Hi PG, I have used proc glm on the same set of data successfully but my professor insists that I also run a proc reg. I changed my statements to: proc reg data=c; model Acar1 = ratio lnTEn lnSIZE TobinQ ADebtratio DEBTRT Cash HYBRID OTHER SHARES UNKNOWN Horizontal Vertical Conglomerate zero one two three four five six seven eight nine ten eleven twelve thirteen fourteen CPS ENERGY FINANCE HEALTH HT IND MATERLS REALEST RETAIL STAPLES TELECOM AEQW/noint; run; But I still get the notes: Note: Model is not full rank. Least-squares solutions for the parameters are not unique. Some statistics will be misleading. A reported DF of 0 or B means that the estimate is biased.  Note: The following parameters have been set to 0, since the variables are a linear combination of other variables as shown. Conglomerate = Cash + HYBRID + OTHER + SHARES + UNKNOWN - Horizontal - Vertical fourteen = Cash + HYBRID + OTHER + SHARES + UNKNOWN - zero - one - two - three - four - five - six - seven - eight - nine - ten - eleven - twelve - thirteen TELECOM = Cash + HYBRID + OTHER + SHARES + UNKNOWN - CPS - ENERGY - FINANCE - HEALTH - HT - IND - MATERLS - REALEST - RETAIL - STAPLES Parameter Estimates Variable Label DF Parameter Estimate Standard Error t Value Pr > |t| ratio ratio 1 0.08509 0.03495 2.44 0.0184 lnTEn lnTEn 1 -0.00575 0.00582 -0.99 0.3281 lnSIZE lnSIZE 1 -0.00398 0.00624 -0.64 0.5269 TobinQ TobinQ 1 0.00001882 0.00003795 0.50 0.6220 ADebtratio ADebtratio 1 2.35285 3.60842 0.65 0.5172 DEBTRT DEBTRT 1 -0.02118 0.02589 -0.82 0.4170 Cash ConsiStr CASHO B 0.04587 0.09930 0.46 0.6461 HYBRID ConsiStr HYBRID B 0.07168 0.10062 0.71 0.4794 OTHER ConsiStr OTHER B 0.08375 0.10428 0.80 0.4256 SHARES ConsiStr SHARES B 0.06744 0.09908 0.68 0.4991 UNKNOWN ConsiStr UNKNOWN B 0.04524 0.10627 0.43 0.6721 Horizontal Type 1 B -0.00760 0.01355 -0.56 0.5775 Vertical Type 2 B 0.01477 0.01575 0.94 0.3527 Conglomerate Type 3 0 0 . . . zero year 2000 B 0.04037 0.03713 1.09 0.2819 one year 2001 B 0.09816 0.03612 2.72 0.0089 two year 2002 B 0.08024 0.03817 2.10 0.0404 three year 2003 B 0.01385 0.03398 0.41 0.6853 four year 2004 B 0.04770 0.03453 1.38 0.1731 five year 2005 B 0.02025 0.03139 0.65 0.5217 six year 2006 B 0.02535 0.02826 0.90 0.3738 seven year 2007 B 0.00789 0.03068 0.26 0.7980 eight year 2008 B 0.08945 0.03590 2.49 0.0159 nine year 2009 B 0.04158 0.03096 1.34 0.1852 ten year 2010 B -0.00238 0.04236 -0.06 0.9553 eleven year 2011 B 0.04103 0.03513 1.17 0.2482 twelve year 2012 B 0.05978 0.03336 1.79 0.0789 thirteen year 2013 B 0.04555 0.04313 1.06 0.2958 fourteen year 2014 0 0 . . . CPS Industry CPS B 0.00974 0.05062 0.19 0.8481 ENERGY Industry ENERGY B 0.07491 0.06755 1.11 0.2725 FINANCE Industry FINANCE B 0.03148 0.05087 0.62 0.5388 HEALTH Industry HEALTH B -0.01152 0.05331 -0.22 0.8298 HT Industry HT B 0.02942 0.05232 0.56 0.5763 IND Industry IND B 0.00880 0.05026 0.18 0.8616 MATERLS Industry MATERLS B 0.03385 0.05001 0.68 0.5015 REALEST Industry REALEST B 0.01833 0.05719 0.32 0.7499 RETAIL Industry RETAIL B 0.02712 0.05067 0.54 0.5947 STAPLES Industry STAPLES B 0.05081 0.05409 0.94 0.3519 TELECOM Industry TELECOM 0 0 . . . AEQW AEQW 1 0.00003368 0.00018967 0.18 0.8598   Thanks, Niloo     ... View more

