Nathanael, On 31 Mar 2008, at 14:37, nathan3073 wrote:
> > It is a reaction time experiment. My program will display 25 circles, > arranged in a 5x5 square. The program will light one circle at a > time, which > the subject should click ASAP. The time interval between two > lighting is > 1.5s. If the subject fails to click in approriate time, the data > will be > considered missing. > > The one I want to explore is the relationship between intellegence > and the > ability to recognize visual stimuli regularity. I arrange the > experiment so > there will be 4 repeated pattern. At last, after all pattern have been > displayed, my program will light the circle randomly. > > I want to check the time series plots, in order to clarify my > hypothesis > that the 'smart' and the 'average' deal with stimuli in a different > way. For > example, because of 'smart' people is known to be able to recognize > regularity faster, we may expect their plot to decline quite > rapidly. But, > because of their automation, we may also expect that they will find > some > difficulties to adapt when the pattern has changed. The adaptation > difficulty may be represented (hopefully) by an increasing reaction > time. How important is the time series aspect here? Why not just do some anova on the difference between these blocks of trials? If the time information is essential, repeated measures anova could be applied. > I think to check every subject's plot, and determine their ARIMA > (p,d,q) > model. Then, if they all follow same ARIMA model, obviously my > hypothesis is > wrong, and I may conclude that there are no differences in the way > subject > deal with stimuli. But, if let's say 20 subject follow ARIMA(1,0,1) > and the > others follow ARIMA(0,0,2) I can say that there are differences in the > subject's cognitive ability for dealing with stimuli. For now, I > set aside > what the differences is and its psychological explanation. This sounds like you need a mixture of ARIMA models. Is that indeed the hypothesis that you want to test: whether there are different strategies that result in either an AR learning process or in an MA learning process? > The problem is, it will be very frustating to have 200 subjects and Who said doing research was going to be fun (-; > determine approriate ARIMA model for each plot. So, there're only 2 > ways > left. One, I reduce the number of subjects to manageable quantity, > let's say > 30 subjects. Or two, I know method(s) that make me possible to analyze > multiple time series plot, and say whether they follow same or > different > model. Using a mixture of ARIMA models would allow you to analyze these data simultaneously. hth, Ingmar > Thank you, > regards, > Nathanael > > PS: please forgive grammatical error > > > Prof Brian Ripley wrote: >> >> Surely you need the insight before choosing a package? >> >> What is the problem you are trying to solve? There are many >> different >> aspects of time series which could be of interest, and we have no >> idea >> which are relevant to your problem. >> >> On Sun, 30 Mar 2008, nathan3073 wrote: >> >>> >>> Dear All, >>> I need to compare hundreds (about 200-300) of time series. Would >>> anyone >>> tell >>> me how to do this in R? If R has no package for doing this, can I >>> get >>> some >>> insight what method I should use? >>> >>> best regards, >>> Nathanael Gratias >>> -- >>> View this message in context: >>> http://www.nabble.com/Comparing-Time-Series-tp16392632p16392632.html >>> Sent from the R help mailing list archive at Nabble.com. >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> >> -- >> Brian D. Ripley, [EMAIL PROTECTED] >> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ >> University of Oxford, Tel: +44 1865 272861 (self) >> 1 South Parks Road, +44 1865 272866 (PA) >> Oxford OX1 3TG, UK Fax: +44 1865 272595 >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> > > -- > View this message in context: http://www.nabble.com/Comparing-Time- > Series-tp16392632p16396039.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. Ingmar Visser Department of Psychology, University of Amsterdam Roetersstraat 15 1018 WB Amsterdam The Netherlands t: +31-20-5256723 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
