similar to: recode problem - unexplained values

I am hoping for some advice regarding limiting decimal points to 3. 'Round' produces the desired results except for the 97.5% confidence interval. Any advice as to how I modify the code to obtain output to 3 decimal points for all ouput is appreciated, regards Bob Green mod.multgran <-multinom(offence ~ grandiose * violent.convictions, data = kc, na.action = na.omit)

A bit of a perennial I'm afraid. My wife has filled up her iPhone 6 with photos, and wants them moved onto my computer. I'm running CentOS 7 patched about 30 minutes ago. Needless to say the computer can't see the data on the iPhone, though it does recognise the phone as an iPhone. Any suggestions (well any that don't involve a steam roller, sledge hammer or GBH to the whole of

A basic question, but one that eludes me. I have created a new variable $numurder, which I have rounded off. I want to save the rounded off version of this variable to an existing datafile called 'ngri.csv' . numurder <-c((murder*no.of.cases)/100) [[1]] [1] 48.952 112.073 182.160 974.610 122.140 663.432 150.856 18.988 137.925 198.045 68.930 203.148 30.056 100.955

Hello, Below is the code for a basic bar graph. I was seeking advice regarding the following: (a) For each time period there are values from 16 people. How I can change the colour value so that each person has a different colour, which recurs across each of the three graphs/tie epriods? (b) I have seen much more sophisticated examples using lattice (e.g each person has a separate

Hi, I have numerical variable that I want to recode into categories '0' and '1 and more' and do analysis with that data. I have tried various of possibilities to do so, but I am sucked and nothing is working. recode(Q12, "0='A';1:30='B'") cut(Q12, breaks=c(0,1,30), lables=c('0', '1 and more')) cat(Q12, "0=0;1-33=1") What should

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I know this comes up, but I didn't see my exact issue in the archives. I have variables in a dataframe that need to be recoded. Here is what I'm dealing with I have a factor called aa > class(aa) [1] "factor" > table(aa) aa * 0 1 2 3 A B C D L N T 0 0 1908 725 2089 0 0 67 0 0 2 1 6 I need to recode

Dear Rusers, My question is about "recode variables". First, i'd like to say something about the idea of recoding: My dataset have three variables:type,soiltem and airtem,which means grass type, soil temperature and air temperature. As we all known, the change of air temperature is greater than soil temperature,so the values in those two different temperaturemay represent different

Hi, Is there an efficient way recoding variables in a data.frame using base R? My purpose is to create new variables and attach them into old data.frame. The basic idea is shown below, but how to create recoding for A, B and C and assing them into new variables? df <- data.frame(A = c(1:5), B = c(3,6,2,8,10), C = c(0,15,5,9,12)) df$A[df$A <= 3] <- "x" df$A[df$A > 3 &

Greetings, I'm in the painful process of migrating from SAS to R. In the process I've discovered that there are some basic things that I am getting hung up on. The most basic is the simple recoding of variables. Suppose I create a vector x <- rnorm(10000) and I want to recode all values of x > 1.5 to NA. How would I do that in R? TIA Cheers, Patrick

I am just beginning to use Sweave with Lyx on a Mac (R2.8.1). I have 12 chunks of Sweave code that work fine, but this piece: <<>>= library(car)

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

?s 23:06 de 25/07/2023, Bob Green escreveu: > Hello, > > I am seeking advice as to how I can download the 833 files from this > site:"http://home.brisnet.org.au/~bgreen/Data/" > > I want to be able to download them to perform a textual analysis. > > If the 833 files, which are in a Directory with two subfolders were on > my computer I could read them

Hi, as an R-beginner, I have a recoding problem and hope you can help me: I am working on a SPSS dataset, which I loaded into R (load("C:/...) I have 2 existing Variables: "ID" and "X" , and one variable to be computed: meanX.dependID (=mean of X for all rows in which ID has the same value) ID = subject ID. Since it is a longitudinal dataset, there are repeated

Hi all I am trying to do a simple recode which I am stumbling on. I figure there must be any easy way but haven't come across it. Given data of A","B","C","D","E","A" it would be nice to recode this into say three categories ie A and B becomes "Treat1", C becomes "Treat 2" and E becomes "Treat 3". I tried

Thanks to the R creators for such a great statistical system. Thanks to the R help list, I have (finally) gotten far enough in R to have a question I hope to be worth posting. I'm using the recode function from John Fox's car package and have encountered some unexpected behavior. Consider the following example: ## Begin cut-and-paste example require( car ) set.seed(12345) nn <-

An earlier post had posed the question: "Does anybody know what is relation between 'T' value calculated by 'wilcox_test' function (coin package) and more common 'W' value?" I found the question interesting and ran the commands in R and SPSS. The W reported by R did not seem to correspond to either Mann-Whitney U, Wilcoxon W or the Z which I have more

I am hoping for some advice regarding ordering a dataframe, by date. The dataframe is in the format below. $story $datepub story10 1 April 1999 story 90 1 March 2002 story 37 10 July 1985 I want to reorder the entire dataframe so the earliest story is first, and save the reordered dataframe. The command, 'class' (datepub) reveals $datepub is a factor variable. I tried

I am hoping for some advice as to how to modify the following syntax, so that instead of saving all records which refer to Farrah, I select all instances that do not include Farrah, or the word Coolum. test <- read.csv("c:\\newdat.csv", as.is=TRUE, header=T) sure <- test[grep('Farrah', paste(test$V3.HD, test$V3.LP, test$V3.TD)),]