search for: darteta001

Dear list, first accept my apologies for asking a non-R question. Can anyone point me to a good reference on logistic regression? web or book references would be great. I am interested in the use and interpretation of dummy variables and prediction models. I checked the contributed section in the CRAN homepage but could not find anything (Julian Faraway?s "practical Regression and ANOVA

Dear list, this must be an easy one: I have a data.frame of two columns, "ID" with four different levels (A to D) and numerical "size", and each of the 4 different IDs is repeated a different number of times. I would like to get the mean size for each ID as another data.frame. I have tried the following: >ID= as.character(unique(data[,1])) # I use unique() because

Dear list, first apologies for this is not strictly an R question but a theoretical one. I have read that use of k-means clustering assumes sphericity of data distribution. Can anyone explain me what this means? My statistical background is too poor. Is it another kind of distribution, like gaussian or binomial? What does it happen if the distribution is not spherical? Could you give me an

Dear list Is there anywhere I could find further information on how to interpret the output for a logistic regression for validate() from Design package?. I tried ?validate and google but I cannot find information on what the rows and the columns represent. Thanks David

Dear list I would like to compare two measurements of disease severity (M1 and M2), one of the is continuous (M1 ranging from 1 to 10) and the other is ordinal (M2 takes Low, Medium, high and very high). Do you think is ok to use cor() function to test whether the two agree, i.e correlate? I am afraid that if I set M2 to 1,2,3 and 4, the function cor() will take them as continuous and

Dear list, I have a data.frame with nine categorical variables (0,1,2 and NAs) that I would like to get the number of events for each of them. I can extract this using summary() for each variable at a time with the as.factor()argument (otherwise it will get me the mean value): >summary(as.factor(mydf[,3])) 0 1 2 NA's 194 67 4 2 Trying to use apply() to get this for

Dear list, I have a categorical variable in a data.frame that I would like to plot using a histogram to show number of events. Values are 0, 1 and some NAs. I can?t make the hist() function to 1) include a column with the number of NAs 2) have the x axis to be categorical, I always get 0, 0.2, 0.4,... 1 divisions Can anyone help me? This is my code. "database" is my data.frame and

Dear list, I have a text file from a scanner that includes 20 lines of text (scanner settings) before it actually starts showing the readings in a tabular format (headings are ID, intensity, background and few others). I am a biologist with some experience using R and my question is if it is possible to read this file into an R workspace and store the actual readings in a dataframe,

I want to take the first row of each unique ID value from a data frame. For instance > ddTable <- data.frame(Id=c(1,1,2,2),name=c("Paul","Joe","Bob","Larry")) I want a dataset that is Id Name 1 Paul 2 Bob > unique(ddTable) Will give me all 4 rows, and > unique(ddTable$Id) Will give me c(1,2), but not accompanied by the name column.

Dear list, I have performed several tests for the hypergeometric distribution using phyper() for some gene annotation categories as follows >phyper(26,830,31042,337, lower.tail=F) >phyper(16,387,31042,337, lower.tail=F) . . . I am only running some selected categories but I would like to correct this value for multiple testing since I have 3121 possible tests according to 3121

Dear list, after fitting an lrm with the Design package (stored as "mymodel") I try running a summary, but I get the following error: dim(mydata) [1] 235 9 names(mydata) [1] "id" "VAR1" "VAR2" "VAR3" "VAR4" "VAR5" "VAR6" "VAR7" "VAR8" summary(mymodel) Error in `contrasts<-`(`*tmp*`,