Hi again,   I used the following statements to first define dummy variables and then run a "proc reg" : libname ev 'C:\Regression'; run; ***Majority All data set- Regression for Acquirors, CAR (-1, +1), announcment date ********/; data final2; set ev.final2(keep= tdscd ADSCD Aname Tname AnDate Wdate Acar1 Acar5 Tcar1 Tcar5 TobinQ ADebtratio DEBTRT HOSTATASS AMVal4wp TMVal4wp EqValAn EnValAn ConsiStr TNation type AEQW); proc sort; by adscd andate; run; data a; set ev.final2; if amval4wp ne 0 and amval4wp ne . then ratio=tmval4wp/amval4wp; lnTEq=log(EqValAn); lnTEn=log(EnValAn); lnTMV=log(TMVal4wp); lnAMV=log(amval4wp); lnSIZE=log(HOSTATASS); year = year(Andate); Industry= AMaCode; run; proc glmmod data=a outdesign=b outparm=parm; class ConsiStr type Industry year; model Acar1 = ratio lnTEn lnSIZE TobinQ ADebtratio DEBTRT ConsiStr type year Industry AEQW / noint; run; proc print data=parm; run; /* If you want, rename the variables created by GLMMOD */ data c; set b; rename col1=ratio col2=lnTEn col3=lnSIZE col4=TobinQ col5=ADebtratio col6=DEBTRT col7=Cash col8=HYBRID col9=OTHER col10=SHARES col11=UNKNOWN col12=Horizental col13=Vertical col14=Conglomerate col15=zero col16=one col17=two col18=three col19=four col20=five col21=six col22=seven col23=eight col24=nine col25=ten col26=eleven col27=twelve col28=thirteen col29=fourteen col30=CPS col31=ENERGY col32=FINANCE col33=HEALTH col34=HT col35=IND col36=MATERLS col37=REALEST col38=RETAIL col39=STAPLES col40=TELECOM col41=AEQW; run; proc reg data=c; model Acar1 = ratio lnTEn lnSIZE TobinQ ADebtratio DEBTRT Cash HYBRID OTHER SHARES UNKNOWN Horizental Vertical Conglomerate zero one two three four five six seven eight nine ten eleven twelve thirteen fourteen CPS ENERGY FINANCE HEALTH HT IND MATERLS REALEST RETAIL STAPLES TELECOM AEQW; run; But I get the following notes in my results viewer : Note: Model is not full rank. Least-squares solutions for the parameters are not unique. Some statistics will be misleading. A reported DF of 0 or B means that the estimate is biased.   Note: The following parameters have been set to 0, since the variables are a linear combination of other variables as shown.   UNKNOWN = Intercept - Cash - HYBRID - OTHER - SHARES Conglomerate = Intercept - Horizental - Vertical fourteen = Intercept - zero - one - two - three - four - five - six - seven - eight - nine - ten - eleven - twelve - thirteen TELECOM = Intercept - CPS - ENERGY - FINANCE - HEALTH - HT - IND - MATERLS - REALEST - RETAIL - STAPLES   Parameter Estimates Variable Label DF Parameter Estimate Standard Error t Value Pr > |t| Intercept Intercept B 0.04524 0.10627 0.43 0.6721 ratio ratio 1 0.08509 0.03495 2.44 0.0184 lnTEn lnTEn 1 -0.00575 0.00582 -0.99 0.3281 lnSIZE lnSIZE 1 -0.00398 0.00624 -0.64 0.5269 TobinQ TobinQ 1 0.00001882 0.00003795 0.50 0.6220 ADebtratio ADebtratio 1 2.35285 3.60842 0.65 0.5172 DEBTRT DEBTRT 1 -0.02118 