similar to: predictive logistic model cell-biology, non-dichotomous data

In this real example (below), all four of the replicates in one treatment combination had zero failures, and this produced a very high standard error in the summary.lm. =20 Just adding one failure to one of the replicates produced a well-behaved standard error. =20 I don't know if this is a bug, but it is certainly hard for users to understand. =20 I would value your comments=20 =20 Thanks =20

Getting the through items from a has_many :through :uniq relationship In a nutshell, I have been using the has_many :through :uniq relationship, and I want a DRY way to list the join model objects. Currently, my objects include taxon objects, toxin objects, data_object objects, and taxon_toxin_citation objects ("citation" is another word for data_object). A taxon has many data objects,

Hi i would like to use some graphs or tables to explore the data and make some sensible guesses of what to expect to see in a glm model to assess if toxin concentration and sex have a relationship with the kill rate of rats. But i cant seem to work it out as i have two predictor variables~help?Thanks.:) Here's my data. >

Hi, there I first sent this e-mail a couple months ago, to no avail.Since I am not a member on your mailing list, so could you please cc: a response to me? I'll be sure to check the list today for replies. I am currently attempting to perform an ANOVA with both nested and normal factors. My problem is that R is treating my nested factors the exact same way as it would interaction terms.

Hi, I am using OpenSSH 2.5.2p2 on Solaris 2.7 (Ultra 10) with 64bit support and have the following problem when connecting with the ssh2 protocol to non-solaris OS: On the client side, I do: /local/work/lysis/bin/slogin -v -2 -p 2222 rs30 On the server side (AIX 4.3), the sshd runs as follows: aix/sbin/sshd -p 2222 -d Full output follows at the end of this mail. The server is compiled with

Hello, I am trying to fit my Elisa results (absorbance readings) to a standard curve. To create the standard curve model, I performed a 4-parameter logistic fit using the 'drc' package (ExpectedConc~Absorbance). This gave me the following: > FourP A 'drc' model. Call: drm(formula = Response ~ Expected, data = SC, fct = LL.4()) Coefficients: b:(Intercept) c:(Intercept)

Hello, I am using R, through rsruby, to create a graph and best fit line for a set of data points, regarding data collected in a Chemistry class. The problem is that although the graph functions perfectly properly, the best fit line will not work. I initially used code I pretty much copied from a website with a tutorial on this, which was: graphData.png("/code/Beer's-Law

Hi, there I am not a member on your mailing list, so could you please cc: a response to me? I am currently attempting to perform an ANOVA with both nested and normal factors. My problem is that R is treating my nested factors the exact same way as it would interaction terms. My output for the nested model is as follows: > nested <- anova(lm(ltotinv ~ habitat + fish/lake +

Hi I have measured the UV absorbance (abs) of 10 solutions of a substance at known concentrations (conc) and have used a linear model to plot a calibration graph with confidence limits. I now want to predict the concentration of solutions with UV absorbance results given in the new.abs data.frame, however predict.lm only appears to work for new "conc" variables not new "abs"

Hello, I'm new here, but will try to be as specific and complete as possible. I'm trying to use “lm“ to first estimate parameter values from a set of calibration measurements, and then later to use those estimates to calculate another set of values with “predict.lm”. First I have a calibration dataset of absorbance values measured from standard solutions with known concentration of

I am having a similar problem understanding the data structure of the "yarn" dataset described in the "[R] data structure for plsr" posts. I have spectroscopic data I'd like to run through a PLSR and have read the tutorial series, but still do not understand the data format required for the code to process my data. My current data structure consists of a .csv file read into

Hello! I am having an issue with the OrgMassSpecR package. I run my HPLC using a DAD detector. My raw data is exported form chemstation as a csv file. I then upload the csv into Rstudio no problem. Using the DrawChromatogram function, I get a nice chromatogram, and my retention time, peak area, and apex intensity values are given as well. The problem comes with the peak area value given. The

HI I'm a student in chemical engineering, and i have to implement an algoritm about FIVE PARAMETERS INTERPOLATION for a calibration curve (dose, optical density) y = a + (c - a) /(1+ e[-b(x-m]) where x = ln(analyte dose + 1) y = the optical absorbance data a = the curves top asymptote b = the slope of the curve c = the curves bottom asymptote m = the curve X intercept Have you never seen

> Can you file a bug with some example outputs that are unrelated to the search string? Here is the example (see attachment). This example does the following: 1)First, it indexes text from the "text.txt" file (see attachment) (actually, this is the text of the following book: "Abbas, Lichtman. Basic immunology"). 2)Next, it searches for the "extracellular

I have 11 vectors representing insect survival probabilities in response to different levels of toxins at 10 concentrations lx100=c(1,1,1,.8,.5,.4,.2,0) day100=c(0,1,2,3,4,5,6,7,8) lx90=c(1,1,1,1,.9,.8,.6,.4,.2,.1,0) day90=c(0,1,2,3,4,5,6,7,8,9,10) #...and so on10% and a zero (control) series lx0=c(1,1,1,1,1,1,.9,.9,.8,.8,.6,.5,.4,.3,.2,.1,.1,0)

To those who have reported having a problem selecting real number quality settings, could you kindly test the new compile you can d/l from: http://homepage.ntlworld.com/jfe1205/testXPd.ZIP and report whether this resolves the problem. No major changes, but I regularised a number of type casting discrepancies that could have been causing a problem. I'm sorry to have to ask for help on this

I have a series of numbers I'm wanting to plot. They come from a nanodrop machine, which graphs with a specific x and y indices. X goes from 220nm to 350nm, which I can set. But the y axis should go from -5 to 65, but I'm finding it impossible to hardcode that. I've looked. I've typed ?plot at the R prompt. Google has not been my friend. _R Graphics_, if it holds the key, has not

http://r.789695.n4.nabble.com/file/n3312061/x_and_y_values.txt x_and_y_values.txt I have the absorbance values form HPLC Chromatogram. I need to find the peaks in datapoints and area under each peak. I am not sure how how to find the peaks, I tried couple of libraries and peak function but they return me a list of values which when computed from area turns out to be huge nnumbers. In the

Hi, Being a novice to R, I would like to create a graph in R with 2 axes. One of the 2 only has positive values, the other one also has negative values. The part I'm struggling with is how to align the 2. Rather than starting to plot the data from the x axis, I would like to start plotting the positive values on the right axis only as of the 0 value on the left axis. Using a simple example

Hi, We are rebasing our audio compression subsystem using OPUS rather than SPEEX. The platform is Android but this piece is written in C code: we need to support armv5/armv7/x86 architectures.... and we use the released opus-1.1beta package from here<http://downloads.xiph.org/releases/opus/opus-1.1-beta.tar.gz>. A lot of our OPUS build system + code to drive the audio compression has been