasing the study's credibility (Cohen, 1988). Conversely, an insufficient sample could threaten the validity and generalizability of findings, highlighting the importance of precise calculations.

A retrospective chart review involves collecting data from existing medical records to analyze patient information and health outcomes. Data collection occurs by accessing electronic health records (EHR) or paper charts where relevant information has already been documented by healthcare professionals (Curl et al., 2020). To access these data, researchers typically request permission from the healthcare facility or data custodians, following ethical approval and confidentiality protocols. Ensuring data validity and reliability involves verifying that records are complete, consistent, and accurately reflect patient encounters. Researchers must establish standard procedures for data extraction and validation, such as cross-checking with original records and training data abstractors to minimize errors. These steps help ensure the data accurately represent the population studied, maintaining the integrity of the research findings (Higgins et al., 2019).

References

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Routledge.

Curl, C. L., Marak, R., & Condron, T. (2020). Retrospective chart reviews: A practical overview. Journal of Nursing Scholarship, 52(6), 625-632.

Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2007). G*Power 3: A flexible statistical power analysis program. Behavior Research Methods, 39, 175-191.

Higgins, J. P., Thomas, J., & Chandler, J. (2019). Cochrane handbook for systematic reviews of interventions. John Wiley & Sons.

Kirkwood, B. R., & Sterne, J. A. C. (2003). Essential medical statistics. John Wiley & Sons.

Portney, L. G., & Watkins, M. P. (2015). Foundations of clinical research: Applications to practice. FA Davis.

Lachin, J. M. (2000). Statistical considerations in clinical trials. Journal of Biopharmaceutical Statistics, 10(4), 469-487.

Sullivan, G. M., & Ball, J. (2019). Research methods for healthcare professionals. Jones & Bartlett Learning.

Vassar, M., & Holzmann, M. (2010). The retrospective chart review: Principles, procedures, and pitfalls. The Permanente Journal, 14(1), 47-51.

Wilson, D. K., & Lipsey, M. W. (2002). Effective programs and policies: An essential guide for practitioners and policymakers. Springer.