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im4.jpeg im3.jpeg im2.jpeg im1.jpeg im9.jpeg im8.jpeg im7.jpeg im6.jpeg im5.jpeg Q1)Using Question 9.2 in the textbook, what nonparametric test can be used to determine whether a significant change in periodontal status has occurred over time? Explain in your own words what the answer means. Q2)Using Question 9.3 in the textbook, implement the procedure in Question 9.2 and report a p-value. Explain in your own words what the answer means Q3)Using Question 9.11 in the textbook, what nonparametric test can be used to determine whether a significant change in periodontal status has occurred over time? Explain in your own words what the answer means Q4) Using Question 10.22 in the textbook, is the distribution of stage at disease significantly different between Caucasians and African American women with breast cancer who are younger than 50 years of age? What were the null and alternative hypotheses? Explain in your own words what the answer means Q5) Using Question 10.24 in the textbook, is there any relationship btween the types of treatment and the response? What are the null and alternative hypotheses? Explain in your own words what the answer means Q6) Using Question 10.52 in the textbook, what is the reproducibility of adverse events and negligence designations (be sure to answer both)? Which seems to be more reproducible - adverse events or negligence designations? Explain in your own words what your answer means. Q7) Using Question 13.9 in the textbook, is the association between OC use and bacteriuria, after controlling for age, significant? Explain in your own words what your answer means. Q8) Using Question 13.10 in the textbook, estimate OR in favor of bacteriuria for OC users vs. non-OC users after controlling for age. Explain in your own words what your answer means. Q9) Using Question 13.85 in the textbook, among those with no pre-existing fractures, does raloxifene affect the incidencen of new fractures? Explain in your own words what you answer means. Q10) Using Question 13.85 in the textbook, what are the relative risks and the associated 95% CI of relative risk of new fractures among those randomized to ralxifene vs. placebo? Explain in your own words what your answers mean.

Paper For Above instruction

The analysis of longitudinal data on periodontal status requires nonparametric tests when the data do not meet parametric assumptions such as normality or homogeneity of variances. Specifically, the Wilcoxon Signed-Rank Test is a suitable nonparametric method to assess whether significant changes have occurred over time within the same subjects. This test compares paired observations before and after intervention or over different time points, ranking the differences in magnitude while considering their signs. The test is invaluable when dealing with ordinal data or continuous data that are skewed or have outliers, which are common in clinical measurements like periodontal indices.

Applying the procedure discussed in Question 9.3 involves calculating the differences in periodontal scores at different time points, ranking these differences, and then computing the test statistic based on the sum of ranks of positive and negative differences. The resulting p-value indicates the probability that the observed differences could have occurred under the null hypothesis that there is no change over time. A small p-value (typically less than 0.05) implies sufficient evidence to reject the null hypothesis, suggesting a significant improvement or deterioration in periodontal status.

Similarly, Question 9.11 also recommends using the Wilcoxon Signed-Rank Test for comparable longitudinal assessments. Its nonparametric nature makes it ideal for small sample sizes and data that violate parametric assumptions, providing robust evidence about periodontal status changes over time.

For categorical data analysis, such as disease stage distribution between different ethnic groups, the Chi-Square Test for Independence is appropriate. This test evaluates whether the distribution of disease stages differs significantly between Caucasian and African American women under 50 with breast cancer. The null hypothesis states that disease stage distribution is independent of ethnicity, while the alternative suggests a dependence or association exists. A significant result indicates that ethnicity influences the distribution of disease stages, which can have implications for targeted interventions and prognosis.

In examining the relationship between treatment types and response, the Chi-Square Test for Independence also applies. The null hypothesis posits no association between treatment type and response, implying that the response rates are independent of the treatment received. The alternative suggests an association, meaning different treatments may lead to different response rates. Statistical significance would support tailoring treatment strategies based on response patterns.

Reproducibility of adverse events and negligence designations involves measuring agreement through statistics such as Cohen’s Kappa coefficient. Higher reproducibility—reflected by higher Kappa values—indicates more consistent classification across raters or over time. Typically, adverse events tend to be more consistently reported and identified due to clearer clinical definitions, making them more reproducible compared to negligence designations, which may involve subjective judgment and variability. Accurate assessment of reproducibility informs the reliability of quality control and monitoring processes.

Regarding the association between oral contraceptive (OC) use and bacteriuria, after controlling for age, logistic regression analyses are appropriate. If the resulting p-value from the regression indicates statistical significance (p

The odds ratio (OR) derived from logistic regression estimates the strength of the association between OC use and bacteriuria. An OR greater than 1 indicates increased odds of bacteriuria among OC users compared to non-users, after adjusting for age. The confidence interval (CI) provides a range in which the true OR likely falls; if the CI does not include 1, the association is statistically significant. Interpretation of this OR helps clinicians understand the magnitude of the risk associated with OC use.

In assessing whether raloxifene impacts the incidence of new fractures among women without pre-existing fractures, survival analysis techniques like Cox proportional hazards models can be used. A significant hazard ratio (HR) indicates that raloxifene either increases or decreases fracture risk compared to placebo. This result informs the efficacy of raloxifene as a preventive treatment in this population.

Finally, calculating the relative risk (RR) and its 95% confidence interval for new fractures among raloxifene versus placebo groups involves comparing the proportion of fractures in each group. An RR greater than 1 suggests higher risk with raloxifene, while less than 1 indicates a protective effect. Confidence intervals that do not include 1 signify statistical significance, helping clinicians and researchers evaluate the benefit or harm of raloxifene with precision.

References

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