Respond to post below: “Based on power analysis for sample size, what is the ant

Respond to post below:
“Based on power analysis for sample size, what is the anticipated sample size for your project and on what basis will you make your sample size decision?
Appropriate sample size or power analysis is important in a research study. The sample size must be significant enough, that it represents the population. Having an appropriate size is helpful in can determining an estimation of the therapeutic effect, Hyun (2021). Insufficient sampling or power analysis can derive incorrect information regarding the outcomes or intervention. To determine if the evidence-practice changes or interventions, would require a sample size that is a good representation of the population being studied. Too small a sample size can be misrepresentative of the entire population, while too large a sample can result in many variables outside the scope of the study. The ability to infer regarding the population.
In consideration of sample size, the cost of implementing interventions to determine the validity of a study is important according to Pung et al. (2019). In consideration of the appropriate sample size for the pilot study, the sample must be representative of the whole population being studied. The sample size of fifty patients was determined. The participants utilize the large hospital system within the community. The patients all have Medicaid insurance, and experience disparities in health and healthcare delivery. One of the important outcomes of the pilot study is to improve, physician involvement in decreasing healthcare disparities among the study population (Guttman, 2021). Identifying health disparities that exist among the study population helps physicians in understanding health barriers due to health disparities and provides interventions for at-risk communities. Patients admitted to the hospital represent the patient population in the community being studied. Power is represented in percentages (Dziadkowiec, 2021). If the sample size is too small it results in Type II errors. A power of 80% indicates that the null hypothesis has been rejected. The effect size, however, makes assumptions about the study population or differences in the study groups. It is not realistic to use an entire population but a sample size that is a good representation of the population is appropriate.
In conclusion, determining the appropriate sample size for a study is important to the outcome of the study. The sample must be a representation of the population being studied. Sample size helps to support the hypothesis for the study. The appropriate sample size will help determine if the proposed intervention is supported by the results of the study.
References
Dziadkowiec, O. (2021). Use of statistical power analysis in prospective and retrospective research. JOGNN: Journal of Obstetric, Gynecologic & Neonatal Nursing; 50(2): 19- 121.
Guttman, K.C. (2021). Investigators uncover health care disparities among US patients.
Ophthalmology Times; 46(4): 26-26
Hyun, K. (2021) Sample size determination and power analysis using the G-power software.
Journal of Educational Evaluation for Health Professions;18: 1-12.
Pung, L., Maher, C., & Granger, B.B (2019). Determining Sample Size in Improvement Science Study. AACN Advanced Critical Care; 30(2): 193-197.