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...enerating under H1 ##### ################################### ## Minor Allele Frequency ## p.control <- minor.allele.prop # p = P(a) # q.control <- 1-p.control # q = P(A) = 1-P(a) # ## Genotype by Mendelian rule: P(G) ## p.aa.control <- p.control^2 # P(G=aa) # p.Aa.control <- 2*p.control*q.control # P(G=Aa) # p.AA.control <- q.control^2 # P(G=AA) # ################################### ##### Generating Control Data ##### #############################...

Dear all, I am using the Instrumental Variable approach to estimate the causal effects of TWO endogenous variables in a Mendelian Randomization study. As long as point estimation is concerned, I have no problem: both "ivreg" in library "AER" and "tsls" in library "sem" do the job perfectly. The problems begin when I try to obtain confidence intervals for these two causal effects. Of...

No, since I'd like to test null: p <= p0 alternative: p > p0. and my understanding is that binom.test tests null: p = p0 (can only be a "simple" null hypothesis according to help(binom.test)) alternative: p > p0 (or p < p0 or p != p0). Thanks, Mirko. > -----Urspr?ngliche Nachricht----- > Von: Douglas Bates [mailto:bates at stat.wisc.edu] >

Hi, I have a genotype data for both case and controls and would like to calculate the HW p-value. However, since the number of one genotype is 0, I got wired result. Would someone help me to figure it out? Or confirm it's right? Thanks a lot. ============ > library( "genetics" ) NOTE: THIS PACKAGE IS NOW OBSOLETE. The R-Genetics project has developed an set of enhanced