When I run a proc contents command, I received the following error message: Code: libname dw odbc datasrc="Vertica" user=myusername password=mypassword schema=ods_abcd; proc contents data=dw.table; run;   Error message:  Error: CLL prepare error: [Vertica] [Vertica DSII] (10) An error occurred during query preparation: Multiple commands cannot be active on the same connnection. Cionsider increasing resultbuffersize or fetching all results before initiating another command. SQL statement: select * from ods_abcd.table.    I used the Vertica connected to my database through ODBC (I use SAS 9.4 SAS server). However, after I get the all the tables, I even could not open the tables in the library and give me the above error message. Any suggestions will be very appreciate!   Regards, Yurie ... View more

Hello, I have a dataset that I need to build a model to predict the # of cases and the charges for year 18 or 20. (We have 13 years data in my sample)  The variables include: year, Gender, Race, Num_Cases, Location, gender, agegroup, Disease, maritual_status, and charge.    1) How can I build the model to predict the charge for the year 18 or 20? (missing value has been coded as 99.) 1) How can I build the model to prediction the number of cases for the year 18 or 20?     Below is my data sample. I will be very thankful for any suggestions or hints.    data have; input year GenderID$ Race Num_Cases Location gender agegroup Disease maritual_status charge; datalines; 1 M 99 1 8 1 6 1 5 900 1 M 99 5 3 1 6 1 1 152 1 F 99 3 16 0 7 1 6 588 1 M 99 26 3 1 7 1 2 79 1 M 99 1 16 1 7 1 6 179 1 M 99 1 12 1 5 1 2 100 1 M 99 2 4 1 7 1 1 245 2 M 99 1 3 1 5 1 5 625 2 F 99 2 3 0 5 1 1 35 2 F 99 1 16 0 6 1 2 144 2 F 99 1 3 0 5 0 5 625 2 F 99 1 3 0 6 0 4 576 2 F 99 3 3 0 6 1 4 192 3 M 99 6 3 1 5 0 1 500 3 M 99 1 3 1 7 1 2 196 3 M 99 1 1 1 6 0 1 36 3 M 99 1 3 1 5 0 1 25 4 M 99 1 3 1 5 0 2 100 4 M 99 3 16 1 5 1 2 352 4 F 99 1 16 0 6 1 6 1296 4 F 99 6 11 0 7 0 2 254 5 M 1 1 3 1 5 1 1 25 5 F 2 3 16 0 4 1 2 213 6 F 1 1 2 0 7 1 6 184 6 F 1 1 13 0 7 1 2 196 6 F 1 1 4 0 7 0 1 49 6 M 4 2 3 1 5 0 1 125 6 F 5 33 3 0 6 0 5 80 7 F 4 1 16 0 7 0 6 1764 7 F 4 2 3 0 6 0 6 648 7 M 6 1 16 1 6 1 6 1296 7 F 2 1 2 0 5 0 5 625 7 F 1 24 3 0 5 0 2 452 7 F 1 1 3 0 6 1 1 362 8 M 5 2 10 1 7 1 2 980 8 M 1 5 3 1 4 1 1 350 8 F 1 1 3 0 6 0 99 352 8 M 5 1 3 1 5 0 1 25 8 M 1 1 3 1 7 0 1 49 9 M 1 1 13 1 7 1 5 1225 9 M 5 4 16 1 7 0 1 122 9 F 5 2 3 0 7 1 2 98 9 M 1 1 1 1 7 1 5 126 10 F 1 66 3 0 6 0 1 54 10 F 2 1 1 0 5 0 1 25 10 F 1 2 4 0 6 0 5 450 10 M 1 3 16 1 7 0 5 408 11 F 1 1 8 0 7 1 2 196 11 M 3 1 3 1 7 1 2 196 11 M 5 5 3 1 6 0 1 72 11 M 1 2 3 1 7 1 1 245 12 F 1 9 11 0 7 0 6 196 12 M 5 2 3 1 5 0 1 125 12 F 5 13 3 0 7 0 6 150 12 M 0 2 3 1 7 0 2 98 13 F 5 3 3 0 5 0 1 215 13 M 0 4 3 1 5 0 1 625 13 M 2 25 3 1 7 1 2 784 13 M 1 1 1 1 7 0 99 480 13 M 2 27 3 1 7 0 2 725 ;   ... View more

