Add mmrm and wilcoxs

R/nonpara_wilcoxon_ranksum.qmd

@@ -0,0 +1,79 @@
+---
+title: "Wilcoxon Rank Sum (Mann Whitney-U) in R"
+---
+
+```{r}
+#| echo: FALSE
+#| include: FALSE
+ library(tidyverse)
+```
+
+# Overview
+
+ Wilcoxon rank sum test, or equivalently, Mann-Whitney U-test is a rank based non-paramatric method. The aim is to examine the differences between two groups. To be more specific, it tests whether the median difference between pairs is equal to zero. 
+
+ It is the non-parametric equivalent to two-sample t-test, where the two groups are not paired.
+
+## Available R package
+
+ The `stats` package implements various classic statistical tests, including wilcoxon rank sum test. 
+
+```{r}
+#| eval: false
+#| echo: true
+# x, y are two unpaired vectors. Do not necessary need to be of the same length.
+stats::wilcox.test(x, y, paired = F)
+```
+
+
+## Example: Birth Weight 
+
+*Data source: Table 30.4, Kirkwood BR. and Sterne JAC. Essentials of medical statistics. Second Edition. ISBN 978-0-86542-871-3*
+
+Comparison of birth weights (kg) of children born to 15 non-smokers with those of children born to 14 heavy smokers.
+
+```{r}
+#| eval: true
+#| echo: true
+# bw_ns: non smokers
+# bw_s: smokers
+bw_ns <- c(3.99, 3.89, 3.6, 3.73, 3.31, 
+            3.7, 4.08, 3.61, 3.83, 3.41, 
+            4.13, 3.36, 3.54, 3.51, 2.71)
+bw_s <- c(3.18, 2.74, 2.9, 3.27, 3.65, 
+           3.42, 3.23, 2.86, 3.6, 3.65, 
+           3.69, 3.53, 2.38, 2.34)
+```
+
+ Can visualize the data on two histograms. Red lines indicate the location of medians. 
+
+```{r}
+#| eval: true
+#| echo: true
+par(mfrow =c(1,2))
+hist(bw_ns, main = 'Birthweight: non-smokers')
+abline(v = median(bw_ns), col = 'red', lwd = 2)
+hist(bw_s, main = 'Birthweight: smokers')
+abline(v = median(bw_s), col = 'red', lwd = 2)
+```
+
+
+It is possible to see that for non-smokers, the median birthweight is higher than those of smokers. Now we can formally test it with wilcoxon rank sum test. 
+
+The default test is two-sided with confidence level of 0.95, and does continuity correction. 
+
+```{r}
+#| eval: true
+#| echo: true
+# default is two sided
+stats::wilcox.test(bw_ns, bw_s, paired = F)
+```
+ We can also carry out a one-sided test, by specifying `alternative = greater` (if the first item is greater than the second). 
+
+```{r}
+#| eval: true
+#| echo: true
+# default is two sided
+stats::wilcox.test(bw_ns, bw_s, paired = F, alternative = 'greater')
+```
+

data/stat_method_tbl.csv

@@ -11,15 +11,15 @@ Generalized Linear Models,Logistic Regression,[R](R/logistic_regr),,
 Generalized Linear Models,Poisson/Negative Binomial Regression,,,
 Generalized Linear Models,Categorical Repeated Measures,,,
 Generalized Linear Models,Categorical Multiple Imputation,,,
-Non-parametric Analysis,Wilcoxon signed rank,,,
+Non-parametric Analysis,Wilcoxon signed rank,[R](R/nonpara_wilcoxon_ranksum),,
 Non-parametric Analysis,Mann-Whitney U/Wilcoxon rank sum,,,
 Non-parametric Analysis,Kolmogorov-Smirnov test,,,
 Non-parametric Analysis,Kruskall-Wallis test,[R](R/kruskal_wallis),[SAS](SAS/kruskal_wallis),[R vs SAS](Comp/r-sas_kruskalwallis)
 Non-parametric Analysis,Friedman test,,,
 Non-parametric Analysis,Jonckheere test,,,
 Categorical Data Analysis,Binomial test,,,
 Categorical Data Analysis,McNemar's test,[R](R/mcnemar),[SAS](SAS/mcnemar),[R vs SAS](Comp/r-sas_mcnemar)
-Categorical Data Analysis,Chi-Square Association/Fishers exact,[R](R/association),,
+Categorical Data Analysis,Chi-Square Association/Fishers exact,[R](R/association),,[R vs SAS](Comp/r-sas_chi-sq)
 Categorical Data Analysis,Cochran Mantel Haenszel,[R](R/cmh),[SAS](SAS/cmh),[R vs SAS](Comp/r-sas_cmh)
 Categorical Data Analysis,Confidence Intervals for proportions,,,
 Linear Mixed Models,MMRM,[R](R/mmrm),[SAS](SAS/mmrm),[R vs SAS](Comp/r-sas_mmrm)
@@ -44,4 +44,4 @@ Multivariate methods,Canonical correlation,,,
 Multivariate methods,PLS,,,
 Other Methods,Nearest neighbour,,,
 Other Methods,Causal inference,,,
-Other Methods,Machine learning,,,
+Other Methods,Machine learning,,,

renv.lock

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