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05-08-2017 11:32 AM - edited 05-08-2017 01:13 PM

I've seen similar posts but I am trying to determine if there is a simpler method for this:

1. Create log10 transformed values of x

2. Process through PROC MEANS to obtain mean, sd, median, min max

3. Raise each of the quantities in (2) to 10**(mean), etc. to get "mean", "SD", "min", and "max" values

4. Calculate dispersion factors

-All quantities based on output from Means procedure in step 2

dfplus=(**10****mean)+(**10****(mean+sd)-**10****(mean));

dfminus=(**10****mean)-(**10****(mean)-**10****(mean-sd));

Since I need to calculate grand mean, sd, min, max, dfplus, and dfminus by anaysis category, is there a way I can reduce the number of steps?

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05-08-2017 01:05 PM

I don't understand what your question has to do with the title of this post, "Factor analysis using maximum likelihood estimation."

What are you trying to accomplish? What variables are you using in the factor analysis?

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05-08-2017 01:06 PM

I chose the incorrect select - can I edit the post so it will show up in the correct location?

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05-08-2017 01:09 PM

Sure. You are welcome to edit the post title, add details, clarify your questions, and so forth.

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05-09-2017 09:42 AM

Here could get you many statistical estimators .

```
data class;
set sashelp.class;
log_height=log(height);
run;
proc univariate data=class outtable=want noprint;
var log_height;
run;
```