Hi There,   I am doing a meta-analysis for correlation between sleep and mental health. The issue is in some studies higher score indicates better sleep, while in other of my studies lower score means better sleep. So the direction of r could mean different things. I am wondering how should I handle this? Can I just pick absolute value? For example, if r=-0.2, then I change it to 0.2. Or if r=0.45, then I change it to -0.45?   Thanks in advance! ... View more

Hello,   I use SAS 9.4 and I am looking at how the presence or absence of disease at baseline year would affect the number of health care use in the next 2 years. I have a data set like this: id     baselinedisease     healthuse 1      0                              3 2      0                             15 3      1                              2 4      0                              5 5      1                              0 ... However, some people developed the disease at year 1 post baseline or year 2 post baseline, and I think this would affect their subsequent number of health care use. So I want to reflect this in the model. I have another data set showing me the presence or absence of disease for each participant in year 1 and year 2 post baseline. The current codes I am using is:   proc genmod data=have; class disease (ref='0') / param=glm; model healthuse = disease / type3 dist=poisson; run; Does anyone can help me figure out the problem? Thank you in advance! ... View more

Hello,   I use SAS 9.4 and I have a data set like this: ID     pcs        year        disease 1       45          1            1 1       47          2            1 1       50          3            1 2       42          1            0 2       43          2            0 2       46          3            0 3       40          1            0 3       40          2            0 3       49          3            0 ...   I want to see how the presence or absence of disease affect the PCS scores rate of change from year 1 to year 3 for each subject. I run the following codes:   proc glimmix data=have; class disease (ref='0'); model pcs = disease year disease*year / cl; run;   Then I got the results but I do not think it is correct, since the estimate for intercept is around 12, but the average pcs at year 1 is over 40 instead of 12. Does anyone can help me figure out the problem?   Thank you! ... View more

Hello,   I use SAS 9.4 and I have a data set which has 7 variables: ID, a, b, c, d, e, f. There are some missing values for variables a-f. a, b and c are categorical variables and d, e, f are continuous variables. I tried the following way for the imputation phase but the missing values are still missing and not be imputed. Does anyone know the reason? Thank you!   proc mi data =have nimpute=100 out=want; class a b c; fcs discrim(a = b c d e f/classeffects=include); fcs discrim(b = a c d e f/classeffects=include); fcs discrim(c = a b d e f/classeffects=include); var a b c d e f; run;   ... View more