Hello, I need to build a preditive model for my data. The variables include: year, gender, race, num_cases, location, ageGroup, disease(1:yes, 0:No), maritual_status, charge. We did not collect race data for the first 4 years (coded 99).   1) How can I deal with the missing race data? (It seems the race is significant.) 2) How can I build a model to predict the probability (disease="yes") for the given variables in the dataset? Very appreciate for any suggestions and help. Thanks.    data have; input year Gender$ Race Num_Cases Location gender agegroup Disease maritual_status charge; datalines; 1 M 99 1 8 1 6 1 5 900 1 M 99 5 3 1 6 1 1 152 1 F 99 3 16 0 7 1 6 588 1 M 99 26 3 1 7 1 2 79 1 M 99 1 16 1 7 1 6 179 1 M 99 1 12 1 5 1 2 100 1 M 99 2 4 1 7 1 1 245 2 M 99 1 3 1 5 1 5 625 2 F 99 2 3 0 5 1 1 35 2 F 99 1 16 0 6 1 2 144 2 F 99 1 3 0 5 0 5 625 2 F 99 1 3 0 6 0 4 576 2 F 99 3 3 0 6 1 4 192 3 M 99 6 3 1 5 0 1 500 3 M 99 1 3 1 7 1 2 196 3 M 99 1 1 1 6 0 1 36 3 M 99 1 3 1 5 0 1 25 4 M 99 1 3 1 5 0 2 100 4 M 99 3 16 1 5 1 2 352 4 F 99 1 16 0 6 1 6 1296 4 F 99 6 11 0 7 0 2 254 5 M 1 1 3 1 5 1 1 25 5 F 2 3 16 0 4 1 2 213 6 F 1 1 2 0 7 1 6 184 6 F 1 1 13 0 7 1 2 196 6 F 1 1 4 0 7 0 1 49 6 M 4 2 3 1 5 0 1 125 6 F 5 33 3 0 6 0 5 80 7 F 4 1 16 0 7 0 6 1764 7 F 4 2 3 0 6 0 6 648 7 M 6 1 16 1 6 1 6 1296 7 F 2 1 2 0 5 0 5 625 7 F 1 24 3 0 5 0 2 452 7 F 1 1 3 0 6 1 1 362 8 M 5 2 10 1 7 1 2 980 8 M 1 5 3 1 4 1 1 350 8 F 1 1 3 0 6 0 99 352 8 M 5 1 3 1 5 0 1 25 8 M 1 1 3 1 7 0 1 49 9 M 1 1 13 1 7 1 5 1225 9 M 5 4 16 1 7 0 1 122 9 F 5 2 3 0 7 1 2 98 9 M 1 1 1 1 7 1 5 126 10 F 1 66 3 0 6 0 1 54 10 F 2 1 1 0 5 0 1 25 10 F 1 2 4 0 6 0 5 450 10 M 1 3 16 1 7 0 5 408 11 F 1 1 8 0 7 1 2 196 11 M 3 1 3 1 7 1 2 196 11 M 5 5 3 1 6 0 1 72 11 M 1 2 3 1 7 1 1 245 12 F 1 9 11 0 7 0 6 196 12 M 5 2 3 1 5 0 1 125 12 F 5 13 3 0 7 0 6 150 12 M 0 2 3 1 7 0 2 98 13 F 5 3 3 0 5 0 1 215 13 M 0 4 3 1 5 0 1 625 13 M 2 25 3 1 7 1 2 784 13 M 1 1 1 1 7 0 99 480 13 M 2 27 3 1 7 0 2 725 ; ... View more

I have a text variable like the following. How can I extract the useful information that I need? Thanks.   {\rtf1\ansi\ansicpg1252\uc0\deff1{\fonttbl {\f0\fswiss\fcharset0\fprq2 Arial;} {\f1\froman\fcharset0\fprq2 Times New Roman;} {\f2\froman\fcharset2\fprq2 Symbol;}} {\colortbl;\red0\green0\blue0;\red255\green255\blue255;\red255\green0\blue0;} {\stylesheet{\s0\f1\fs20 Normal;}{\*\cs10\additive Default Paragraph Font;}{\s16\f0\fs24 [Normal];}{\s17\sa120\f1\fs20\sbasedon0 Body Text;}{\s18\qc\sb360\sa240\f0\fs20\b\sbasedon0\snext0 heading 1;}} {\*\listtable{\list\listtemplateid1\listsimple{\listlevel\levelnfc0\leveljc0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'02\'00\'2e;}{\levelnumbers\'01;}\f1\fs24\b0\i0\strike0\ul0\cf0\cb0\fi-360\li821}{\listname ;}\listid1}} {\*\listoverridetable{\listoverride\listid1\listoverridecount0\ls1}} {\*\generator TX_RTF32 9.1.312.500;} \deftab1134\paperw12240\paperh15840\margl2592\margt3888\margr1138\margb1138\pard\s17\sl480\slmult1\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360\tx10080\plain\f1\fs24\cf3 <CERTIFIED MAIL #> <HAND DELIVERY> \par\pard\s17\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360\tx10080\plain\f1\fs24 [Today in Words()]\par\par [Admin. 1st Name (Frank)()] [Admin. Last name (Smith)()], Administrator\parhe facility received an \loch\f1\hich\f1 \'93A\'94 during its survey,...   ... View more