Josh B
2011-Sep-30 22:10 UTC
[R] Data simulation for ANOVA decomposition into sums of squares
Dear listserv, Please consider the following dataset: x <- matrix(nrow = 8, ncol = 2) colnames(matrix) <- c("classification", "soluble_fiber") x[1:4,1] <- "bagel" x[5:8,1] <- "donut" How would I simulate a dataset for a one-way fixed-effect ANOVA (where "classification" is the treatment variable and "soluble_fiber" is the response variable) such that the total sums of squares are equal to 1, and the treatment sums of squares are equal to 0.1? In other words, I simply want to make up "soluble_fiber" values for each observation (rows) such that an ANOVA of "soluable_fiber" ~ "classification" yields total sums of squares = 1 and treatment sums of squares = 0.1. More generally, I'd like to develop some code that will let me simulate datasets with different treatment sums of squares (ranging from 0.1 - 0.9) while holding the total sums of squares constant (equal to 1). Many thanks in advance for your suggestions. I recognize that this is as much a statistical/mathematical question as an R programing question. Sincerely, ----------------------------------- Josh Banta, Ph.D Assistant Professor Department of Biology The University of Texas at Tyler Tyler, TX 75799 Tel: (903) 565-5655 http://plantevolutionaryecology.org [[alternative HTML version deleted]]
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