Selecting Appropriate Analysis Techniques For Studies
Selecting Appropriate Analysis Techniques For Studiesques
Exercise 23: Selecting Appropriate Analysis Techniques for Studies Questions to Be Graded Name: Class: Date: : A researcher surveyed two groups of professionals, nurse practitioners and physicians, and asked them whether or not they supported expanding the role of nurse practitioners’ (NPs) prescribing privileges, answered as either “yes” or “no.” Her research question is: Is there a difference between NPs and physicians on proportions of support for expanded prescription privileges? What is the appropriate statistic to address the research question? Answer: - 2: What statistic would be appropriate for an associational research question involving the correlation between two non-normally distributed, skewed continuous variables? Answer: - 3: A researcher is interested in the extent to which years of practice among NPs predicts level of support for expanded prescription privileges, measured on a 10-point Likert scale. She finds that both variables, years of practice and level of support, are normally distributed. Her research question is: Does years of practice among NPs predict level of support for expanded prescription privileges? What is the appropriate statistic to address the research question? Answer: - 4: What statistic would be appropriate for a difference research question involving the comparison of two independent groups on a normally distributed continuous dependent variable? Answer: - 5: A statistics professor tests her students’ level of knowledge at the beginning of the semester and administers the same test at the end of the semester. She compares the two sets of continuous scores. Her research question is: Is there a difference in statistics knowledge from the beginning to the end of the semester? What is the appropriate statistic to address the research question, if the scores are normally distributed? Answer: - 6: What is the appropriate statistic to address the research question in Question 5 if the scores are NOT normally distributed? Answer: - 7: What is the appropriate statistic to identify the association between two dichotomous variables, where the researcher is interested in identifying the odds of an outcome occurring? Answer: - 8: In the case of a skewed, continuous dependent variable? Answer: - 9: A nurse educator is interested in the difference between traditional clinical instruction in pediatrics and simulated pediatrics instruction in a BSN (Bachelor of Science in Nursing) program. She randomizes students to receiving 50 hours of either traditional clinical rotations in a pediatrics department or 50 hours of simulated instruction in pediatrics. At the end of the 50 hours, the students are assessed for clinical competency in pediatrics using a standardized instrument that yields a pass/fail result. Her research question is: Is there a difference in between the traditional clinical group and the simulation group on rates of passing the competency assessment? What is the appropriate statistic to address the research question? Answer: - 10: What statistic would be appropriate for an associational research question involving the extent to which a set of variables predict a continuous, normally distributed dependent variable? Answer: - Powered by TCPDF ( s_name: Prof. Dillard sclass: NUR 416 Case Study: Healing and Autonomy Mike and Joanne are the parents of James and Samuel, identical twins born 8 years ago. James is currently suffering from acute glomerulonephritis, kidney failure. James was originally brought into the hospital for complications associated with a strep throat infection. The spread of the A streptococcus infection led to the subsequent kidney failure. James’s condition was acute enough to warrant immediate treatment. Usually cases of acute glomerulonephritis caused by strep infection tend to improve on their own or with an antibiotic. However, James also had elevated blood pressure and enough fluid buildup that required temporary dialysis to relieve. The attending physician suggested immediate dialysis. After some time of discussion with Joanne, Mike informs the physician that they are going to forego the dialysis and place their faith in God. Mike and Joanne had been moved by a sermon their pastor had given a week ago, and also had witnessed a close friend regain mobility when she was prayed over at a healing service after a serious stroke. They thought it more prudent to take James immediately to a faith healing service instead of putting James through multiple rounds of dialysis. Yet, Mike and Joanne agreed to return to the hospital after the faith healing services later in the week, and in hopes that James would be healed by then. Two days later the family returned and was forced to place James on dialysis, as his condition had deteriorated. Mike felt perplexed and tormented by his decision to not treat James earlier. Had he not enough faith? Was God punishing him or James? To make matters worse, James's kidneys had deteriorated such that his dialysis was now not a temporary matter and was in need of a kidney transplant. Crushed and desperate, Mike and Joanne immediately offered to donate one of their own kidneys to James, but they were not compatible donors. Over the next few weeks, amidst daily rounds of dialysis, some of their close friends and church members also offered to donate a kidney to James. However, none of them were tissue matches. James’s nephrologist called to schedule a private appointment with Mike and Joanne. James was stable, given the regular dialysis, but would require a kidney transplant within the year. Given the desperate situation, the nephrologist informed Mike and Joanne of a donor that was an ideal tissue match, but as of yet had not been considered—James’s brother Samuel. Mike vacillates and struggles to decide whether he should have his other son Samuel lose a kidney or perhaps wait for God to do a miracle this time around. Perhaps this is where the real testing of his faith will come in? Mike reasons, “This time around it is a matter of life and death. What could require greater faith than that?” © 2020. Grand Canyon University. All Rights Reserved. 