Date: Sat, 18 Mar 2006 07:38:01 -0800 Reply-To: Dale McLerran Sender: "SAS(r) Discussion" From: Dale McLerran Subject: Re: Proc Mixed (of course) In-Reply-To: <200603171712.k2HGusKh016830@mailgw.cc.uga.edu> Content-Type: text/plain; charset=iso-8859-1 --- Wendy Buzy wrote: > I apologize for sending this question to the list, but I've read many > of > the previous posts regarding Proc Mixed and my poor, pea-sized brain > is > still struggling. I'm trained as a clinical psychologist and my > statistical knowledge is somewhat limited, although I'm trying my > best to > learn! > > I'm trying to analyze data from a task that subjects performed 6 > times -- > i.e., at 3 different levels of difficulty (Level) and at 2 different > interstimulus intervals (ISI) within each difficulty level. Thus, > each > subject performed the task at: > > * Level=1, ISI=3200 > * Level=1, ISI=2800 > * Level=2, ISI=3200 > * Level=2, ISI=2800 > * Level=3, ISI=3200 > * Level=3, ISI=2800 > > in that order, on the same day. Some subjects have missing data, > which is > why we're trying to use Proc Mixed rather than Proc GLM. > > There are two groups of subjects (ADHD vs. NC). > > So far, we've struggled with when/whether to use the RANDOM statement > versus the REPEATED statement, and also with which covariance > structure(s) > to use. We've come up with the following code: > > > proc sort data=usethis; by subject level descending isi; run; > proc mixed data=usethis order=DATA; > class group level isi subject; > model accuracy = group | level | isi; > repeated level isi / type=un@cs subject=subject; > run; > > > My questions are as follows: > > 1. Are we using the REPEATED statement correctly and/or should we be > using > the RANDOM statement (instead)? My guess is that you probably want both a RANDOM statement as well as the REPEATED statement. The question is whether the mean of the six responses varies from one individual to the next. If there are subject-specific means, then you need the RANDOM statement. But you may still need a REPEATED statement. > > 2. It seems that because there are only two levels of ISI, it doesn't > matter whether we specify "type=un@cs" or "type=un@ar(1)", etc. Is > that correct? That is correct. The two covariance structures are identical given that you have only 2 levels of ISI. > > 3. Is it appropriate to be using an unstructured covariance > structure? An unstructured covariance structure is never inappropriate, but it could be inefficient. > > 4. I would like to use intelligence (IQ) as a covariate. Is it > correct to > simply add IQ to the model statement (but not the class statement)? > Probably. I presume that the IQ measure is continuous. However, it is not necessarily the case that the relationship between the response and IQ is linear. If the relationship between the two is nonlinear, then naming IQ as a CLASS variable CAN be useful. Of course, another way to handle nonlinear relationships is to use polynomial terms. Dale --------------------------------------- Dale McLerran Fred Hutchinson Cancer Research Center mailto: dmclerra@NO_SPAMfhcrc.org Ph: (206) 667-2926 Fax: (206) 667-5977 --------------------------------------- __________________________________________________ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com

Back to: Top of message | Previous page | Main SAS-L page