similar to: Logistic Regression with genetic component

Greetings ~ I need some assistance determining an appropriate approach to analyzing multivariate binary response data, and how to do it in R. The setting: Data from an assay, wherein 6-hours-post-fertilization zebrafish embryos (n=20, say) are exposed in a vial to a chemical (replicated 3 times, say), and 5 days later observed for the presence/absence (1/0) of defects in several organ systems

[Env: R 2.14.2 / Win Xp] In the script below, I want to select some variables from rrcov::OsloTransect, delete cases with any missing data, and subset the data frame Oslo to remove cases for two levels of the factor litho that occur with low frequency. The checks I run on my new data frame Oslo look OK, but I when I try to fit a multivariate linear model with lm(), I am getting an error:

Hi all Consider the classic data below from Darwin on the heights of 15 pairs of zea mays (corn) plants either cross-fertilized or self-fertilized, where the goal is to see if it makes a difference. > head(ZeaMays) pair pot cross self diff 1 1 1 23.500 17.375 6.125 2 2 1 12.000 20.375 -8.375 3 3 1 21.000 20.000 1.000 4 4 2 22.000 20.000 2.000 5 5 2 19.125

The last line of the example in droplevels' manual page seems to be incorrect to me. I think it should read: "table(droplevels(aq$Month))". Amazingly (I don't understand) both variants seem to produce the same result (R 3.3.3): --- > aq <- transform(airquality, Month = factor(Month, labels = month.abb[5:9])) > aq <- subset(aq, Month != "Jul") >

Hello, I used the glm function in R to fit a dose-response relationship and then have been using dose.p to calculate the LC50, however I would like to calculate the NOEL (no observed effect level), ie the lowest dose above which responses start occurring. Does anyone know how to do this? [[alternative HTML version deleted]]

Hello, Inline. Em 12-04-2017 16:40, Henric Winell escreveu: > (Let's keep the discussion on-list -- I've added back R-devel.) > > On 2017-04-12 16:39, Ulrich Windl wrote: > >>>>> Henric Winell <nilsson.henric at gmail.com> schrieb am 12.04.2017 >>>>> um 15:35 in >> Nachricht <b66fe849-bb8d-f00d-87e5-553f866d57e0 at gmail.com>:

Dear all, I am developing a package, which bundles my most frequently used functions. One of those is a modified version of droplevels from the base package (basically, it preserves any contrast function which was used to create the factor, contrast matrices are not kept, for they could be wrong if a level is dropped). In my NAMESPACE file I've the following directives, which should export

Hi, Just reporting a small bug? not really a big deal, but I don?t think that is intended: droplevels()?also drops all object?s attributes. Example: > > test <- c("hello", "something", "hi") > > test <- factor(test) > > comment(test) <- "this is a test" > > attr(test, "description") <- "this is another

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Tue, 16 May 2017 11:01:23 +0200 writes: >>>>> Serge Bibauw <sbibauw at gmail.com> >>>>> on Mon, 15 May 2017 11:59:32 -0400 writes: >> Hi, >> Just reporting a small bug? not really a big deal, but I >> don?t think that is

Hello I have the following problem : The dataframe TEST has multiple lines for a same person because : there are differents values of Nom or differents values of Prenom but the values of Matricule or Sexe or Date.de.naissance are the same. TEST <- structure(list(Matricule = c(66L, 67L, 67L, 68L, 89L, 90L, 90L, 91L, 108L, 108L, 108L), Nom = structure(c(1L, 2L, 2L, 4L, 8L, 5L, 6L, 9L, 3L, 3L,

In R devel r71124, if 'x' is a factor, droplevels(x) gives factor(x, exclude = NULL) . In R 3.3.1, it gives factor(x) . If a factor 'x' has NA and levels of 'x' doesn't contain NA, factor(x) gives the expected result for droplevels(x) , but factor(x, exclude = NULL) doesn't. As I said in https://stat.ethz.ch/pipermail/r-devel/2016-May/072796.html , factor(x,

Dear all, Today I figured out that there is a neat function called droplevels, which, well, drops unused levels in a data frame. I tried the function with some of my data sets and it turned out that not only the unused levels were dropped but also the contrasts I set via "C". I had a look into the code, and this behaviour arises from the fact that droplevels uses simply factor to drop

In R devel r71157, 'droplevels' documentation, in "Arguments" section, says this about argument 'exclude'. passed to factor(); factor levels which should be excluded from the result even if present. Note that this was implicitly NA in R <= 3.3.1 which did drop NA levels even when present in x, contrary to the documentation. The current default is compatible with x[ ,

Hi, I have the following data: > Myvalues Gene ES MEF Embryo ESHyp 1 GeneA -0.38509507 0.00 1.6250 1.7039921 2 GeneB 0.06262914 0.00 1.6250 -0.272033 and so on... I want to plot the expression values of GeneA and GeneB in the different cell/embryo/conditions (columns 2:5 above). Now, if I do: >library(ggplot2) > qplot(x=Gene, Embryo, geom =

I am basically fine with the change. How about using just the following? if(!is.character(exclude)) exclude <- as.vector(exclude, typeof(x)) # may result in NA x <- as.character(x) It looks simpler and is, more or less, equivalent. In factor.Rd, in description of argument 'exclude', "(when \code{x} is a \code{factor} already)" can be removed. A larger

On Mon, 22 Jan 2024, Rich Shepard wrote: > As an aquatic ecologist I see regulators apply the geometric mean to > geochemical concentrations rather than using the arithmetic mean. I want to > know whether the geometric mean of a set of chemical concentrations (e.g., > in mg/L) is an appropriate representation of the expected value. If not, I > want to explain this to non-technical

Hi all, I am having a bit of trouble using the levels() function. I have a factor with many elements, and when I use the function levels() to extract the list of unique elements, some of the elements returned are not actually in the factor. For example I would have this: > vector <- dataset$Benchmark > class(vector) [1] "factor" > length(vector) [1] 35615 > vector2

I have searched the archives and instructions high and low but have not found what I need. I have a dataframe named Data with columns: AdjResND0 - the numeric result Parameter - the classification (chemical name) Sort - the order I want the chemical names to appear, with leading zeros so all are the same length Client.Name - the sample name I am trying to generate a series of 1 page barcharts,

I'm doing these manipulations on the data frame and wondering why does R have to remember historical data on my operation and not just keep the needed info. Probably a basic fundamentals of the way R handles data .. Pls point me to the manual if possible .. I have this Index data: > head(NIFTY_INDX) Constituents.list.of.S.P.CNX.Nifty X X.1 X.2 X.3

hello, I am very new to R. My current data set is a mix of values and categories. It is a geoscience data set, with values per rock sample. Case in point, each sample belongs to a lithology class, and each sample has several physical property measurements (density, porosity...). I want to be able to plot these physical properties for all samples in each lithology class. this is how i'm doing