2 ways to import count data but get different results from
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From: Arthur Tabachneck on 28 Dec 2009 20:36 Vivian, You didn't show your code, thus the best I can do is an educated guess. If I understand, correctly, you are analyzing rate/frequency data, aggregated at two different levels. My guess is that you didn't weight the analyses, by FTE, in one or both analyses. I would presume that, if you did, you would get the same results. Art ------- On Mon, 28 Dec 2009 14:28:52 -0800, Vivian Pun <vivianpun09(a)GMAIL.COM> wrote: >Hi SAS users, > > When I analyze the rate of injury by hospital teaching status. I >calculate the average injury rates by teaching status: > Rate Rate ratio > Teaching 26/1000 FTEs 26/18 = 1.44 > Non-teaching 18/1000 FTEs reference > > I have tried two ways (there could be more ways) to import the >injury count data into SAS. > OPTION 1: use SAS datalines option such as: > data data1; > input teaching count total_fte; > l_fte=log(total_fte); > datalines; > No 6041 332967.7441 > Yes 12778 490319.0468 > ; > run; > *This option is simple, but doesn't allow a more complicated >model multivariate testing. > > OPTION 2: use count dataset that include breakdown of all >variables, such as: > year quarter count total_fte teaching bedcat .... > 2002 3 23 2345 No >1 ..... > 2004 1 100 100322 Yes >2 ..... > *This option does allow a more complicated model multivariate >testing. > > When I fit the data from either OPTION into a Poisson model, an >crude univariate poisson regression model for the association between >injury rate and teaching status shows that the model rate ratio from >OPTION 1 is 1.44, model rate ratio from OPTION 2 is 1.33. I don't >understand why the crude model rate ratio for OPTION 2 isn't 1.44 like >the observed rate ratio or OPTION 1??? Any thoughts on this? Thank >you. > > >Vivian
From: Dale McLerran on 28 Dec 2009 20:40 Vivian, Please show the code which you employed to fit your Poisson models to the data for each of your two options. I presume that for option 1, your code was something like: proc genmod data=data1; class teaching; model count = teaching / offset=l_fte dist=poisson; run; Is that correct? Dale --------------------------------------- Dale McLerran Fred Hutchinson Cancer Research Center mailto: dmclerra(a)NO_SPAMfhcrc.org Ph: (206) 667-2926 Fax: (206) 667-5977 --------------------------------------- --- On Mon, 12/28/09, Vivian Pun <vivianpun09(a)GMAIL.COM> wrote: > From: Vivian Pun <vivianpun09(a)GMAIL.COM> > Subject: 2 ways to import count data but get different results from Poisson Regression > To: SAS-L(a)LISTSERV.UGA.EDU > Date: Monday, December 28, 2009, 2:28 PM > Hi SAS users, > > When I analyze the rate of injury by hospital teaching status. I > calculate the average injury rates by teaching status: > > Rate Rate ratio > Teaching 26/1000 FTEs 26/18 = 1.44 > Non-teaching 18/1000 FTEs reference > > I have tried two ways (there could be more ways) to import the > injury count data into SAS. > OPTION 1: use SAS datalines option such as: > > data data1; > input teaching count total_fte; > l_fte=log(total_fte); > datalines; > No 6041 332967.7441 > Yes 12778 490319.0468 > ; > > run; > *This option is simple, but doesn't allow a more complicated > model multivariate testing. > > OPTION 2: use count dataset that include breakdown of all > variables, such as: > > year quarter count total_fte teaching bedcat .... > > 2002 3 23 2345 No 1 ..... > 2004 1 100 100322 Yes 2 ..... > *This option does allow a more complicated model multivariate > testing. > > When I fit the data from either OPTION into a Poisson model, an > crude univariate poisson regression model for the association between > injury rate and teaching status shows that the model rate ratio from > OPTION 1 is 1.44, model rate ratio from OPTION 2 is 1.33. I don't > understand why the crude model rate ratio for OPTION 2 isn't 1.44 like > the observed rate ratio or OPTION 1??? Any thoughts on this? Thank > you. > > > Vivian >
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