Statistics for nursing research

Exercise 14

1. According to the study narrative and Figure 1 in the Flannigan et al. (2014) study, does the APLS UK formula under- or overestimate the weight of children younger than 1 year of age? Provide a rationale for your answer.

2. Using the values a = 3.161 and b = 0.502 with the novel formula in Figure 1, what is the predicted weight in kilograms (kg) for a child at 7 months of age? Show your calculations.

3. Using the values a = 3.161 and b = 0.502 with the novel formula in Figure 1, what is the predicted weight in kilograms for a child at 10 months of age? Show your calculations.

4. In Figure 2, the formula for calculating y (weight in kg) is Weight in kg = (0.176 × Age in months) + 7.241. Identify the y intercept and the slope in this formula.

5. Using the values a = 7.241 and b = 0.176 with the novel formula in Figure 2, what is the predicted weight in kilograms for a child 3 years of age? Show your calculations.

6. Using the values a = 7.241 and b = 0.176 with the novel formula in Figure 2, what is the predicted weight in kilograms for a child 5 years of age? Show your calculations. 

7. In Figure 3, some of the actual mean weights represented by the colored line with squares are above the dotted straight line for the novel formula, but others are below the straight line. Is this an expected finding? Provide a rationale for your answer.

8. In Figure 3, the novel formula is ‘Weight in kilograms = (0.331 × Age in months) − 6.868’. What is the predicted weight in kilograms for a child 11 years old? Show your calculations. 

9. Was the sample size of this study adequate for conducting simple linear regression? Provide a rationale for your answer. 

10. Describe one potential clinical advantage and one potential clinical problem with using the three novel formulas presented in Figures 1, 2, and 3 in a PICU setting.

Exercise 15

1. What are the assumptions for multiple linear regression?

2. Was multiple regression analysis the appropriate analysis technique to conduct in the Franck et al. (2014) study? Provide a rationale for your answer.

3. Was the independent variable length of hospital stay significantly correlated with the dependent variable parental PTSS? Provide a rationale for your answer. 

4. Was the independent variable depression significantly correlated with parental PTSS in this study? Provide a rationale for your answer. 

5. What is multicollinearity? Why is it important to test for multicollinearity? Is there a potential for multicollinearity in this study? 

6. According to the study narrative and Table 4, “5 out of 8 predictors were uniquely and significantly associated with PTSS” (Franck et al., 2014, p. 6). Which five variables were significant predictors of PTSS in the regression model, before moderating effects and interaction terms were tested? Provide a rationale for your answer. 

7. What was the percentage of variance of parental PTSS explained by the regression analysis of the independent variables parent coping strategies (negative coping and optimism) entered in step 2 of the regression analysis? Provide your calculations. 

8. What was the percentage of variance for parental PTSS explained by the regression analysis for parent distress during hospitalization (anxiety, depression, and uncertainty) entered in step 3 of the regression analysis? Provide your calculations. 

9. What was the percentage of variance for parental PTSS during hospitalization explained by the full regression model? Discuss the meaning of these results. 

10. What additional research is needed in this area of parental PTSS after their child’s hospitalization? Provide a rationale for your answer.

Exercise 17

1. What are the assumptions for conducting a paired or dependent samples t-test in a study? Which of these assumptions do you think were met by the Lindseth et al. (2014) study?

2. In the introduction, Lindseth et al. (2014, p. 187) described a “2-week washout between diets.” What does this mean? Why is this important?

3. What is the paired t-test value for mood (irritability) between the participants’ consumption of high- versus low-aspartame diets? Is this result statistically significant? Provide a rationale for your answer.

4. State the null hypothesis for mood (irritability) that was tested in this study. Was this hypothesis accepted or rejected? Provide a rationale for your answer.

5. Which t value in Table 2 represents the greatest relative or standardized difference between the high- and low-aspartame diets? Is this t value statistically significant? Provide a rationale for your answer.

6. Discuss why the larger t values are more likely to be statistically significant.

7. Discuss the meaning of the results regarding depression for this study. What is the clinical importance of this result?

8. What is the smallest, paired t-test value in Table 2? Why do you think the smaller t values are not statistically significant?

