```Date: Thu, 7 Jul 2005 14:51:13 -0400 Reply-To: Peter Flom Sender: "SAS(r) Discussion" From: Peter Flom Subject: Re: Modeling Yes/No variable Comments: To: Cody.Cook@ERIEINSURANCE.COM Content-Type: text/plain; charset=US-ASCII Thanks for this clarification Here, I see no reason to use other than the canonical (usual) link function......but I may be missing something Peter >>> "Cook, Cody" 7/7/2005 11:50:29 AM >>> Okay... I am trying to quantify the impacts of several policyholder characteristics on renewal ratios (renew with us or not?). I can do this by modeling the probability they will stay with us (0 means they didn't... 1 means they did). I have over 11 million observations... I have characteristics such as how long have they been with our company... geodemographic data... prior loss experience... etc. By understanding what has happened in the past, I hope to shed some light on the near future, given predicted x-combination outcomes. My brothers, a computer programmer and a high school math teacher, would probably each be asleep by now... or giving me lip about how boring my job is... but, given they paid attention, I believe they'd understand my objective at this point. Cody Cook -----Original Message----- From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of Peter Flom Sent: Thursday, July 07, 2005 11:43 AM To: SAS-L@LISTSERV.UGA.EDU Subject: Re: Modeling Yes/No variable >>> "Cook, Cody" 7/7/2005 11:35:18 AM >>> <<< Forgive me for my limited knowledge and the relatively vague e-mail. >>> Well, we all have limited knowledge. :-) <<< Yes/No is the answer to a given question... for example, lets say the class variable I am speaking of is State (which is one of several other descriptive variables within the analysis, for example, gender, salary, etc). We might expect a similar probability of a person saying yes from state-to-state, but we want to quantify the impact of the participant being from a particular state (say the countrywide probability is 90% say yes -- we might expect dummy variables for Alabama and New York tohave slightly different means -- we want to be able to quantify this difference, given our data). >>> Independent variables of this type can be handled in LOGISTIC and also in GENMOD. <<< I didn't use logistic because I have never used it... bad reason, I know, but I have only been using SAS for about a year. I tend to operate with procs that I am functional with... and only deviate when it is completely necessary to invest the time to switch. I am comfortable with learning LOGISTIC if you think this would be a better approach/procedure. >>> Nope, GENMOD should be fine, I just think LOGISTIC is easier, probably because it's what I am used to. <<< > what are the IVs? What is N? I believe you mean what is N in the dependent variable... which would beanswered above (yes/no to given question)... however, I'm not certain I follow... have I answered above? >>> By 'what is N' I meant what's the total sample size? But giving sensible answers to this sort of question always requires context. Explain what you are trying to do, as if you were explaining it to your brother who knows no statistics. <<< I apologize for the confusion of adding Poisson and Gamma to the discussion as they obviously are not distributions useful in this particular study and set of dependent variables. I spoke of them in reference to error distribution / link function combinations -- not as options for this particular analysis. Again, sorry for the confusion... >>>> Oh, OK. I think that's partly my fault.....maybe I didn't read your original post carefully enough Peter Peter L. Flom, PhD Assistant Director, Statistics and Data Analysis Core Center for Drug Use and HIV Research National Development and Research Institutes 71 W. 23rd St www.peterflom.com New York, NY 10010 (212) 845-4485 (voice) (917) 438-0894 (fax) ----------------------------------------- Disclaimer: This message (and any attachments) is confidential and is intended only for the addressee(s). This message may contain information that is protected by one or more legally recognized privileges. If the reader of this message is not the intended recipient, I did not intend to waive, and I do not waive, any legal privilege or the confidentiality of the message. If you receive this message in error, please notify me immediately by return e-mail and delete this message from your computer and network without saving it in any manner. The unauthorized use, dissemination, distribution, or reproduction of this message, including attachments, is prohibited and may be unlawful. ```

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