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- JMP Equivalent to SAS MODEL events/trials?

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Mar 18, 2016 7:51 PM
(1518 views)

I have data that looks like this:

Reporting Fraction = A/AB

I would like to model the Reporting Fraction as a function of Period, but use the A and AB columns. In SAS the LOGISTIC procedure supports the following form:

*<label:>* MODEL events/trials=<effects></ options> ;

In the *events/trials* syntax, you specify two variables that contain count data for a binomial experiment. These two variables are separated by a slash. The value of the first variable, *events*, is the number of positive responses (or events). The value of the second variable, *trials*, is the number of trials. The values of both *events* and (*trials–events*) must be nonnegative and the value of *trials* must be positive for the response to be valid.

Is there something equivalent in JMP's generalized regression platform? My A column represents events, and AB represents trials.

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Mar 21, 2016 1:54 AM
(2806 views)

Solution

According to:

http://www.jmp.com/support/help/Distribution_Option_in_Generalized_Regression.shtml

*Y has a binomial distribution with parameters p and n. The response, Y, indicates the total number of successes in n independent trials with a fixed probability, p, for all trials. This distribution allows for the use of a sample size column. If no column is listed, it is assumed that the sample size is one. The link function for p is the logit. When you select Binomial as the Distribution, the response variable must be specified in one of the following ways:*

*(Method 3):*

*Summarized with sample size column entered as second Y: If your data are summarized as frequencies of events (successes) and trials, specify two continuous columns as Y in this order: the count of the number of successes, and the count of the number of trials.*

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Mar 21, 2016 1:54 AM
(2807 views)

According to:

http://www.jmp.com/support/help/Distribution_Option_in_Generalized_Regression.shtml

*Y has a binomial distribution with parameters p and n. The response, Y, indicates the total number of successes in n independent trials with a fixed probability, p, for all trials. This distribution allows for the use of a sample size column. If no column is listed, it is assumed that the sample size is one. The link function for p is the logit. When you select Binomial as the Distribution, the response variable must be specified in one of the following ways:*

*(Method 3):*

*Summarized with sample size column entered as second Y: If your data are summarized as frequencies of events (successes) and trials, specify two continuous columns as Y in this order: the count of the number of successes, and the count of the number of trials.*

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Mar 22, 2016 5:06 AM
(1403 views)