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Zorluk: OrtaInferential Statistical Tests

A team of hepatologists is evaluating the impact of three distinct dietary regimens—Mediterranean, low-fat, and ketogenic—on liver fibrosis progression in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). A total of 150 patients are randomly assigned in equal proportions to one of the three diets for a period of 6 months. The primary outcome is the change in liver stiffness, measured continuously in kilopascals (kPa) using transient elastography, from baseline to the end of the study period. A preliminary analysis of the data reveals that the changes in liver stiffness measurements across all three groups are highly right-skewed and do not follow a normal distribution. Which of the following statistical tests is most appropriate to determine if there is a significant difference in the change in liver stiffness among the three dietary groups?

  1. A
    Analysis of variance
  2. B
    Chi-square test
  3. Kruskal-Wallis testCevap
  4. D
    Mann-Whitney U test
  5. E
    Spearman rank correlation

Cevap

The Kruskal-Wallis test is the correct choice.
The correct statistical test is the Kruskal-Wallis test. In this clinical scenario, the researchers are comparing an outcome across three independent groups (the three different diets). The dependent variable (change in liver stiffness in kPa) is continuous. However, because the data is highly skewed and does not follow a normal distribution, parametric tests (like ANOVA) cannot be used. The Kruskal-Wallis test is the non-parametric equivalent of the one-way ANOVA and is the most appropriate method to analyze continuous, non-normally distributed data across three or more independent groups.

Adım Adım Çözüm

1
Identify the independent variable.
The independent variable is the dietary regimen, which is categorical and consists of three independent groups (Mediterranean, low-fat, ketogenic).
Determining the number of groups dictates whether a two-sample test (e.g., t-test) or a multi-sample test (e.g., ANOVA) is required.
2
Identify the dependent variable and its scale of measurement.
The dependent variable is the change in liver stiffness, which is measured continuously in kilopascals (kPa).
The nature of the outcome variable (categorical vs. continuous) narrows down the family of applicable statistical tests.
3
Assess the distribution of the data.
The data is explicitly described as highly right-skewed and non-normally distributed.
Non-normal distribution of a continuous variable requires the use of non-parametric testing rather than parametric testing.
4
Select the test that fits continuous, non-normal data across three independent groups.
The Kruskal-Wallis test.
The Kruskal-Wallis test is the non-parametric equivalent of one-way ANOVA, specifically designed for three or more independent groups with non-normal continuous or ordinal data.

Anahtar Kavram

Selecting the appropriate statistical test based on variable type, number of groups, and data distribution.
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Inferential Statistical Tests

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