Health Research Methodologies

Health Research Methodologies

Question 1

Compare and contrast four nonparametric tests performed in biostatical studies. Include an example of how public health researchers can use each test. How do they compare with parametric test? Your response must be at least 500 words in length with in-text citations and references

Question 2

Discuss the role of Biostatistical analysis in public health research. Your response must be at least 150 words in length.

Question 3

Explain how to formulate scientific question into statistical hypothesis. Your response must be at least 150 words in length.

Question 4

The Kruskal-Wallis test is used in place of the one-way analysis of variance (ANOVA). What are the four assumptions required for the application of the Kruskal-Wallis test?

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Answer

Question 1: Comparison of Nonparametric Tests in Biostatistical Studies

Nonparametric tests are essential tools in biostatistics, especially when the data does not meet the assumptions necessary for parametric tests, such as normality or homogeneity of variances. Below, I discuss four widely used nonparametric tests: the Wilcoxon signed-rank test, the Mann-Whitney U test, the Kruskal-Wallis test, and the Friedman test, along with examples of their application in public health research. Health Research Methodologies

1. Wilcoxon Signed-Rank Test: This test is used to compare two related samples to assess whether their population mean ranks differ. It is particularly useful when the data are paired or matched. For instance, public health researchers might use this test to compare the blood pressure measurements of patients before and after a treatment intervention. If the data are not normally distributed, the Wilcoxon signed-rank test provides a robust alternative to the paired t-test.
2. Mann-Whitney U Test: This test compares two independent samples to determine whether they come from the same distribution. Public health researchers might utilize the Mann-Whitney U test to compare the effectiveness of two different health promotion interventions, such as smoking cessation programs, by assessing the quit rates in two independent groups. This test serves as an alternative to the independent samples t-test when the assumption of normality is violated.
3. Kruskal-Wallis Test: As an extension of the Mann-Whitney U test, the Kruskal-Wallis test is used when comparing three or more independent groups. It assesses whether the samples originate from the same distribution. Public health researchers may apply this test to evaluate the impact of different lifestyle modifications (such as diet, exercise, and medication) on cholesterol levels across multiple groups. If the data do not meet the assumptions for one-way ANOVA, the Kruskal-Wallis test offers a valid nonparametric alternative.
4. Friedman Test: The Friedman test is a nonparametric alternative to the repeated measures ANOVA and is used for comparing three or more related groups. For example, public health researchers could use the Friedman test to evaluate the effectiveness of different interventions on the same group of patients over time, such as assessing weight loss in patients undergoing three different dietary programs at different intervals. This test allows researchers to analyze the data without assuming normality or equal variances.

Comparison with Parametric Tests: Nonparametric tests have several advantages over parametric tests. They do not require the assumption of normality, making them suitable for ordinal data or data with outliers. Health Research Methodologies. Additionally…