9. Discuss the clinical importance of these study results about the consumption of aspartame. Document your answer with a relevant source.

10. Are these study findings related to the consumption of high- and low-aspartame diets ready for implementation in practice? Provide a rationale for your answer.

Exercise 18

1. Mayland et al. (2014) do not provide the degrees of freedom (df) in their study. Use the degrees of freedom formulas provided at the beginning of this exercise to calculate the group df and the error df.

2. What is the F value and p value for spiritual need—patient? What do these results mean?

3. What is the post hoc result for facilities for the hospital with LCP vs. the hospital without LCP (see Table 2)? Is this result statistically significant? In your opinion, is this an expected finding?

4. What are the assumptions for use of ANOVA?

5. What variable on Table 3 has the result F = 10.6, p < 0.0001? What does the result mean?

6. ANOVA was used for analysis by Mayland et al. (2014). Would t-tests have also been appropriate? Provide a rationale for your answer. 

7. Which group had the largest mean for the care variable? Identify the mean, standard deviation, and range for this group and discuss what these results mean.

8. State the null hypothesis for care for the three study groups (see Table 2). Should the null hypothesis be accepted or rejected? Provide a rationale for your answer.

9. What are the post hoc results for care? Which results are statistically significant? What do the results mean? Document your answer.

10. In your opinion, do the study findings presented in Tables 2 and 3 have implications for end of life care in the United States? Provide a rationale for your answer. Document your answer.

Exercise 19

1. According to the relevant study results section of the Darling-Fisher et al. (2014) study, what variables are reported to be statistically significant?

2. What level of measurement is appropriate for calculating the χ2 statistic? Give two examples from Table 2 of demographic variables measured at the level appropriate for χ2.

3. What is the χ2 for U.S. practice region? Is the χ2 value statistically significant? Is the p value accurately expressed for this variable? Provide a rationale for your answer.

4. What is the df for provider type? Provide a rationale for why the df for provider type presented in Table 2 is correct.

5. Is there a statistically significant difference for practice setting between the Rapid Assessment for Adolescent Preventive Services (RAAPS) users and nonusers? Provide a rationale for your answer.

6. State the null hypothesis for provider age in years for RAAPS users and RAAPS nonusers.

7. Should the null hypothesis for provider age in years developed for Question 6 be accepted or rejected? Provide a rationale for your answer.

8. Describe at least one clinical advantage and one clinical challenge of using RAAPS as described by Darling-Fisher et al. (2014).

9. How many null hypotheses are rejected in the Darling-Fisher et al. (2014) study for the results presented in Table 2? How many null hypotheses were accepted? Provide rationales for your answers.

10. A statistically significant difference is present between RAAPS users and RAAPS nonusers for U.S. practice region, χ2 = 29.68. Does the χ2 result provide the location of the difference? Provide a rationale for your answer.

Exercise 24

1. When is the optimal time to perform a power analysis—before the beginning of the study or after the study ends? Provide a rationale for your answer.

2. Define effect size.

3. A researcher is planning to compute a Pearson r. What effect size measure should be used in the power analysis? Provide a rationale for your answer.

4. A researcher is planning to compute a one-way ANOVA. What effect size measure should be used in the power analysis? Provide a rationale for your answer.

5. A researcher is planning to compute an independent samples t-test. What effect size measure should be used in the power analysis?

6. A researcher is planning to perform paired samples t-test. What effect size measure should be used in the power analysis?

7. A study reported an OR of 1.70, which was not significant. The authors note that their power analysis was based on a large effect size. Can they accept the null hypothesis?

8. Before conducting a power analysis, you reviewed the literature and discovered that two similar studies reported Cohens d values of 0.50 and 0.75. Which effect will require more study participants? Provide a rationale for your answer.

9. Before conducting a power analysis, a researcher reviews the literature and discovered a similar study comparing differences between groups. The authors reported a d value of 27%. How would you characterize the magnitude of that effect?

10. A researcher plans a study whereby she will compute three statistical tests: a Pearson r, a paired samples t-test, and multiple regression. She performs a power analysis based on an anticipated R2 and enrolls the required number of participants based on the results of that power analysis, states that the study has adequate statistical power, and begins the study. Is the researcher correct? Provide a rationale for your answer.