2k-factorial design with 10 parameters
Hi Sven, just use: lm(y~(x1+x2+x3+...+x10)^10) e.g., y <- rnorm(5000) x1 <- factor(sample(0:1, 5000, TRUE)) x2 <- factor(sample(0:1, 5000, TRUE)) x3 <- factor(sample(0:1, 5000, TRUE)) x4 <- factor(sample(0:1, 5000, TRUE)) lm1 <- lm(y~(x1+x2+x3+x4)^4) summary(lm1) I hope it helps. Best, Dimitris ---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/16/336899 Fax: +32/16/337015 Web: http://www.med.kuleuven.ac.be/biostat http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm ----- Original Message ----- From: "Sven" <svuwie at gmx.de> To: <r-help at stat.math.ethz.ch> Sent: Tuesday, November 30, 2004 12:59 PM Subject: [R] 2k-factorial design with 10 parameters
Hi, I'd like to apply a 2^k factorial design with k=10 parameters. Obviously this results in a quite long term for the model equation due to the high number of combinations of parameters. How can I specify the equation for the linear model (lm) without writing all combinations explicitly down by hand? Does a R command exist for this problematic? Thanks for your help in advance, Sven
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