0.02589 -0.82 0.4170 Cash ConsiStr CASHO B 0.00063236 0.03488 0.02 0.9856 HYBRID ConsiStr HYBRID B 0.02644 0.04301 0.61 0.5414 OTHER ConsiStr OTHER B 0.03852 0.05761 0.67 0.5067 SHARES ConsiStr SHARES B 0.02220 0.03162 0.70 0.4857 UNKNOWN ConsiStr UNKNOWN 0 0 . . . Horizental Type 1 B -0.00760 0.01355 -0.56 0.5775 Vertical Type 2 B 0.01477 0.01575 0.94 0.3527 Conglomerate Type 3 0 0 . . . zero year 2000 B 0.04037 0.03713 1.09 0.2819 one year 2001 B 0.09816 0.03612 2.72 0.0089 two year 2002 B 0.08024 0.03817 2.10 0.0404 three year 2003 B 0.01385 0.03398 0.41 0.6853 four year 2004 B 0.04770 0.03453 1.38 0.1731 five year 2005 B 0.02025 0.03139 0.65 0.5217 six year 2006 B 0.02535 0.02826 0.90 0.3738 seven year 2007 B 0.00789 0.03068 0.26 0.7980 eight year 2008 B 0.08945 0.03590 2.49 0.0159 nine year 2009 B 0.04158 0.03096 1.34 0.1852 ten year 2010 B -0.00238 0.04236 -0.06 0.9553 eleven year 2011 B 0.04103 0.03513 1.17 0.2482 twelve year 2012 B 0.05978 0.03336 1.79 0.0789 thirteen year 2013 B 0.04555 0.04313 1.06 0.2958 fourteen year 2014 0 0 . . . CPS Industry CPS B 0.00974 0.05062 0.19 0.8481 ENERGY Industry ENERGY B 0.07491 0.06755 1.11 0.2725 FINANCE Industry FINANCE B 0.03148 0.05087 0.62 0.5388 HEALTH Industry HEALTH B -0.01152 0.05331 -0.22 0.8298 HT Industry HT B 0.02942 0.05232 0.56 0.5763 IND Industry IND B 0.00880 0.05026 0.18 0.8616 MATERLS Industry MATERLS B 0.03385 0.05001 0.68 0.5015 REALEST Industry REALEST B 0.01833 0.05719 0.32 0.7499 RETAIL Industry RETAIL B 0.02712 0.05067 0.54 0.5947 STAPLES Industry STAPLES B 0.05081 0.05409 0.94 0.3519 TELECOM Industry TELECOM 0 0 . . . AEQW AEQW 1 0.00003368 0.00018967 0.18 0.8598  Is this an example of exact multicolinearity? Could you please let me know how I can create dummy variables and then run a proc reg on all variables?It seems that all my results are biased.   Thank you, Niloo   ... View more

Thak you very much. It works perfectly now. ... View more

Thank you soooooo much PG it worked. i used the third one. However the type variable still gives me errors: proc glm data=a; where UPCASE(type)="3"; class type ConsiStr year Industry; model Acar1 = year / noint; run; QUIT; error: 182 proc glm data=a; 183 where UPCASE(type)="3"; ERROR: Function UPCASE requires a character expression as argument 1. 184 class type ConsiStr year Industry; 185 model Acar1 = year / noint; 186 run; WARNING: RUN statement ignored due to previous errors. Submit QUIT; to terminate the procedure. 187 QUIT; NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE GLM used (Total process time): real time 0.00 seconds cpu time 0.00 seconds     ... View more

