search for: time4

Displaying 16 results from an estimated 16 matches for "time4".

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2007 Jan 19
4
Newbie question: Statistical functions (e.g., mean, sd) in a "transform" statement?
Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to total...
2010 May 20
1
Strange behaviour when using diff with POSIXt and POSIXlt objects
...ot;%Y %m %d %H %M") > > diff(c(time1,time2),units="mins") Time difference of 10 mins .. I get the correct response in minutes. But if I try the same thing with different values, say.. > time3=strptime("2009 06 01 00 47 00",format="%Y %m %d %H %M") > time4=strptime("2009 06 01 00 57 00",format="%Y %m %d %H %M") > > diff(c(time3,time4)) Time difference of NA secs ...which is not what I´m looking for. The difference should also be 10 minutes. I burned a few neurons (and searched the documentation) and I cannot figure why thi...
2012 Nov 30
1
help on "stacking" matrices up
Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2 <-matrix(c((0*INTERVAL):(7*INTERVAL))) TIME1 <-matrix(c((0*INTERVAL):(8*INTERVAL))) CDURINF1 <-((Dose/Tinf)*(1/(0.088*76.9)))*(1-exp(-0.088*TIME1)) CAFTINF1 <-((Dose/Tinf)*(1/(0.088*76.9)))*(...
2004 Jul 04
2
Random intercept model with time-dependent covariates, results different from SAS
Dear list-members I am new to R and a statistics beginner. I really like the ease with which I can extract and manipulate data in R, and would like to use it primarily. I've been learning by checking analyses that have already been run in SAS. In an experiment with Y being a response variable, and group a 2-level between-subject factor, and time a 5-level within-subject factor. 2
2002 Aug 10
0
lme output
...me + group:time, random=~1|subject, na.action=na.omit, data=mydata) ...for a dataset where there are two groups being followed over time. pre is before the treatment, and there are 4 post-treatment times (unequally spaced). The fitted coefficients are: (Intercept) pre group2 time2 time3 time4 group2:time2 group2:time3 group2:time4 2.6442 0.5478 1.0183 0.6085 0.2326 0.5059 -1.9177 -0.3500 -2.2029 of which there are only significant p-values (<0.05) for (Intercept), pre, group2:time2 and group2:time4. anova(fit) gives: numDF denDF F-value p-value (Inte...
2005 Nov 15
1
Repeates Measures MANOVA for Time*Treatment Interactions
...htly different mind-set behind their experiments than, say, an ecologist, who is interested in the effects of time per se, and not just the effects of a treatment. For example, here's my dataset, say, looking at plant height in cm with and without fertilizer Treatment, Time1, Time2, Time3, Time4, Time5 Fertilizer, 1, 4, 8, 10, 12 Control,1,2,3,4,5 Fertilizer,1,8,10,12,20 Control,1,3,5,6,6 Fertilizer,2,5,10,20,25 Control,1,2,4,4,4 Clearly there is a time*treatment interaction (just eyeballing the dataset) My question is, how does one set this up using the anova.mlm approach so that in...
2011 Aug 17
1
contrast package with interactions in gls model
...-9.38703 23.74893 -0.395261 0.6935 LugarChixchulub -0.15377 19.60260 -0.007845 0.9938 Lugar Hobonil -173.21354 15.89736 -10.895741 0.0000 Time2 -14.74999 14.55909 -1.013112 0.3135 Time3 14.42177 15.64594 0.921758 0.3589 Time4 14.77803 16.72367 0.883659 0.3790 Tra0:Time2 17.93859 20.78257 0.863156 0.3901 Tra0:Time3 -48.77118 22.17628 -2.199250 0.0302 Tra0:Time4 -52.63611 23.20192 -2.268610 0.0254 Tra0:LugarChixchulub 74.43956 28.11275 2.647893 0.00...
2005 Aug 10
2
Treatment-response analysis along time
...ith some of my data. I have a very typical analysis in biology, however it is difficult for me to find the right way to analyse. I had a group of animals, I gave them a treatment, and I measure a variable along time -one??s per day- along 5 days,for example(fake data): Animals Time1 Time2 Time3 Time4 1 1 5 3 1 2 2 7 4 1 3 5 5 3 1 4 1 3 7 2 5 2 7 7 1 Please, notice that all the animals get the same treatment, and there are no cont...
2012 Mar 28
3
Connect lines in a dot plot on a subject-by-subject basis
...are not drawn on a subject-by-subject basis, (2) not all lines are drawn. I hope someone can help me fix my code Thanks, John # Create a matrix to hold our data. mydata <- matrix(nrow=10,ncol=10) dimnames(mydata) <- list(NULL,c("time1", "time2", "time3", "time4", "time5", "clot1", "clot2", "clot3", "clot4", "clot5")) # load data into the matrix. # The first five columns represent time of measurement # Columns 6-10 have the measured values. mydata[1,]=c( 1, 3,...
