similar to: data managment

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter

Unless there is good reason not to, always cc the list -- there are lots of smarter folks than I on it who can help. I may or may not have time to look at this. Hopefully someone else will. -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474

Hi, When I run the survfit function, I want to get the restricted mean value and the standard error also. I found out using the "print" function to do so, as shown below, print(km.fit,print.rmean=TRUE) Call: survfit(formula = Surv(diff, status) ~ 1, type = "kaplan-meier") records n.max n.start events *rmean *se(rmean) median 200.000

Dear all,I am a new user of WinBUGS and need your help. After running the following code, I got parameters of beta0 through beta4 (stats, density), but I don't know how to get the prediction of the last value of h, the variable I set to NA and want to model it using the following code.Does anyone can given me a hint? Any advice would be greatly appreciated.Best

I am trying to use t.test on the following data: date type INTERVAL nCASES MTF SDF MTO SDO nFST MF nOBS MO MB BIASCV BIASEV ME MAE RMSE CRCF 2001-06-15 avn GE1.00 4385 0.246 0.300 1.502 0.556 1367 1.373 4385 1.502 1.471 0.285 0.164 -1.256 1.266 1.399 0.056 2001-06-15 avn

I have a file: x y z 0.025 0.025 1.65775 0.025 0.050 1.62602 0.025 0.075 1.63683 0.025 0.100 1.91847 0.025 0.125 2.00913 0.025 0.150 1.82222 0.025 0.175 1.70901 0.025 0.200 1.39759 0.025 0.225 1.39089 0.025 0.250 1.04762 If I read the file like this: data<-read.table("file.dat") How do I access the vectors x,y,z that are inside the dataframe data? I studied Venables and

Hi, I am using R to do a principal components analysis for a class which is generally using SPSS - so some of my question relates to SPSS output (and this might not be the right place). I have scoured the mailing list and the web but can't get a feel for this. It is annoying because they will be marking to the SPSS output. Basically I'm getting different values for the component

I am doing some coxPH model fitting and would like to have some idea about how good the fits are. Someone suggested to use Frank Harrell's C-index measure. As I understand it, a C-index > 0.5 indicates a useful model. I am probably making an error here because I am getting values less than 0.5 on real datasets. Can someone tell me where I am going wrong please ? Here is an example using

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has

I currently work on a draft of an aquatic bioassessment. The conditions tested are the following: ER river water T dechlorinated water control 0.5 + 0.5mg / L of malate T + 1 dechlorinated water control + 1g / L of malate T ED dechlorinated water control SED + ER + river water sediment SED ED + sediment + water dechlorinated. It is the result of AChE in muscle (fillet of fish). The production of

Dear helpers, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

Hello, I’m trying to follow the syntax of a script from a journal website. In order to create a regression formula used later in the script, the regression matrix must have column names “X1”, “X2”, etc. I have tried to assign these column names to my matrix ScoutRSM.mat using a for loop, but I don’t know how to interpret the error message. Suggestions? Thanks, Paul

Hi- I am having trouble with the syntax of looping through the rows and columns of a data frame. I have a table with 17 observations for 84 lines at n=5-10 per line. So the table is ~700x17. I want to pull out the median and stdev for each line and put it in a dataframe with rowname = linename. So I have tried the following.... #read in the table input.table <- read.table(file =

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