Sorry I made a mistake. In my data base "type" is numeric: 1for horizental deals, 2 for vertical and 3 for conglomerate.(so there is no horizental, vertical, conglomerate under type variable only 1 and 2 and3. "ConsiStr" is a character variable: Cash, stock, hybrid, unknown. I changed the statements to: proc glm data=a; where type="3"; class ConsiStr year Industry; model Acar1 = year / noint; run; QUIT; proc glm data=a; where put (ConsiStr,$char6.)="cash"; class ConsiStr type year Industry; model Acar1 = ConsiStr / noint; run; QUIT; and the error is still:  46 proc glm data=a; 147 where type="3"; ERROR: WHERE clause operator requires compatible variables. 148 class ConsiStr year Industry; 149 model Acar1 = year / noint; 150 run; WARNING: RUN statement ignored due to previous errors. Submit QUIT; to terminate the procedure. 151 QUIT; NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE GLM used (Total process time): real time 0.00 seconds cpu time 0.01 seconds   152 proc glm data=a; 153 where put (ConsiStr,$char6.)="cash"; 154 class ConsiStr type year Industry; 155 model Acar1 = ConsiStr / noint; 156 run; NOTE: No observations were selected from data set WORK.A. NOTE: PROCEDURE GLM used (Total process time): real time 0.00 seconds cpu time 0.01 seconds 157 QUIT;  thanks, Niloo     ... View more

Thanks PG, I tried it but I got this error:   74 proc glm data=a; 75 where type="cash"; ERROR: WHERE clause operator requires compatible variables. 76 class ConsiStr year Industry; 77 model Acar1 = year / noint; 78 run; WARNING: RUN statement ignored due to previous errors. Submit QUIT; to terminate the procedure. 79 QUIT; NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE GLM used (Total process time): real time 0.02 seconds cpu time 0.00 seconds   Shall I run the PROC GLMMOD before my PROC GLM statements? ... View more

Hi again,   I have a question about the dummy variables created by Proc GLM. Variable "type" showes the type of payment (Cash, stock, Hybrid, Unknown) and variable "ConsiStr" discribes the type of deal(horizental, vertical, conglomerate). I need to run a regression on my dependent variable (ACAR1) and "cash" type of payment (not the whole "type" variable) and on ACAR1 and "conglomerate" dales( not the ConsiStr variable itself. But I cannot do it using my current PROC GLM statements. Is there a way I can do this using Proc GLM? Here is what I currently have: libname ev 'C:\Regression'; run; data final2; set ev.final2(keep= tdscd ADSCD Aname Tname AnDate Wdate Acar1 Acar5 Tcar1 Tcar5 TobinQ ADebtratio DEBTRT HOSTATASS AMVal4wp TMVal4wp EqValAn EnValAn ConsiStr TNation type AEQW); proc sort; by adscd andate; run;   data a; set ev.final2; if amval4wp ne 0 and amval4wp ne . then ratio=tmval4wp/amval4wp; lnTEq=log(EqValAn); lnTEn=log(EnValAn); lnTMV=log(TMVal4wp); lnAMV=log(amval4wp); lnSIZE=log(HOSTATASS); year = year(Andate); Industry= AMaCode; run; proc glm data=a; class ConsiStr type year Industry; model Acar1 = year / noint; QUIT; run; proc glm data=a; class ConsiStr type year Industry; model Acar1 = Industry / noint; QUIT; run; proc glm data=a; class ConsiStr type year Industry; model Acar1 = AEQW/ noint; QUIT; run; .... and the rest of the variables ODS TAGSETS.EXCELXP file='C:\Users\esy\Desktop\niloofar\DePaul Research\M&AJAPAN\Majority\Results\regression.xls' STYLE=minimal OPTIONS ( Orientation = 'landscape' FitToPage = 'yes' Pages_FitWidth = '1' Pages_FitHeight = '100' sheet_interval='NONE' );   Thanks, Niloo ... View more