Is QDrive a syntax? or a drive like C:/? ... View more

Thank you so much. This worked and was shorter. I solved the problem by creating a dataset containing smoke 1 vs 0, and then creating 4 dataset from that have the parameter estimates of each level of my composite variable. I then used proc mianalyze on each of the 4 datasets and each dataset gave me the OR. Longer but it did it. Thanks so much! ... View more

Hello Rob, I outputted the interaction effects of the 50 imputed variables in a dataset Please how do i get the pooled estimate of these estimates. Here's the snip of my code. Please i need help or is there a contact of anyone in SAS who can help? I can't find a contact on the sas.com website. The SAS document on this topic did not release how to implement using proc mianalyse to pool estimates of interaction term. proc surveylogistic data =newnsch3c NAMELEN=100; BY _Imputation_; class smokes(Ref= '0') composite (ref='0') /param=glm ; strata Fipsst; cluster hhid; weight fwc; Model asthma (event ='1') = smokes composite smokes*composite ; lsmeans smokes*composite/ diff; ods output diffs=diff_ds; run; smokes has 2 levels (0 and 1) while composite has (0,1,2,3).The above code gave me a dataset with a structure like this. How do i pool these effects together using proc mianalyze.                   ... View more

Hello, Thanks. This part if the code is a little confusing proc surveylogistic data=test; by _imputation_; class a/param=glm; model y=a|x1; lsmeans a/at x1=.2 diff; lsmeans a/at x1=.4 diff;   I assume you got x1= 0.2 from intercept and x1 =0.4 from the coefficient of a-b. Since my predictors are all categorical, why can't i do something like this: lsmeans a/at x1=0 diff; to denote the first level of my cat variables  lsmeans a/at x1=1 diff; to denote the second level of my cat variables.   ... View more

Hello Rob, I saw you gave the response to this post just a few months ago. I've been struggling with how to output the OR of interaction term from the pooled multiple imputation estimates. For example, lets assume that B is a categorical variables and Ind1 is a categorical variable with three levels. If there's an interaction between  B and Ind1 and i want to find the OR of the interaction, taking the exponential of b*Ind1 as in the dataset does not give me the OR of the interaction at different level of the exposure. Do you have an idea how to get OR from a pooled imputed estimates in which the model has an interaction term?  proc mianalyze parms(classvar=classval)=parms; class a b Ind1; modeleffects intercept a b ind1 b*Ind1; by response; run;   ... View more

Hello, Thank you. I sorted the dataset and that problem resolved. My variable is asthma severity categorized as none, mild and moderate/severe. I guess that makes it ordinal in nature. I tried the clogit  as  suggested online for ordinal logistic regression. However, i'm interested in looking at the odd ratio of mild  vs none and moderate/severe vs none outcomes and the ordinal logistic (both clogit and logit) did not give me that. Instead it gave me a single odds ratio (see the output below) However when i used the multinomial (glogit) link function, it gave me different ORs of my predictors against the outcomes (mild vs none and moderate/severe vs none) which is what i'm interested in. This output is the result of ordinal logistic. Are the ORs telling me that Mold is protective of asthma severity? The multinomial logistic output below, for example, is telling me that mold had a stronger association in people with moderate/severe asthma than in people with mild asthma.      ... View more

Another question: Do you also know why i'm getting this message?   ... View more

Thank you very much. That worked. Then there's a question on how to output Odd Ratios of interaction terms that i have asked here 2 weeks ago and i never got a response about it. Here is my code: proc surveylogistic data =newnsch3c NAMELEN=100; class sex (ref = '0') race(Ref = '0') FPL (ref= '0') smokeinside(Ref= '0') family (ref='0') composite (ref='0') age3_1718 (ref='2') /param=glm ; strata Fipsst; cluster hhid; weight fwc; Model asthma (event ='1') = age3_1718 sex race FPL smokeinside composite family smokeinside*composite ; lsmeans smokeinside*composite/oddsratio cl diff; slice smokeinside*composite/ sliceby=composite diff=control('0' '0') oddsratio cl; ODS OUTPUT PARAMETERESTIMATES=lgsparms ODDSRATIO=lgsodds; BY _Imputation_; run; PROC MIANALYZE PARMS(CLASSVAR=CLASSVAL)=lgsparms; CLASS age3_1718 sex race FPL smokeinside composite family ; MODELEFFECTS age3_1718 sex race FPL smokeinside composite family smokeinside*composite; ODS OUTPUT PARAMETERESTIMATES=mian_; RUN; - In the first code, i used the Odds Ratio statement but it did not output the odd ratios. How can i output the ORs.  - The second code pooled all the 20 imputed parameters  (mian_). Now exponentiation of those parameters gives the OR for variables not involved in the interaction. However, for the interaction terms, smoking inside has 3 levels and composite has 4 level, a simple exponentiation will not give OR of smokeinside at each level of composite. How do i get the OR of this interaction term from the pooled parameter.       ... View more

Hello, I know it's been 2 years since you solved this problem. I get your codes in this example. What if i had an interaction term. how can i output the Odds ratio. For example, if my model is model y=a x1 a*x1; How can i get the OR in this case if both a and x1 are categorical variables. ... View more