y(A,B) = b0 + b1*A + b2*B + b12*A*B + error.
This equation has 4 unknowns, b1, b1, b2 and b12. If you have all 4 cells in the 2x2 table, then you can estimate all 4 unknowns. If you have data for only 3 cells, the standard analysis pretends that b12 = 0 and estimates the other three. If you have only 2 cells, say (both absent) and (both present), the standard analysis can estimate b0 plus either of b1 or b2. However, in fact, these really estimate (b0+b12) and (b1+b2). To understand this, consult any good book that discusses confounding with 2-level fractional factorial designs.
To do this in R, use "lm", as
fit <- lm(y~A+B, data.frame(y=..., A=..., B=..,)
hope this helps. spencer graves
[EMAIL PROTECTED] wrote:
Hello,
I am planning a study with the main point to evaluate the interaction of two treatments, but for ethical reasons one cell is empty, that with patients receaving no treatment at all
Treatment B
+
-
Treatment A + a b
-
c
-------
I am looking for functions in R to estimate the sample size and/or to conduct the analysis. I have just found an article from Byar in Statistics in Medicine for a 2^3 incomplete factorial design, but I would like not to discover again the wheel..
TIA
dr. Giovanni Parrinello
Section of Medical Statistics
Department of Biosciences
University of Brescia
25127 Viale Europa, 11
Brescia Italy
Tel: +390303717528
Fax: +390303701157
[[alternative HTML version deleted]]
______________________________________________
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
