search for: popb

...bootstrapping algorithm than handles populations as the sample unit instead of individual data points? I bet mixed models could handle this problem somehow, but I'd like to stick to the theme of a mantel test. The data look like this pop1 pop2 genetic_distance(dependent) (independent1) popa popb data data popb popd data data popc pope data data popf popg data data popg poph data data So for example, popb appears twice, as does popg. Clearly each row is not independent. Thanks for any insight Rob. -- View this message in context: http://r.789695.n4.nabble.co...

...ignment which is already known ("populations" in the dummy data). I want to know how such work can be implemented, maybe by using R. #dummy data, clus.data <- data.frame(individual = paste("ind", 1:12, sep = ""), populations = c(rep("popA", 5), rep("popB", 7)), cluster.1 = c(rep(1, 5), rep(2, 7)), cluster.2 = c(rep(2, 4), rep(1, 8)), cluster.3 = c(rep(4, 7), rep(5, 5))) clus.data Thanks. -- Jian-Feng, Mao the Institute of Botany, Chinese Academy of Botany,

I'm not certain I am using the lattice plot correctly here. Below is reproducible code. Suppose I have two data frames, such as: set.seed(1234) datA <- data.frame(condition = gl(3, 100), scores = c(rnorm(100), rnorm(100, 1,1), rnorm(100, 2,1))) datB <- data.frame(condition = gl(3, 1000), scores = c(rnorm(1000, 3,1), rnorm(1000, 4,1), rnorm(1000, 5,1))) I would like to plot the