```Date: Mon, 23 Jan 2006 16:19:08 -0600 Reply-To: Jiann-Shiun Huang Sender: "SAS(r) Discussion" From: Jiann-Shiun Huang Subject: SV: Re: help with SAS programming Comments: To: antoniababe@YAHOO.SE Content-Type: text/plain; charset=US-ASCII Yen: There got to be some limits on the number of independent variables. What is that limit? J S Huang 1-515-557-3987 fax 1-515-557-2422 >>> 1/23/2006 12:35:26 PM >>> The independent variables are group and weight In logistic regression the prob will look like logit(probability of being alive at time j) = b0 + b1*weight(at j=1) + b1*weight(at j=2) + ...+ b*weight(at j-1) + b*group then the weight at each time point is the independent variable. --- Jiann-Shiun Huang skrev: > Yen: > > What are independent variables in your model? I > suppose that you > want to use the weights in the three periods before > the current time. > If not, let us know what are your independent > variables. > > J S Huang > 1-515-557-3987 > fax 1-515-557-2422 > > >>> 1/23/2006 12:16:48 PM >>> > Hi, > Thank you for giving me a so fast solution. > But I am afraid I don't understand the solution yet. > I I want to calculate the probability of being > observed at time j=7 then this prob is based on the > weights at times 1-6. Do I have to create a new > variable that contains the weights up to time j-1 > every time I calculate the prob of being observed at > time j ? I have a dataset of 550 animal and each > animal is measured at least 20 times. If I want to > calculate the prob of being alive for each animal at > each time point then there will many probabilities. > > if I use the data you done for and use it im my > model. > Should I write > > Proc genmod data= weight4; > > class group week animal; > > model R = group week wghtL1 week*wghtL1 / > > link=logit > > dist=bin; > > run; > > > > --- Jiann-Shiun Huang > skrev: > > > Yen: > > > > Use the following code to add wghtL1, wghtL2 and > > wghtL3 to the file. > > The rest is to write the model according to the > new > > variables. The > > resulting output follows the code. > > > > data weight; > > input Animal \$ week Group \$ Weight R; > > cards; > > 1 1 1 28.4 1 > > 1 2 1 28.6 1 > > 1 3 1 28.7 1 > > 1 4 1 29.7 1 > > 1 5 1 29.9 1 > > 1 6 1 30.1 1 > > 1 7 1 30.9 1 > > ; > > run; > > > > proc sort data=weight; > > by animal week; > > run; > > > > data Weight4; > > set weight; > > wghtL1=lag(weight); > > wghtL2=lag2(weight); > > wghtL3=lag3(weight); > > run; > > > > proc print; > > run; > > > > ***** Output ***** > > > > > > wght > > wght wght > > Obs Animal week Group > > Weight R L1 > > L2 L3 > > > > 1 1 1 1 > > 28.4 1 . > > . . > > 2 1 2 1 > > 28.6 1 28.4 > > . . > > 3 1 3 1 > > 28.7 1 28.6 > > 28.4 . > > 4 1 4 1 > > 29.7 1 28.7 > > 28.6 28.4 > > 5 1 5 1 > > 29.9 1 29.7 > > 28.7 28.6 > > 6 1 6 1 > > 30.1 1 29.9 > > 29.7 28.7 > > 7 1 7 1 > > 30.9 1 30.1 > > 29.9 29.7 > > > > J S Huang > > 1-515-557-3987 > > fax 1-515-557-2422 > > > > >>> 1/23/2006 10:51:26 AM > >>> > > Dear all, > > I have a dataset like > > > > Obs Animal week Group Weight R > > > > 1 1 1 1 28.4 1 > > 2 1 2 1 28.6 1 > > 3 1 3 1 28.7 1 > > 4 1 4 1 29.7 1 > > 5 1 5 1 29.9 1 > > 6 1 6 1 30.1 1 > > 7 1 7 1 30.9 1 > > > > > > . . > > . . > > > > 33508 550 13 1 28.1 1 > > 33509 550 14 1 28.0 1 > > 33510 550 15 1 29.6 1 > > 33511 550 16 1 28.4 1 > > 33512 550 17 1 29.7 1 > > 33513 550 19 1 28.5 1 > > > > > > I want to calculate the probability that for > example > > animal 1 is alive at time 4 depends on its weights > > at > > time 1, 2 and 3. This is done by using logistic > > regression as follows > > > > Proc genmod data= new; > > class group week animal; > > model R = group week weight* week*weight* / > > link=logit > > dist=bin; > > run; > > > > My question is how do I write in SAS so that > weight* > > contains the values of weight at time 1, 2 and 3. > > Below is what I tried to do before using the proc > > logistic. > > > > data new; > > set bdw; > > by animal; > > weight*=lag(weight) > > run; > > > > data new looks like > > > > > > Obs Animal week Weight R weight* > > 1 1 1 28.4 1 . > > 2 1 2 28.6 1 28.4 > > 3 1 3 28.7 1 28.6 > > 4 1 4 29.7 1 28.7 > > 5 1 5 29.9 1 29.7 > > 6 1 6 30.1 1 29.9 > > 7 1 7 30.9 1 30.1 > > 8 1 8 31.6 1 30.9 > > 9 1 9 31.2 1 31.6 > > > > > > If I want to calculate the probability of being > > alive > > at time 4, then this prob only depends on weight > at > > time 3 and not at time 1 and 2, if I use the data > > new. > > > > > > Can anyone help me ? I want actually calculate the > > prob of being alive for every time point. > > > > Thanks in advance, > > Yen > > > ```

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