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Date:         Thu, 2 Jul 2009 22:38:59 -0300
Reply-To:     Hector Maletta <hmaletta@fibertel.com.ar>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Hector Maletta <hmaletta@fibertel.com.ar>
Subject:      Re: percent increase vs regression line as a predictor
Comments: To: "Pirritano, Matthew" <MPirritano@ochca.com>
In-Reply-To:  <97D6F0A82A6E894DAF44B9F575305CC9093D4ADF@HCAMAIL03.ochca.com>
Content-Type: multipart/alternative;

Then my second paragraph applies: the crude average past percentage rate of growth is usually a poor predictor, except if you have some objective grounds to expect a constant rate of growth.

Why the number of prescriptions per month should be an increasing (or decreasing) function of time? Time starting when? Are you talking of time counted since some condition is diagnosed, or something similar, or the mere passing of time? If time is the only predictor for the NUMBER of prescriptions, the PERCENTAGE GROWTH of prescriptions has little to do with it. If the number of prescriptions is a function of time, then the proportional increase in the number of prescriptions would be (by definition) a function of the logarithm of time.

Hector

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From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Pirritano, Matthew Sent: 02 July 2009 20:25 To: SPSSX-L@LISTSERV.UGA.EDU Subject: Re: percent increase vs regression line as a predictor

The variables are not dichotomous in this case. I'm looking at number of prescriptions per month. Number of prescriptions is the DV and time is the IV.

Matthew Pirritano, Ph.D.

Research Analyst IV

Medical Services Initiative (MSI)

Orange County Health Care Agency

(714) 568-5648

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From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Hector Maletta Sent: Thursday, July 02, 2009 3:17 PM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Re: percent increase vs regression line as a predictor

For a pair of dichotomous variables, the percent difference in Y between the two values of X is mathematically equivalent to a regression coefficient.

Average crude percentage change in the past (independently of predictors) may be a very poor forecasting tool. To mention just a famous example, remember the (in)famous Fisher blunder in 1929, predicting continuous growth in the stock exchange by simply projecting average past increases, even after the initial crash. The future does not always repeat the past.

Hector

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From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Pirritano, Matthew Sent: 02 July 2009 17:44 To: SPSSX-L@LISTSERV.UGA.EDU Subject: percent increase vs regression line as a predictor

Pawsers,

Stats question. I've not done any forecasting before other than with multiple regression analyses. What is the difference between multiple regression and using average past percent change to make predictions? Based on one scenario I'm dealing with it looks like percent change results in a positive curvilinear (possibly logistic?) relationship.

Thanks,

matt

Matthew Pirritano, Ph.D.

Research Analyst IV

Medical Services Initiative (MSI)

Orange County Health Care Agency

(714) 568-5648


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