similar to: extract a value from vector

The expected number of bladder cancer over next 20 years a tire industry is 1.8. Poission distribution is assumed to hold and 6 reported deaths are caused by bladder cancer among the employees. Trying to find how unusual this event is. > ppois(q=6, lambda=1.8, lower.tail = TRUE, log.p = FALSE) [1] 0.9974306 not sure if ppois is the right one to use and the parameters... thx much

R-experts: A quick question, please. >From a lab exp, I got 12 positives out of 50. To get 90% CI for this , I think binom.test might be the one to be used. Is there a better way or function to calculate this? > binom.test(x=12, n=50, p=12/50, conf.level = 0.90) Exact binomial test data: 12 and 50 number of successes = 12, number of trials = 50, p-value = 1 alternative

What would be the R formulae for a two-sided test? I have a formula for a one-sided test: powertest <- function(a,m0,m1,n,s){ t1 = -qnorm(1-a) num = abs(m0-m1) * sqrt(n) t2 = num/s pow = pnorm(t1 + t2) } Would you pls let me know if you know of? Thank you, ej

I have the clinical study data. Year 0 Year 3 Retinol (nmol/L) N Mean +-sd Mean +-sd Vitamin A group 73 1.89+-0.36 2.06+-0.53 Trace group 57 1.83+-0.31 1.78+-0.30 where N is the number of male for the clinical study. I want to test if the mean serum retinol has increased over 3 years among subjects in the vitamin A group. > 1.89+0.36

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# R 2.3.1 I read the data set into R, but the data set have two rows per record. i.e. ......... 105 1 1 1103 1 5 4 8 5 22 105 2 2 2 2 1 2 17 16 26 106 1 2 606 1 5 12 11 9 37 106 2 2 2 2 2 2 16 14 29

A quick question please! How do you rename column names? i.e. V1 --> Apple; V2 --> Orange, etc. thx much ej [[alternative HTML version deleted]]

I have a quick question, please. Does R have function to compute i.e. a 90% confidence interval for the mean for these numbers? > mean (6,11,5,14,30,11,17,3,9,3,8,8) [1] 6 I thought pt or qt would give me the interval, but it seems not. thx much. ej

// R 2.3.1 Can someone please explain why this error returns? > y=numeric(100) > x=matrix(runif(16),4,4) > for(i in 2:100) + { + y[i]=which(rmultinom(1, size = 1, prob = x[y[i-1], ])==1) + } Error in rmultinom(n, size, prob) : too few positive probabilities thx much ej

>x=c(3.05176E-05,0.000457764,0.003204346,0.0138855,0.04165649,0.09164429,0.1527405,0.1963806,0.1963806,0.1527405,0.09164429,0.04165649,0.0138855,0.003204346,0.000457764,3.05176E-05) >y=c(0.0000306,0.0004566,0.0031985,0.0139083,0.0415539,0.0917678,0.1528134,0.1962831,0.1962994,0.1527996,0.0917336,0.0415497,0.0139308,0.0031917,0.0004529,0.0000301) I tried chisq.test, t-test, prop.test, etc,

An apparatus exists whereby a collection of balls is displaced to the top of a stack by suction. A top level (Level 1) each ball is shifted 1 unit to the left or 1 unit to the right at random with equal probability. The ball then drops down to level 2. At Level 2, each ball is again shifted 1 unit to the left or 1 unit to the right at random. The process continues for 15 levels and the balls are

Hi, 1. How do I construct 95% prediction interval for new x values, for example - x = 30000? 2. How do I construct 95% confidence interval? my dataframe is as follows : >dt structure(list(y = c(26100000, 60500000, 16200000, 30700000, 70100000, 57700000, 46700000, 8600000, 10000000, 61800000, 30200000, 52200000, 71900000, 55000000, 12700000 ), x = c(108000, 136000,

I am getting "Chi-squared approximation may be incorrect in: chisq.test(x)" with the data bleow. Frequency distribution of number of male offspring in families of size 5. Number of Male Offspring N 0 518 1 2245 2 4621 3 4753 4 2476 5

Hi I have used a polycor package for categorical correlation coefficients. I run the following script. But there were no results. Could you tell me how to correct the script? Thanks in advance, vars <- names(sdi) for (i in 1:length(vars)) { for (j in 1:length(vars)) { paste(vars[i]," and ", vars[j]) polychor(vars[i], vars[j]) # corr } } -- Kum-Hoe Hwang, Ph.D.Phone :

Dear list, I have a table where first 3 columns are identical if the name in the first column is the same, and the number in N4 is slightly different for all identical names, like this: ------------------------------------------------------------------- 29 Mm.1_at 3 + 93649936 30 Mm.1_at 3 + 93649990 31 Mm.1_at 3 + 93649993 32

Hi, I would like to know how to extract the arguments from a list : For example, I have a list of charchacter x x<- c("Bentazone","Atrazine","Epoxiconazol","Metolachlor","Epoxiconazol","Atrazine desethyl","Fenpropimorph","Epoxiconazol","Metolachlor","Simazine","Atrazine

Dear R-help list, I hope I did not miss something obvious, because my question seems very simple, but I couln't figure out how to do it. If I have the following data: Day<-c(1,2,3,4,5,6,7) V<-c(5,NA,10,30,45,NA,10) than the line in plot plot(V~Day, type="b") will start with the 3rd value and stop stop at the 5th value because all NA are omitted. Is there now a parameter

Hi, I would like to estimate something like y = a + b*d2*y + c*d3*y where the dummies are created from some vector d with three (actually many more) levels using factor(). But either there is included the variable y or d1*y. How could I get rid of these? Example: x = c(1,2,3,4,5,6,7,8) y = c(3,6,2,8,7,6,2,4) d = c(1,1,1,2,3,2,3,3) fd = factor(d) lm(x ~ fd*y) gives: Coefficients: (Intercept)

I am running a series of candidate mixed models using lmer (package lme4) and I'd like to be able to compile a list of the AIC scores for those models so that I can quickly summarize and rank the models by AIC. When I do logistic regression, I can easily generate this kind of list by creating the model objects using glm, and doing: > md <- c("md1.lr", "md2.lr",

Dear all, I am new to R. I wish to use R's multiple imputation to deal with missing data. I have a data set with the size around 300 observations and 150 variables. I checked the help function in R and could not locate how to write the codes for this. can anyone give a hand? Do appreciate your time and kindness! Q. [[alternative HTML version deleted]]