4 ASSIGNMENT TITLE HERE Typing Template for APA Papers: A Sample of Proper Formatting for the APA 6th Edition Student A. Sample Grand Canyon University:
Paper For Above instruction
The selection of appropriate analysis techniques is crucial in nursing research as it determines the validity, reliability, and overall credibility of the study findings. Choosing the correct statistical methods depends on the nature of the research question, type of data collected, and the distribution of variables involved. This paper explores various statistical techniques suitable for different research designs and data types commonly encountered in nursing research, with an emphasis on comparing and selecting the most appropriate methods for specific scenarios.
In the first scenario, a researcher aims to determine whether there is a difference between nurse practitioners (NPs) and physicians regarding their support for expanding prescribing privileges. The data collected are categorical, with responses of "yes" or "no" from two independent groups. The appropriate statistical test here is the Chi-square test of independence because it assesses whether there is a significant association between two categorical variables. This test compares the observed frequencies of support versus non-support in each group to the expected frequencies if there were no association, thus addressing the research question effectively (Polit & Beck, 2017).
For the second scenario involving the correlation between two continuous variables, the selection of the correlation coefficient depends on the distribution of data. When both variables are non-normally distributed and skewed, the Spearman rank-order correlation coefficient is appropriate. Unlike Pearson’s correlation, Spearman’s does not assume normality and is less affected by outliers or skewed data (Funder & Ozer, 2019). It assesses the monotonic relationship—whether one variable tends to increase or decrease as the other does—without requiring linearity or normal distribution assumptions.
The third scenario involves examining whetherYears of practice among NPs predict their level of support for expanded prescription privileges, measured on a Likert scale. Despite the Likert scale data, the researcher finds that both variables are normally distributed, justifying the use of Pearson’s correlation coefficient to measure the strength and direction of the linear relationship between the two continuous variables (Field, 2018). This approach helps clarify whether more experienced NPs tend to be more supportive of expanding prescribing rights.
When comparing two independent groups on a normally distributed continuous dependent variable, the independent samples t-test is the appropriate choice. In this context, the researcher compares the clinical competency scores of students receiving traditional clinical instruction versus simulated instruction. The t-test evaluates whether there is a statistically significant difference in mean scores between the two groups (Levine et al., 2019). It presumes normally distributed data and homogeneity of variances, which should be tested prior to analysis.
If the scores are not normally distributed in this scenario, the Mann-Whitney U test offers a non-parametric alternative. This test compares the median ranks of the two groups without assuming normality, making it suitable when data are skewed or ordinal (Gibbons & Chakraborti, 2011). It addresses the same research question—whether the two instructional methods differ significantly in terms of passing rates—without the constraints of parametric assumptions.
In the case of assessing the association between two dichotomous variables, the odds ratio derived from a 2x2 contingency table is the measure of interest when interested in the odds of an outcome. Logistic regression further allows modeling the probability of an event based on predictor variables, providing insight into how the set of variables influences the continuous dependent variable. It’s especially useful when the outcome of interest is binary, such as pass/fail in competency assessment (Hosmer et al., 2013).
When the dependent variable is skewed, the choice of analysis depends on whether the data transformation or specific non-parametric methods are suitable. For example, if analyzing a skewed continuous dependent variable, transformations like log or square root may normalize data, which then permits parametric tests. Alternatively, non-parametric regression techniques such as Spearman’s rank correlation or quantile regression can be employed to analyze relationships or differences