https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/Help-with-Weight-Option/m-p/63225#M1522 Hi,<BR /> I'm working on patient satisfaction with first level health care in Mexico. The Data base contains a variable called 'factores de expansion final' to allow the sample to be representative of the whole population. According to what I know, this variable should be included in the weight option of any procedure used in SAS.<BR /> The data base contains a lot of potential independant variables ( variables of partial satisfaction) which are all correlated to each others. Thus I decided to run a factor analisis. As the variables are defined on lickert scale, I choose to transform them with proc prinqual and then run the factor analisis with the transformed variables. <BR /> <BR /> This solution was really meaningfull and logical as long as I didn't use the weight option. With the weight option, factors and transformations had no sense, even with rotations.<BR /> I dont understand why the inclusion of this option is changing so much the correlations between variables.<BR /> <BR /> Then I used the factors from the solution without weight in a binary logistic regression to modelize global satisfaction and this time, the solution with the weight option in proc logit is very very good (R2=0.9, too good?) and very very bad without it ( R2 =0.1).<BR /> I stilll dont understand why does the solution changes so much with or without the option.<BR /> Which solutin should I use? Should I never use the option weight, always use it or only use it when the results are coherent?<BR /> Please help me, this analisis is suppose to help improve the mexican health car system,<BR /> Thanks for your attention and help,<BR /> Chompy Thu, 12 Aug 2010 17:47:58 GMT deleted_user 2010-08-12T17:47:58Z https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/Help-with-Weight-Option/m-p/63225#M1522 Hi,<BR /> I'm working on patient satisfaction with first level health care in Mexico. The Data base contains a variable called 'factores de expansion final' to allow the sample to be representative of the whole population. According to what I know, this variable should be included in the weight option of any procedure used in SAS.<BR /> The data base contains a lot of potential independant variables ( variables of partial satisfaction) which are all correlated to each others. Thus I decided to run a factor analisis. As the variables are defined on lickert scale, I choose to transform them with proc prinqual and then run the factor analisis with the transformed variables. <BR /> <BR /> This solution was really meaningfull and logical as long as I didn't use the weight option. With the weight option, factors and transformations had no sense, even with rotations.<BR /> I dont understand why the inclusion of this option is changing so much the correlations between variables.<BR /> <BR /> Then I used the factors from the solution without weight in a binary logistic regression to modelize global satisfaction and this time, the solution with the weight option in proc logit is very very good (R2=0.9, too good?) and very very bad without it ( R2 =0.1).<BR /> I stilll dont understand why does the solution changes so much with or without the option.<BR /> Which solutin should I use? Should I never use the option weight, always use it or only use it when the results are coherent?<BR /> Please help me, this analisis is suppose to help improve the mexican health car system,<BR /> Thanks for your attention and help,<BR /> Chompy Thu, 12 Aug 2010 17:47:58 GMT https://communities.sas.com/t5/SAS-Health-and-Life-Sciences/Help-with-Weight-Option/m-p/63225#M1522 deleted_user 2010-08-12T17:47:58Z