The data below are on the Hamilton depression scale factor measurements in 9 patients with mixed anxiety and depression, taken at the first (x) and second (y) visit after initiation of a therapy.x = c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 2.06, 1.30)y = c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)Perform a Wilcoxon signed-rank test to test if there has been a decrease in Hamilton depression scale measurements since the intervention. Report your p-value below to 4 decimal places.
Question
The data below are on the Hamilton depression scale factor measurements in 9 patients with mixed anxiety and depression, taken at the first (x) and second (y) visit after initiation of a therapy.x = c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 2.06, 1.30)y = c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)Perform a Wilcoxon signed-rank test to test if there has been a decrease in Hamilton depression scale measurements since the intervention. Report your p-value below to 4 decimal places.
Solution
To perform a Wilcoxon signed-rank test in R, you can use the wilcox.test() function. Here are the steps:
- First, you need to create two vectors x and y with the given data:
x = c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 2.06, 1.30)
y = c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)
- Then, you can perform the Wilcoxon signed-rank test with the wilcox.test() function. The paired = TRUE argument indicates that you are performing a paired test:
test_result = wilcox.test(x, y, paired = TRUE, alternative = "greater")
The "greater" argument is used because we are testing if there has been a decrease in Hamilton depression scale measurements since the intervention.
- Finally, you can get the p-value from the test result:
p_value = test_result$p.value
- To report the p-value to 4 decimal places, you can use the round() function:
p_value = round(p_value, 4)
Please note that you need to run these commands in an R environment to get the actual p-value.
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