search for: quintiles

I have some output from a survey shown below and would like to insert total rows for each category to then be able to use it as a data set for further analysis. Is it possible to do this in R. In this example I would like to insert a row between rows 5 and 6, 10 and 11, 15 and 16, 20 and 21 and put in the sum of the rows 1-5, 6-10, 11-15, 16-20 and to delete row 21 which has NA in it. I would

Hi, I am using the package "demography" from Rob Hyndman for the Lee-Carter-Model. It is an amazing powerful tool but I am struggling with one issue: *I want to compute different quintiles for the cumulative survival probability derived from the Lee-Carter-Forecast (e.g. the 50%-quintile, 75%-quintile and 99%-quintile) for the next 10 years. * I am sure the package possess this functionality but I didn't find any way to calculate quintile values. Hope you can help me! Than...

Dear All, I am economist and working on poverty / income inequality. I need descriptive statitics like the ratio of education expentitures between different income quintiles where each household has a different weight. After a bit of google search I found 'Hmisc' and 'quantreg' libraries for weighted quantiles. The problem is that these packages give me only weighted quintiles; but what I need is conditional weighted quintiles. The below example illust...

Hi, I have a mysql table with fields userid,track,frequency e.g u1,1,10 u1,2,100 u1,3,110 u1,4,200 u1,5,120 u1,6,130 . u2,1,23 . . where "frequency" is the number of times a music track is played by a "userid" I need to turn my 'frequency' table into a rating table (it's for a recommender system). So, for each user, I need to categorise the frequency of tracks

...works in some cases and often gives the following error: Error in cut.default(df$VOLATILITY, unique(breaks), label = FALSE, na.rm =TRUE): invalid number of intervals Could you give me some advice on how to improve this code so that it works properly. It's relatively urgent. Many thanks! quintilesVolByMonth <- function(x){ months<-as.vector(unique(x$DATE)) dfx<-data.frame() for(n in seq(1,length(months))){ num<-5 print(paste("Appending month",months[n],sep="")) df<-subset(x,DATE==months[n]) breaks<-quantile(df$VOLATILITY,pr...

Hi, I am looking to build even quintiles for a set of data. I managed to get it done, but I would like to know if there is a more direct way to write the data from my loop output x in the bottom of the code into the "empty" matrix p1, which I filled with NA''s. The way I am doing it at the moment is, more or less adding...

...115 0.123 0.115 0.166 0.000 MMA 0.091 0.107 0.115 0.142 0.179 0.000 DMA 0.126 0.103 0.126 0.129 0.142 0.031 The numbers in the dataframe indicate values of a continuous variable INMET (indicating ratio of inorganic arsenic vesus methylated arsenic species) for the respective quintiles of variables INAS, MMA, and DMA; "lowest" through "highest" indicate quintile levels of INAS, MMA, and DMA. INAS, MMA, and DMA are discrete ordinal variables (factors, each variable has following levels: lowest, ..., highest). Significance indicates significance levels. >F...

...ot against the fourth which is the date. First I 'aggregate' the patient_ids: id<-unique(dat$patient_id) Then I try (and fail) to create a loop, that is supposed to plot the data: for(i in 1:8480){patient_id==id[i]plot(date,value)} What might be wrong? And how could I only plot eg quintiles for the ones that go down fastest? Thanks, Jukka

Hello- I wonder if there's a way to replicate SAS rank procedure where it ranks a variable by a certain number of groups. For example, it's very easy to calculate quintile rank in SAS, but I couldn't find the similar function in R. Does anyone know how to do this? Thanks. -- View this message in context:

Hello All, I am trying to color five subsets of points in a series of vertical strip charts by quintiles using the quantile function, but I have not been able to do this successfully, nor have I been able to find an example of this online. I would like to have the "E1", "E2", and "E3" columns plotted on a single plot (containing the three strip charts). I am overlaying...

Hi all, I am not sure how to handle interactions with categorical predictors in the GAM models. For example what is the different between these bellow two models. Tests are indicating that they are different but their predictions are essentially the same. Thanks a bunch, > gam.1 <- gam(mortality.under.2~ maternal_age_c+ I(maternal_age_c^2)+ + s(birth_year,by=wealth) + +

...culo he leído que el PSM se puede utilizar como un elemento de clasificación y por tanto de homogeneización. Mi intención es aplicar el PSM a un análisis de supervivencia. En este sentido mi hipótesis es que una variable ?x? tanto en su versión cuantitativa como categorizada a terciles,cuartiles o quintiles influye sobre la supervivencia de los sujetos. Esto entiendo que puedo resolverlo con un análisis de supervivencia y posteriormente con una regresión de Cox. Este método seria valido desde el punto de vista estadístico si bien desde el punto de vista biológico podría tener alguna duda de interpreta...

...culo he leído que el PSM se puede utilizar como un elemento de clasificación y por tanto de homogeneización. Mi intención es aplicar el PSM a un análisis de supervivencia. En este sentido mi hipótesis es que una variable ?x? tanto en su versión cuantitativa como categorizada a terciles,cuartiles o quintiles influye sobre la supervivencia de los sujetos. Esto entiendo que puedo resolverlo con un análisis de supervivencia y posteriormente con una regresión de Cox. Este método seria valido desde el punto de vista estadístico si bien desde el punto de vista biológico podría tener alguna duda de interpreta...

...two-comun data frame. column 1 is the period-one individuals' earnings and column two is the period-two. n <- nrow(X) #12000 sim <- runif(n, -.0001, .0001) X <- X + sim q <- 10 # in order to compute deciles. it could be quintiles, quartiles, whatever p <- seq(0,1,1/q) f.x <- quantile(X[,1], p, names=F) f.y <- quantile(X[,2], p, names=F) f.x[1] <- 0; f.y[1] <- 0 a <- cut(X[,1], f.x, right=T) b <- cut(X[,2], f.y, right=T)...

I used points graphic (geoR) in this way: points(zn,pt.divide=c("quintiles"), main="Location map of Zn",lambda=1,col="gray",yl="coord y",xl="coord x",x.leg=0. 3, y.leg=5.5,dig.leg=2,cex.min=0.5,cex.max=1,) Can I reduce legend characters (a sort of cex)?

Dear R-people, I am analyzing epidemiological data using GLMM using the lmer package. I usually explore the assumption of linearity of continuous variables in the logit of the outcome by creating 4 categories of the variable, performing a bivariate logistic regression, and then plotting the coefficients of each category against their mid points. That gives me a pretty good idea about the

Hi everyone, I'm experiencing difficulty getting the results I want when I use a nested for loop. I have a data set to which I perform some calculations, and then try to apply a regression over a rolling window. The code runs, but the regression results I am getting (intercept and slope) are simply the same, repeated again and again in the results matrix. The regression does not seem to be

Hello, I have inherited a setup where there are 2 AIX 5.1 systems in 2 separate sites. There are large database files that are backed from each site to the other via rsync. Currently, it is using rsync version 2.5.4. It does it via ssh with the options -avz. This has all been merrily plodding along for some time. There is one file that is over 45 GB, and it started having trouble with that

Some time ago I was allowed to discuss "Diamond Graphs", and whether they would be useful in R, in this mailing list. The August 2003 issue of The American Statistician has finally arrived here and I have been able to read the article. A number of points of interest arise. 1. The article is "A Diamond-Shaped Equiponderant Graphical Display of the Effects of Two

I've written a function that takes some input data output from a simulation model and creates some graphs. It's not very complicated code, and it works perfectly fine if I just run the code as is. But I have converted it into a function so we call it externally, and when I try to source the code to test the function, I get the error message "variable names are limited to 256