similar to: ggplot2: mixing colour and linetype in geom_line

Hallo, I have this dataset with repeated measures. There are two within-subject factors, "formant" (2 levels: 1 and 2) and "f2 Ref" (25 levels: 670, 729, 788, 846, 905, 1080, 1100, 1120, 1140, 1170, 1480, 1470, 1450, 1440, 1430, 1890, 1840, 1790, 1740, 1690, 2290, 2210, 2120, 2040, 1950), and one between-subject factor, lang (2 levels:1 and 2). The response variable

Hello, I’d like to do next, see if you could help me please: I have a csv called “datuak” with a id called “calee_id” and a colunm called “poids”. I have another csv called “datuak2” with the same id called “calee_id”, (although there are “calee_id” that are in “datuak” but not in “datuak2” and inverse), and a column called “kg_totales” in which the values are repeteated for each calee_id

Hello, after splitting a data-frame I want to access the results. Maybe the problem is, that the factor/index is a string... ...or do I miss knowing details of the index-uasge? Please look and help: ======================================= > weblog <- read_weblog("web.log") > > > str(weblog) 'data.frame': 2247 obs. of 18 variables: $ host : Factor w/ 77

Hi Folks... Œbeen playing with this for a while, with no luck, so I¹m hoping someone knows it off the top of their head... Difficult to find this nuance in the archives, as so many msgs deal with read.csv! I¹m trying to read a data file with the following structure (a little piece of the actual data, they are actually csv just didn¹t paste with the commas): wavelength SampleA SampleB SampleC

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Hi, I've looked through the archives and seen references to placing calls on hold on a snom 200 (any version of the firmware but we have the latest: 2.05e.) Basically, we can't place calls on hold on the snom 200! The manual talks about the Flash button (which is really the "R" button, as far as I can tell.) Pressing the R button will immediately disconnect the incoming call.

Hi everyone, I'm sorry if this turns out to be more a statistical question than one specifically about R - but would greatly appreciate your advice anyway. I've been using a logistic regression model to look at the relationship between a binary outcome (say, the odds of picking n white balls from a bag containing m balls in total) and a variety of other binary parameters:

Dears useRs, I am using the mle function but this gives me the follow erros that I don't understand. Perhaps there is someone that can help me. thank you for you atention. Bernardo. > erizo <- read.csv("Datos_Stokes_1.csv", header = TRUE) > head(erizo) EDAD TALLA 1 0 7.7 2 1 14.5 3 1 16.9 4 1 13.2 5 1 24.4 6 1 22.5 > TAN <-

Hi All, I have conducted the following survival analysis which appears to be OK (thanks BRipley for solving my earlier problem). > surv.mod1 <- survreg( Surv(timep1, relall6)~randgrpc, data=Dataset, dist="weibull", scale = 1) > summary(surv.mod1) Call: survreg(formula = Surv(timep1, relall6) ~ randgrpc, data = Dataset, dist = "weibull", scale = 1)

Dear all: I converted the columns (Baci, Meti, Fungii, Protozoai) into integers (using excel) and then imported the data (.txt) into R. Interestingly, the other three variables were loaded as INT, but the 'Baci' one continued as Num. I imported the data using the following command line: X <- read.delim(file.choose(), header = TRUE, dec =

I would like to know if it is possible to perform negative binomial regression with rate data (incidence density) using the glm.nb (in MASS) function. I used the poisson regression glm call to assess the count of injuries across census tracts. The glm request was adjusted to handle the data as rates using the offset parameter since the population of census tracts can vary by a factor of

I have a huge frame holding holding model results for a number of locations and time series: > str(tonedata) `data.frame': 434 obs. of 339 variables: $ VALUE : int 101 104 105 106 111 118 119 121 122 123 ... $ COUNT : int 2443 184 1539 1016 132 1208 1580 654 864 560 ... $ AREA : num 6.11e+08 4.60e+07 3.85e+08 2.54e+08 3.30e+07 ... $ D1_1958 : num 470 446 452 457 407 ...

The R documentation for some of the foreign package's functions says that the set of variable labels becomes attributes in the resulting data frame. Thus, e.g., 5="strongly agree", 4="agree", etc. I'm happy that the labels are being passed, but unfortunately, when R summarizes the data, it will list it only as categories, and doesn't deal with the

Dear R-developers, I came to a somewhat unexpected behaviour of read.csv() which is trivial but worthwhile to note -- my data involves a protein named "1433E" but to save space I drop the quote so it becomes, Gene,SNP,prot,log10p YWHAE,13:62129097_C_T,1433E,7.35 YWHAE,4:72617557_T_TA,1433E,7.73 Both read.cv() and readr::read_csv() consider prot(ein) name as (possibly confused by

Hello!   I estimate vector error correction model (vecm) model. I have only one cointegratio relationship. I write :   joh.vecm.rls <- cajorls(joh.vecm, r=1) The output estimation is : Call: lm(formula = substitute(form1), data = data.mat) Coefficients:                up.d            expl.d        upd.d           r.d      ect1      -1.34e-01   4.55e+02   6.91e+00   2.43e+03 constant 

I am a novice R user, and I am having difficulty understanding R's influence plots. I am trying to remove outliers from a particular variable, "sib." I am able to generate influence plots and further outlier information such as below (which is a shortened example). For my analyses, I end up excluding the points R refers to, 7, 18, 26, and 105. However, my question is, how can I

Hi Folks, I've encountered something I hadn't been consciously aware of previously, and I'm wondering what the explanation might be. In (on another list) using R to demonstrate the difference between different contrasts in 'lm' I set up an example where Y is sampled from three different normal distributions according to the levels ("A","B","C")

Are there any Snom 200 users that have two extns defined on their phone? I've been trying to get two (or more) extns defined in such a way that when extn #1 rings, LED #1 flashs; extn #2 rings, LED #2 flashes, etc. (Answer greating will be different depending upon which extension is called.) I can get multiple extns to register and work with * just fine, but regardless of which extn is

Using the small reproducible example below, I'd like to know if one can somehow use the matrix "sig" (defined below) to add a black outline (with lwd=2) to all pixels with a corresponding value of 1 in the matrix 'sig'? So for example, in the ggplot2 plot below, the pixel located at [1,3] would be outlined by a black square since the value at sig[1,3] == 1. This is my first

Hi guys, I have been testing the hypothesis for difference of survival between four different classes. The p-values provided in coxph output are confusing for me to interpret. Here is the output : sur<-coxph(Surv(SURVIV, status == 1)~factor(A)+cluster(rownames(d)), data = d, model=TRUE) Call: coxph(formula = Surv(SURVIV, status == 1) ~ factor(A) + cluster(rownames(d)), data = d, model = TRUE)