similar to: read.table problem with column headers

I'm trying to get a semi-automated approach to processing survey data that I'm getting from mod_survey, an Apache-based web survey tool. It looks like one can do this with enough experience in writing R routines. Before I start from scratch, is there a sample file that shows good techniques for producing labeled graphs and tables from survey data with R? I've looked but not found what

Hint #1, to do any useful transformations on your variables you will probably need to convert them temporarily into character variables (aka strings). Do that with as.character(n$OSUSE) Probably your will want to convert each of the variables that are in this format into a set of numeric variables. Something like this: n <- data.frame(OSUSE =

I am processing some survey results, and my data are being read in as "factors". I don't know how to process these things in any way. To start with, several of the survey questions are mulit-choice check boxes on the original (web-based) survey, as in "check all that apply". These are encoded as numbers. For example, if the survey has a question: Which operating systems

Hey, Is it possible that R can calculate each options under each column and return a summary table? Suppose I have a table like this: Gender Age Rate Female 0-10 Good Male 0-10 Good Female 11-20 Bad Male 11-20 Bad Male >20 N/A I want to have a summary table including the information that how many answers in each category, sth like this: X

Hello All R Users, Function loglm() in library MASS can be cajoled to accomodate structural zeros in a cross-classification table. An example from Fienberg demonstrates how this can be done. My question is: Can the function glm() perform the same task? Can glm() estimate a log-linear model with fixed zeros like loglm()? Thanks for your help, Andrew ## Fienberg, The Analysis of Cross-Classified

Dear R people, I have a very big tab-delim txt file with header and I only want to import several columns into R. I checked the options for "read.table" and only found "nrows" which lets you specify the maximum number of rows to read in. Although I can use some text editors (e.g., wordpad) to edit the txt file first before running R, I feel it?s not very convenient. The

Hi all, I have data collected from a survey administered on a subset of the population. I also have the population proportions of variables such as gender, race and housing type. I would like to combine the weights from each separate cross tab (of gender, race and housing type) such that the weighted proportions of my survey data matches that of the population. I have tried the following:

Let''s say I have three hypothetical MySQL tables: ? people, with columns id, gender, and source_id belongs_to :boys and :girls ? boys, with columns id and name has_many :people ? girls, with columns id and name has_many :people The gender column in people specifies which of the two source tables the source_id refers to. For example, if we have values: 1, boy, 1 in people,

Dear R helpers, I have a social network data including repated measures of ten alters (whom you contact) and their attributes(gender, age, strength of tie). I wrote variables related with alters just for wrote alter 1 and alter 2. I'd like to change the like below. I'd change each name separetely. Do you know any pratical way to change it? All the bests, Niklas variables for alter 1

Hi, When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables. So for example in this data-frame: data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5))) aggregate(data,

Basic question: when I use names() to extract the name of a dataframe element, why does it have "." instead of " " between words? Context: I'm importing a CSV file of survey results for analysis. I read them like this: df <- read.csv("surveydata.csv",nrows=40,header=TRUE,

Hi Everyone, Here's a silly newbie question. How do I remove unwanted rows from an R table? Say that I read my data as: X <- read.table("mydata.txt") and say that there are columns for age and gender. Call these X[5] and X[10], respectively. Here, X[5] is a column of positive integers and X[10] is binary valued i.e., zero (for male) and one (for female) Now, say that I

Hi there I'm trying to fit a logistic regression model to data that looks very similar to the data in the sample below. I don't understand why I'm getting this error; none of the data are proportional and the weights are numeric values. Should I be concerned about the warning about non-integer successes in my binomial glm? If I should be, how do I go about addressing it? I'm

Dear all, I have a table like this: > eds R.ID Region Gender Agegr Time nvisits 1 1 A F 60--64 1:00 1 2 2 O F 55--59 1:20 1 3 3 O F 55--59 3:45 3 4 4 S M 60--64 1:10 3 5 5 W F 55--59 12:30 1 6

Dear list colleagues, I'm trying to come up with a test question for undergraduates to illustrate comparison of means from a complex survey design. The data for the example looks roughly like this: mytest<-data.frame(harper=rnorm(500, mean=60, sd=1), party=sample(c("BQ", "NDP", "Conservative", "Liberal", "None", NA), size=500,

Hello, I am working on some examples of GLMM for my students but I am afraid that my way of preparing a dataframe to pass to lmer will make them think that R is a very difficult and un-natural language. Here is for example a simple data set about approval ratings on two different surveys for a random sample of 1600 individuals. > ## Example: Ratings of prime minister (Agresti, Table 12.1,

Hi, Im having trouble creating the following graph. Here is my code: library(plotrix) library(prettyR) female_improvement <-read.table("C://project/graphs/gender/breakdown/gender-improvement/female-improvement.csv", sep=",", header=TRUE) barp(rbind(rep(length(female_improvement$gender),2),freq(female_improvement$reason)[[1]]), ylab="22 Males participated in the

Dear all, I am a R beginner, and I am looking for a way to do the same thing for all levels of a column in a table. Basically, I have a bunch of protein sequences composed of different amino acid residues, and each residue is represented by an uppercase letter. I want to calculate the ratio of different amino acid residues at each position of the proteins. Here is an example table: Proteins

I have a data file that looks like this. __DATA__ D7KAR5Z02F447V 176 G 0.22 D7KAR5Z02J3WLG 94 A 1.05 29 D7KAR5Z02F4K6L 198 a 0.13 D7KAR5Z02J4SYO 67 C 0.95 28 D7KAR5Z02J4SYO 83 C 1.01 29 D7KAR5Z02J4SYO 97 T 0.13 D7KAR5Z02J4SYO 166 A 0.94 27 I want the rows where the last column has no-entry to be filled with "-". Is there a way to do it with

Dear colleagues, I'm working with the 2008 Canada Election Studies (http://www.queensu.ca/cora/_files/_CES/CES2008.sav.zip), trying to construct a weighted national sample using the survey package. Three weights are included in the national survey (a household weight, a provincial weight and a national weight which is a product of the first two). In the following code I removed variables with