Databases
StackOverflow2013
Postsdbo
PO
 

Note that there are some explanatory texts on larger screens.

plurals
  1. PO
    primarykey
    data
    text
    <p>Oooh, this is going to be a tricky one, and if it's even possible using standard nlme functions, is going to take some serious study of Pinheiro/Bates.</p> <p>Before you spend the time doing that though, you should make absolutely sure that this is exact model you need. Perhaps there's something else that might fit the story of your data better. Or maybe there's something R can do more easily that is just as good, but not quite the same.</p> <p>First, here's my take on what you're doing in SAS with this line:</p> <pre><code>repeated / type=cs subject=person group=GROUP; </code></pre> <p>This <code>type=cs subject=person</code> is inducing correlation between all the measurements on the same person, and that correlation is the same for all pairs of days. The <code>group=GROUP</code> is allowing the correlation for each group to be different.</p> <p>In contrast, here's my take on what your R code is doing:</p> <pre><code>random = ~ +1 | person, correlation=corCompSymm(form=~day|person) </code></pre> <p>This code is actually adding almost the same effect in two different ways; the <code>random</code> line is adding a random effect for each person, and the <code>correlation</code> line is inducing correlation between all the measurements on the same person. However, these two things are almost identical; if the correlation is positive, you get the exact same result by including either of them. I'm not sure what happens when you include both, but I do know that only one is necessary. Regardless, this code has the same correlation for all individuals, it's not allowing each group to have their own correlation.</p> <p>To let each group have their own correlation, I think you have to build a more complicated correlation structure up out of two different pieces; I've never done this but I'm pretty sure I remember Pinheiro/Bates doing it.</p> <p>You might consider instead adding a random effect for person and then letting the variance be different for the different groups with <code>weights=varIdent(form=~1|group)</code> (from memory, check my syntax, please). This won't quite be the same but tells a similar story. The story in SAS is that the measurements on some individuals are more correlated than the measurements on other individuals. Thinking about what that means, the measurements for individuals with higher correlation will be closer together than the measurements for individuals with lower correlation. In contrast, the story in R is that the variability of measurements within individuals varies; thinking about that, measurements with higher variability with have lower correlation. So they do tell similar stories, but come at it from opposite sides.</p> <p>It is even possible (but I would be surprised) that these two models end up being different parameterizations of the same thing. My intuition is that the overall measurement variability will be different in some way. But even if they aren't the same thing, it would be worth writing out the parameterizations just to be sure you understand them and to make sure that they are appropriately describing the story of your data.</p>
    singulars
    1. This table or related slice is empty.
    1. POConverting Repeated Measures mixed model formula from SAS to R
      singulars
      1. PTQuestion
    1. PTAnswer
    1. This table or related slice is empty.
    1. USAaron
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    1. COA final thought though, changing the the correlation structure usually doesn't affect the estimates of the fixed effects, so if that's what's different, there may be something else going too.
      singulars
      1. PO
      1. USAaron
    2. COYour answer sounds reasonable to me, but I really think we need to hear/see more from the OP about what the output of each program looks like (I have access to SAS, but not conveniently) and where the key differences are ...
      singulars
      1. PO
      1. USBen Bolker
    3. COThanks, @BenBolker. I haven't tried running the OP's code either; I have access to SAS but not conveniently from home.
      singulars
      1. PO
      1. USAaron
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload