Hi I recently changed computer from a 32 bit windows Vista machine to a 64 bit Windows 7 machine running SAS 9.4 x64 bit. I am trying to compile globally used SAS macros, but I receive an error message. Could some good person briefly explain why this is happening and me how to overcome the error. Is there something simple I need to do. I am just starting to reuse SAS again, so still learning. Below is my code and error message. Thanks Ian. Macro code: **** PUT ALL GLOBAL MACRO VARIABLES IN ALPHABETICAL ORDER ***; options mstored sasmstore=utility; %macro putmacrovars / store source   des = 'Puts all the global macros and their values in the output window';   title 'Current global macro variables in alphabetical order';   footnote;   proc sql flow;   select name, value   from dictionary.macros   where scope='GLOBAL'   order by name;   quit; %mend; Error message: 110  **** PUT ALL GLOBAL MACRO VARIABLES IN ALPHABETICAL ORDER ***; 111  options mstored sasmstore=utility; 112  %macro putmacrovars / store source NOTE: The SAS System was unable to open the macro library referenced by the SASMSTORE = libref       UTILITY. ERROR: File UTILITY.SASMACR.CATALOG was created for a different operating system. ERROR: A dummy macro will be compiled. 113      des = 'Puts all the global macros and their values in the output window'; 114      title 'Current global macro variables in alphabetical order'; 115      footnote; 116      proc sql flow; 117          select name, value 118          from dictionary.macros 119          where scope='GLOBAL' 120          order by name; 121      quit; 122  %mend; 123 ... View more

Hi, My question is not so much about a statistical procedure as producing journal quality statistical tables using SAS output. I have been using SAS for the past two years and everytime after manipulating my data and getting the results, producing good quality statistical tables is always a challenge. For example, using proc reg or proc GML to produce a journal quality statistical table is quite cumbersome. What I do now is when I get to this last stage of my empirical work, I switch to STATA and with little effort, I can produce a table that I can cut and paste into a word document for my paper. I have searched on this forum and in the web for articles or discussions about this topic, but I don't seem to find anything. Am I missing something? Is SAS easy to use for producing journal quality statistical tables? Although I use ODS a little bit, I am certainly not an expert. At the moment, all my outputs are either excel or html using ODS, but they take a huge amount of editing to get to journal quality level. Can someone enlighten me or pass me some links that talk about this issue. Thanks Ian. ... View more

Proc Univariate provides three tests of location: t, signed, and ranked sign. These test results are provided if your analysis variable is equally weighted, i.e. when no WEIGHT option is used. However, when the  WEIGHT option is used, the results for sign and ranked sign tests are not provided, while only those of the t test are. I can understand why they are not provided for the sign test, because the results should in principle be the same as when no weight option is used. But I would like to get the ranked sign results of a weighted analysis variable. Does any body know how to do this in a SAS with an in-built procedure? FYI, my analysis variable is excess bond returns (difference between actual bond return and an index return) , so the interval to calculate the ranks is well defined. However, I want to calculate the value of a portfolio of excess returns (for an event study) on each trading day. I want to weight the excess returns of each bond issue in the portfolio according to market value. In other words, the excess return ranking will be based not only size of the excess return, but also on the weight of the issue. I provide a sample data set. The main analysis variable is abret11 (excess or abnormal returns of bonds). The weight variable is pfmv_bdo. The by variables are bindx_cat evttime. Using proc univariate and assuming equally weighted excess returns, the code I would use is: proc univariate data=sample100 ;   by bindx_cat evttime; var abret11;   ods output testsforlocation = test1;   /* This contains the p-values */   ods output moments = test1a;         /* This contains the descriptive data */   run; What I would like to do, if it were possible, is add the option: WEIGHT pfmv_bdo; and also get results for the Ranked Sign test. The question is HOW??? Thanks for any help provided. Ian. ... View more

Hi, In SAS 9.2 Help, there is an example entitled "Weighted Statistics Example" that uses the Proc Means Weight option. I am trying to understand how the variances in the example are calculated by doing it manually in EXCEL, but I cannot work out how SAS calculates it. Referring to the code below, I am able to calculate the variance that is in Example 1, but can someone please explain to me Example 2 and 3. My exact questions are: 1. In example 2, how do you calculate Est_SigmaSq (i.e. var)? 2. If you were to transform the variable ObjectSize in Example 2, what would it be in order to get the variance Est_SigmaSq? 3. The same two questions apply for Example 3. Below is the code as given in SAS Help and I also attach the Excel I am using to do my manual calculations if you need it. Thanks and Regards Ian. data size;    input Distance ObjectSize @@;    Precision=1/distance;    datalines; 1.5 30 1.5 20 1.5 30 1.5 25 3   43 3   33 3   25 3   30 4.5 25 4.5 36 4.5 48 4.5 33 6   43 6   36 6   23 6   48 7.5 30 7.5 25 7.5 50 7.5 38 ; *EXAMPLE1; proc means data=size maxdec=3 n mean var stddev;    var objectsize;    title1 'Unweighted Analysis of the SIZE Data Set'; run; **EXAMPLE2; proc means data=size maxdec=3 n mean var stddev;    weight precision;    var objectsize;    output out=wtstats var=Est_SigmaSq std=Est_Sigma;    title1 'Weighted Analysis Using Default VARDEF=DF'; run; **EXAMPLE3; proc means data=size maxdec=3 n mean var std vardef=weight;    weight precision;    var objectsize;    title1 'Weighted Analysis Using VARDEF=WEIGHT'; run; ... View more