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Re: st: Can you confirm these Stata limitations?


From   Jorge Eduardo Pérez Pérez <perez.jorge@ur.edu.co>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Can you confirm these Stata limitations?
Date   Tue, 7 Sep 2010 10:13:34 -0400

1. Not true

set obs 100
forv i=1(1)100 {
gen x`i'=uniform()
}
gen id=round(_n/10)
collapse x*, by(id)

2. See -cond-


_______________________
Jorge Eduardo Pérez Pérez




On Sun, Sep 5, 2010 at 2:26 PM, Pietro Mazzoni <pm125@columbia.edu> wrote:
> Hello everyone,
>
> It's my first time writing to this list, which is a very helpful forum. I can use some help in clarifying certain features of Stata that seem to be limitations, at least in the style of analysis I would like to implement. I am deciding whether to have my whole lab switch from JMP to Stata for our data analysis due to the high cost of JMP. I will avoid the debate about virtues and faults of an interactive, GUI-based program like JMP. I see the value and power of Stata's approach, and cost considerations may be forcing us to switch regardless. But the following limitations are making it difficult to convince my postdocs (and, frankly, me), that using Stata will not, even after a transition period, take orders of magnitude more time for visualization of our data. I apologize if these questions are elementary. I read through "A Gentle Introduction to Stata" and searched the Web, but could not find these answers.
>
> I am using Stata 10 for Mac. The data is usually a table of movement variables (duration, peak velocity, etc) for each of several trials in motor control experiments. There are several trials per condition, several conditions per session, a few sessions per subject, and several subjects per group. We usually work with two main tables: the one just described (to look at trial-to-trial time course of variables within conditions) and a calculated table that has the mean values of all these variables for each condition.
>
> 1. A common step early in our analysis is to collapse single-trial data into mean values per condition. Is it indeed true that the collapse command can only handle 8 variables at a time? This means that instead of being able to create a single table with all the variables' means, I'd have to create multiple tables, 8 variables at a time, and then join them.
>
> 2. We often calculate derived variables based on a formula. However, the formula can differ slightly for different groups or conditions. Can a complex "if" statement be used at the end of a formula, or is there the equivalent of a "case..." command that could be part of a formula. For example:
>
> gen int outcome = [ 1 if (peakVel > 10 & condition == "easy"); 2 if (peakVel > 50 & condition == "difficult") ]
>
> 3. Is it true that there is no option for error bars in a continuous vs. categorical plot, i.e. it is necessary to convert the category into a numerical variable in order to plot error bars? I found the command serrbar, which removes some of the steps required in the usual workarounds (calculating error value is enough; high and low values are no longer explicitly needed), but it only works with a continuous-variable x axis. This is a minor inconvenience (the much more lamented inconvenience, for users of JMP, is not being able to have the graph show standard error on a mean plot without having to explicitly calculate it).
>
> 4. Is there any way to create a graph that shows individual values overlaid on top of mean values? For example, one that has the following two elements on a single graph, for variables vel, subj, group (one value of vel for each subj; several subj per group; several groups):
>
> a.  vel vs. group: individual values of vel (one value for each subject) as dots lined up as a vertical array above each condition
> b. group mean of vel vs. group: mean values of vel, across each group, indicated by a bar or a thick orizontal marker, aligned with the vertical array of dots above each condition.
>
> This graph is of common use for our data: it allows us to see mean values of a variable for a group while at the same time seeing how that mean arises from individual subject values.
>
> 5. The time it takes for Stata 10 to generate a graph on a Mac, even on a late-model machine, is inordinately slow (several seconds) and grows quickly (to tens of seconds) with the number of elements that are added to the graph. Does anyone know if Stata 11 is faster at drawing graphs on a Mac?
>
> Thank you in advance for any uelp or suggestions.
>
> Pietro
> -----------------------
> Pietro Mazzoni, MD PhD
> Associate Professor of Neurology
> Co-director, Motor Performance Laboratory
> Columbia University
> New York
>
>
>
>
>
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