search for: measurable

I have a table that looks like this: measurement?? ?date??? door ?? color 0.93529385?? ?513?? ?open?? ?red 0.97419293?? ?420??? open ?? red 0.962053514?? ?513?? ?closed?? ?red 0.963909937?? ?1230?? ?open?? ?blue 0.97652034?? ?1230?? ?open?? ?green 0.989310795?? ?1230?? ?closed?? ?blue 0.9941022?? ?917?? ?closed?? ?yellow I would like to create a table that has: Open measurement, Closed

Hello, I have two series, one with stream stage measurements every 5 minutes, and the other with barometric pressure measurements every hour. I want to subtract each barometric pressure measurement from the 12 stage measurements closest in time to it (6 stage measurements on either side of the hour). I want to do something like the following, but I don't know the syntax. "If the

I have a new device that takes measurements anywhere from every second, to every 15 minutes (depending on changes). The matrix has a date, time and Y column (Y is the measurement). For three days it is 25,000 rows. How do I average the measurements by every 30 minutes so my matrix is 48 rows per day? I have been working on this and cannot figure out a simple method. Any ideas? Thank you. ----- In

Hello, I have some measurements that I am trying to fit a model to. I also have uncertainties for these measurements. Some of the measurements are not well detected, so I'd like to use a limit instead of the actual measurement. (I am always dealing with upper limits, i.e. left censored data.) I have successfully run survreg using the combination of well detected measurements and limits,

R-helpers: I would like to measure the correlation coefficient between the repeated measures of a single variable that is measured over time and is unbalanced. As an example, consider the Orthodont dataset from package nlme, where the model is: fit <- lmer(distance ~ age + (1 | Subject), data=Orthodont) I would like to measure the correlation b/t the variable "distance" at

If this has already been answered, my apologies in advance I am relatively new to this aspect of [R]. it is a bit of a basic question. I have 4 columns of data (site, Date, measurement type, value) in a tab delimited text file. Site is a site where measurements were collected, Date is a date in DD/MM/YYYY format, measurement is a code for the type of measurement made, and value just the value

Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The

I am familiar with pairwise t-tests, corrections for multiple testing, etc. however I have a problem whose answer I have not found after extensive R-help archive and Google searching. What I have done in the past: I have N items which are measured, exposed to a condition, and then measured again. I wish to know if the condition changes the items so I can perform a t-test. Better yet I can

Hi all, I have a data frame with some measured values of some animals. Sometimes the measurement failed, resulting in a NA for a measurement and sometimes the animal died, resulting in NA for all measurements. I have several groups of animals. How do I find the size of each group with only alive animals? And how do I find the size of the groups for each measurement? An example: l1 <-

Hi all, Say I have a data frame something like the one below with different sample vials, measured before(B) and after(A) some process, with a value recorded at each measurement point vial measure value 1 B 26 1 A 12 2 B 45 2 A 30 3 B 32 3 A 27 4 B

Dear R user, I have a question on using R to analyze data with repeated measurements. I have 2 species with several strains (12) per species, each of which has been measured twice with for a given trait. No particular covariance, just two measures. Now I want to analyze the data with an ANOVA (aov) considering these repeated measures to get the MSq and SSq for the species and strain level. I

R 2.6.0 Windows XP At the risk of raising the ire of the R gods . . . I am looking for a package that will allow me to perform a poisson, quasipoisson, or negative binomial regression with adjustment for repeated measures. I have looked at glm, it does not appear to allow repeated measures. Although I can't get any help for lme or lme4 I remember that those packages perform repeated measures

I am using lme to handle repeated measurements. So far i can follow the examples from the book from pinheiro and bates. Now i get the problem , that i have "nested" repeated measuremnts, and i cant find out how to do the grouping part of the lme formula. 1.The simple problem ist that i have different Samples , from which i make repeated measurements (each sample is measured 6 times) and

Hi, I am a graduate student at Stanford University and I have a general statistics question. What exactly is the difference between doing a two-factor repeated measures ANOVA and a Hotelling T-squared test for a paired comparison of mean vectors? Given: Anova: repeated measures on both factors, 1st factor = two different treatments, 2nd factor = 4 time points, where you are measuring the blood

Hello, I have a loop with 1000 repetitions which includes OR computation of an exposure factor and outcome. I compute OR like this: t<-table(exposure,outcome) oddsratio(t)$measure["estimate"] This gives me the estimates for exposure=0 and exposure=1 but exposure=0 is the reference group and i need only the estimate for exposure=1. I specified a matrix OR with 3 columns (for OR

Hello All, I have a more statistical question, and how this is implemented in R. The problem is the following: We have 2 different solutions (samples), which are filtered and then the concentration of the filtrate is measured. We want to evaluate how the filter proces and the concentration measurement influences the detection of the difference of the two solutions and which step has which

Hello, I've got a matrix (mail end) with the colnames x, y, z. In this matrix are different measurements. x and y are risign coordinates. With the following line I got the median value of z for all "x" AND "y" witch are the same (not every measurment in my list hast the same number of "x" and "y" values. Sometimes lines are missing. >MEDIAN <-

Dear All I have one centos server equipped with WiFi . I want to measure data rate speed on this connection . Is there any utility on my centos that can measure data speed on one specific Ethernet connection when transferring large size files through WiFi connection? Thank you -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hello Listserve, Here is another question to keep you on your toes. Please consider the following toy dataset: a <- read.table(textConnection("fred sam joe alex measure.1 10 4 10 1 measure.2 10 4 2 8 measure.3 3 1 8 3 measure.4 5 1 3 3 measure.5 8 6 8 3 measure.6 9 5 1 0 measure.7 4 6 10 1 measure.8 3 6 8 9 measure.9 8 6 7 7 measure.10 7 8 9 8"), header = TRUE) And also please

I would be grateful if members of the list could point me in the direction of any code (preferably in R) that will allow me to estimate 95th percentiles from a set of repeated measurements. For example, we are interested in a clinical measurement where we have 3 measures for 14 subjects and 2 measurements on 24 subjects and single measurement on 36 subjects. We want to combine these to form a