2010 Jun 01
0
selecting monotone pattern of missing data from a dataframe with mixed pattern of missingness
Dear R- User,   I have a dataset that looks like the following:   jh<-data.frame(  'id'=seq(1,10,1),   'time0'=c(8,5,8,8,9,NA,NA,2,4,5),   'time4'=c(NA,NA,9,8,NA,2,3,2,4,5),  'time8'=c(NA,2,8,NA,5,NA,2,3,NA,4),  'time12'=c(NA,2,NA,NA,NA,3,3,2,3,NA),   'sex'=c('m','f','m','m','f','f','f','m','f','m'),   'trt'=c('P','...
2011 May 01
1
Mean/SD of Each Position in Table
...h have the basic format: > test X Substance1 Substance2 Substance3 Substance4 Substance5 1 Time1 10 0 0 0 0 2 Time2 9 5 0 0 0 3 Time3 8 10 1 0 0 4 Time4 7 20 2 1 0 5 Time5 6 25 3 2 1 6 Time6 5 30 4 2 2 7 Time7 4 25 5 3 3 8 Time8 3 20 6...
2007 May 13
2
Some questions on repeated measures (M)ANOVA & mixed models with lme4
...amp; Li, 2006), something along the lines of: aov(outcome ~ group * time + baseline + Error(subj+subj:time)) (from: http://cran.r-project.org/doc/contrib/Baron-rpsych.pdf, p. 41) C. "Repeated measures" MANOVA as follows (using data in wide format): response <- cbind(time1,time2,time3,time4,time5,time6) mlmfit <- lm(response ~ group) mlmfit1 <- lm(response ~ 1) mlmfit0 <- lm(response ~ 0) # Test time*group effect anova.mlm(mlmfit, mlmfit1, X=~1, test="Spherical") # Test overall group effect anova.mlm(mlmfit, mlmfit1, M=~1) # Test overall time effect anova.mlm(mlmfit...
2008 Oct 29
2
call works with gee and yags, but not geepack
...str="exch",data=dat) I obtain the following error: Error in geese.fit(x, y, id, offset, soffset, w, waves, zsca, zcor, corp, : nrow(zsca) and length(y) not match Could someone tell me what I have done incorrectly. Thanks for your time, Juliet. Data Below: id treat time1 time2 time3 time4 chem1 chem2 chem3 chem4 time score chem 1 1 20 18 15 15 1000 1100 1200 1300 0 20 1000 1 1 20 18 15 15 1000 1100 1200 1300 2 18 1100 1 1 20 18 15 15 1000 1100 1200 1300 3 15 1200 1 1 20 18 15 15 1000 1100 1200 1300 6 15 1300 2 1 22 24 18 22 1000 1000 1055 950 0 22 1000 2 1 22 24 18 22 1000 1000 1055...
1999 Mar 09
2
summary() of lm() problem (PR#135)
...fus", "drugs", "retained.pl", "baby.no", "weight", "apgar1", "apgar5", "scbu", "ph.ven", "be.ven", "dilat1", "time2", "dilat2", "time3", "dilat3", "time4", "dilat4", "time5", "dilat5", "time6", "dilat6", "time7", "dilat7", "srom.time", "srom.dilat", "epi.time", "epi.dilat"))) *********************************************************...
2011 Aug 10
5
anova medidas repetidas con lme
Hola compañeros de la lista. Tengo el siguiente set de datos: Repeticiones <- c(rep("RI", 14), rep("RII", 14), rep("RIII", 14)) Tiempo <- rep(c(0, 2, 4, 6, 8, 10, 12, 24, 36, 48, 60, 72, 96, 120), 3) Concentracion_celular <- c(0.4862, 0.5375, 0.4309, 0.4390, 0.4603, 0.4733, 0.3936, 0.9085, 0.5838, 0.5477, 0.6331, 0.8693, 1.0092, 0.6341, 0.5350,
2006 Oct 11
9
time synchronization problem (using NTP)
Hi, using SLES10 I''m unable to synchronize the time of DomU with that of Dom0. There is a persistent offset of about 3 seconds! Here''s a small history (not actual output): remote refid st t when poll reach delay offset jitter rkdvmso1.dvm.kl 192.168.0.11 5 u - 64 1 0.136 -2977.1 0.099 *rkdvmso1.dvm.kl 192.168.0.11 5 u 2 64