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xxformat_com
Barite | Level 11

Hi,

 

When computing confidence interval (CLM), proc means seems to use

- the Student table for small values of n (eg. n=44 > 2,0167 for a 95%CI)

- the Normal table for large values of n (eg. n=4400 > 1,96 for a 95%CI)

 

Do you have references in the SAS online doc which would indicate which table is used depending on which value of n for CLM, LCLM and UCLM?

 

Best Regards,

 

 

1 ACCEPTED SOLUTION
8 REPLIES 8
WarrenKuhfeld
Rhodochrosite | Level 12

p values are not looked up in tables. SAS has software to compute p values for a bunch of distributions given a particular set of parameters. Normal and t are not much different for large n.

xxformat_com
Barite | Level 11

Thanks. But I'm looking for the computation method used by the system.

Of course, table is just the manual way of accessing to the information. I guess I should have make it clearer using distribution used.

But my point is: which one is selected based on which criteria by the system and where it is documented.

PaigeMiller
Diamond | Level 26

@xxformat_com wrote:

 

When computing confidence interval (CLM), proc means seems to use

- the Student table for small values of n (eg. n=44 > 2,0167 for a 95%CI)

- the Normal table for large values of n (eg. n=4400 > 1,96 for a 95%CI)


The t-table value for 4399 df is, to 2 decimal places, the exact same value as the normal distribution.

--
Paige Miller
xxformat_com
Barite | Level 11

Hi,

Thanks but my question is not to compare the student distribution with the normal distribution for large df. My question is where is specified in the SAS online documentation which tables are programmed internally in the system.

WarrenKuhfeld
Rhodochrosite | Level 12

As I said, there are no internal tables to document.  Mathematical programming statements generate the results.

xxformat_com
Barite | Level 11

As as said, my point is not whether it is a table or a formula. My point is to find the definition used internally.

xxformat_com
Barite | Level 11

Thank you. That's exactly what I was looking for 🙂

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