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Posted 09-06-2019 01:56 PM
(5017 views)

Hi, so I run a Fisher's exact test, and it shows me that the table probability is <0.0001, but doesn't show any other p-values like the one-sided or two-sided p-values

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Your answer is in the WARNING.

WARNING: There is not enough memory available to compute Fisher's exact test.

The suggestion would be to either use the asymptotic test or get a Monte-Carlo estimate of the exact p-value by adding the MC option to the EXACT statement.

PROC FREQ DATA=first;

TABLES cut*Oxarma;

EXACT FISHER/MC:

RUN:

8 REPLIES 8

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Show your code and log.

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PROC FORMAT; value $Oxarma '1' = 'None' '2' = 'Trace' '3' = 'Some' '4' = 'Unacceptable'; value $Oxarmab '1' = 'None/Trace' '2' = 'None/Trace' '3' = 'Some' '4' = 'Unacceptable'; value $Oxarmac '1' = 'Acceptable' '2' = 'Acceptable' '3' = 'Acceptable' '4' = 'Unacceptable'; Run; PROC FREQ data=first; tables day*Oxarma / FISHER; format Oxarma $Oxarma.; Run; Quit;

Log:

PROC FREQ data=first;

946 tables cut*Oxarma / FISHER;

947 format Oxarma $Oxarma.;

948 Run;NOTE: Writing HTML Body file: sashtml.htm

WARNING: Computing exact p-values for this problem may require much time and memory. Press the

system interrupt key to terminate exact computations.

WARNING: There is not enough memory available to compute Fisher's exact test.

NOTE: There were 913 observations read from the data set WORK.FIRST.

NOTE: PROCEDURE FREQ used (Total process time):

real time 5:32.70

cpu time 5:28.39

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Your answer is in the WARNING.

WARNING: There is not enough memory available to compute Fisher's exact test.

The suggestion would be to either use the asymptotic test or get a Monte-Carlo estimate of the exact p-value by adding the MC option to the EXACT statement.

PROC FREQ DATA=first;

TABLES cut*Oxarma;

EXACT FISHER/MC:

RUN:

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Monte Carlo Estimate for the Exact Test

Pr <= P 0.9481

99% Lower Conf Limit 0.9424

99% Upper Conf Limit 0.9538

Number of Samples 10000

Initial Seed 358024000

This is the data I get. How reliable is this Monte Carlo estimate? This suggests that the two variables are independent and that the treatment does not affect the outcome, does it not?

Pr <= P 0.9481

99% Lower Conf Limit 0.9424

99% Upper Conf Limit 0.9538

Number of Samples 10000

Initial Seed 358024000

This is the data I get. How reliable is this Monte Carlo estimate? This suggests that the two variables are independent and that the treatment does not affect the outcome, does it not?

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The MC estimate is very reliable. Interpretation in terms of treatment and outcome is left to the researcher. Only he/she knows the details of the data. For instance, why so many data are missing...

PG

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I see, thank you. I achieved significance for other variable measured. Missing data is due to having sensory panelists that did not participate in every session.

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You should mark SAS_rob's answer as correct, not your own. He provided you the workaround to get your problem solved.

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Yes, that's what I meant to do, thank you for bringing that to my attention.

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