similar to: paste command

Dear List: I am working to generate graphs for individual students that will be created through a series of loops in Sweave. Before doing so, I am still trying to design the graph. The code for creating the barplot is below with some sample datapoints just made up for now. Ultimately, this chart will take data from an lme object using longitudinal student data. So, the dots represent the

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is

Dear List: I was able to run the following in nlme successfully, but the same model and code (same dataset) failed to run in lme4 and gave me the error message below. Any thoughts? lme(math~year, data=egsingle, random=~year|schoolid/childid) Error in lme(formula = math ~ year, data = egsingle, random = structure(list( : Unable to invert singular factor of downdated X'X

Dear List: I'm creating a series of barplots using Sweave that must assume a standard format. This is student achievement data and the x-axis must include all grades 3 to 8. In some cases, the data for a grade (or more than one grade) are missing in the vector math.bar, but are never missing for the vector apmxpmeet. The following sample code illustrates the issue. Using the code below to

Hello I have a longitudinal dataframe organized in the long format and would like to make comparison between successive rows if certain conditions apply. Specifically, I have four variables of interest: grade, score, year, and schid, associated with each school with 3 measurements per school per grade, therefore the rows are temporally ordered and each school occupies multiple rows. For example,

This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the

I have grades data. I read them from a csv in letter-grade format. I then converted them to levels levels(grades$grade)=c('A+','A','A-','B+','B','B-','C+','C','C-','D+','D','D-') And then to numbers grades$gp=grades$grade levels(grades$gp)=c(4.3,4.0,3.7, 3.3,3.0,2.7, 2.3,2.0,1.7, 1.3,1.0,0.7)

I have a form that I want to use to update multiple objects. In the controller, @grades = Grade.find(params[:grade].keys) @grades.each_with_index do |grade, i| grade.update_attribute(params[:grade][i]) end all_valid = @grades.inject(true) {|memo, c| c.valid? && memo } this doesn''t update the attributes as I would expect. (I would just use

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

Hi-- I am trying to normalize course grades for each instance of a course, e.g. Stats 1 Fall2009 J. Smith. I have a frame for all instances of a course, e.g. stats 1 in the last 5 years, that looks like SIDN TERM GRADE INST where SIDN is a Student ID Number, TERM is a factor that gives the quarter and year a course was offered, GRADE is a 0-4.3 grade and INST is the instructor, again as a

Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The

I would like to create 15 box plots from two sets of data. Set1 - containts PayGrade, Min_Salary, Max_Salary data for 15 pay grades Set2 - contains PayGrade, Actual_Min, Actual_Max, and Actual_Mean for the 15 pay grades I would like 15 box plots (one for each paygrade) whose whiskers were the Min_Salary and Max_Salary data and whose ''box'' was Actual_Min, Actual_Mean,

Env: R 2.8.1, Win Xp, Eclipse/StatET In a .Rd file, I have an example containing the lines: # calculate Y M, using polynomial contrasts trends <- as.matrix(VocabGrowth) %*% poly(8:11, degree=3) colnames(trends)<- c("Linear", "Quad", "Cubic") [At the risk of a long message, I'll append the complete .Rd file at the end of this message, in case this was

Dear List: I have a large dataset of multiple schools. My goal is to produce a separate tex file for each school that plots some of the student achievement scores. Essentially, the aim is to develop a custom report for each school. To accomplish this, I have code for a loop that gets sourced into R and then Sweaves the multiple files to create the individual school reports. Here is the code for

Is there an efficient way to create a series of dummy codes from a single variable? For example, I have a variable, “grade” = {2, …, 12}. I want to create k-1 dummy codes for grade such that grade 2 is the base (i.e, grade 2 =0). I am hoping that the new variables can be labeled as grade.3, grade.4 etc. I'll then use grade <- paste("grade.", 3:12, sep="") in

I am working with a longitudinal data set in the long format. This data set has three observations per grade level per year. Here are the first 10 rows of the data frame: >tenn.dat[1:10,] year schid type grade gain se new cohort 6 2001 100005 5 4 33.1 3.5 4 3 7 2002 100005 5 4 33.9 3.9 4 2 8 2003 100005 5 4 32.3 4.2 4 1 10 2001 100005

I have data on every grade in all elementary schools in Chicago over 5 years. I would like to estimate a trend over time for each grade in each school. There are 17,600 data all together (about 460 schools, nearly 8 grades each, over 5 years). Is there a not-so-hard way to do this in R (I was thinking of using rlm)? ______________________________________________________________________ Stuart

Two things I think are some of the best developments in statistics and production are the lattice package and the beamer class for presentation in Latex. One thing I have not become very good at is properly sizing my visuals to look good in a presentation. For instance, I have the following code that creates a nice plot (sorry, cannot provide reproducible data).

Hola, Esta pregunta la hice en stackoverflow <http://stackoverflow.com/questions/31137940/randomly-assign-teachers-to-classrooms-imposing-restrictions/31143808#31143808>pero nadie pudo contestarla. 1. Quiero generar N escuelas, con G grados y C divisiones. 2. Quiero asignar cada uno de T maestros a 2 divisiones en un grado y escuela Si tengo C=4 divisiones, puedo lograr lo que quiero con

I get the following error when I run qplot() qplot(grade, read,data = hhm.long.m, geom = c("point", "smooth")) Error in smooth.construct.cr.smooth.spec(object, data, knots) : x has insufficient unique values to support 10 knots: reduce k. I am not sure how to tackle this problem. When I take a subsample (< 1000) than I am able to run that function but with my sample