Thank you for providing this! I have never used macros before as I have never earned this, but I tried following the detailed instructions and using google for a couple things. Where in my sas code should I place it? I received this error below. Also, I am unsure if you could help me with this, but I saw in my google search that some people use an .xlsx file for outdoc so I created a file and included the filepath and name in the outdoc statement. I am unsure if this was the right thing to do. 328 %tablen(data=IAT2018, by=D_biep_White_Good_all, - 180 ERROR 180-322: Statement is not valid or it is used out of proper order. 329 var=Age raceomb_002 birthSex edu politicalid_7 occupation_selfdetail_001, 330 type=1 2, pvals=5, 331 contdisplay=m sd, outdoc=\Users\tjoseph6\Documents\IAT2018.xlsx); 332 run; ... View more

Thank you for your response. I did not provide the table as a means of showing a hypothesis test; I provided it to give a little more context if possible about what my committee chair wanted me to do using proc means, which frankly I was confused by so it's reassuring to see that it didn't much sense to you as well. An example of what I actually want to test for is to see if there is a difference in mean IAT score between each race. The null hypothesis: there is no difference in mean IAT score between each race. Alternative hypothesis: at least one of the races has a different mean IAT score. I would like to do this for each demographic category (Gender, race, education level, political affiliation, occupation). Please let me know if I need to add further information or need to clarify something? Also, please let me know if there is anything wrong with what I am trying to test. ... View more

Since you are saying this is impossible, do you think simply running PROC ANOVA and PROC TTEST would provide the result as you stated? Also, please let me know if you require information or more details on what my committee chair is asking me to do! ... View more

This is what I wanted to run initially, but my committee chair stated that I need to run a test between each group in each category. For example, get the p-value for the mean IAT score and the different age groups (16-19, 20-29, 30-39, 40-49, 50-64, and 65+). For context, I used proc means in order to get the mean IAT scores in the table below; the data does IAT score does not show up as mean values of course. Unfortunately, he is asking me to do this but is unable to show me any sort of example of how to achieve what he is asking for since he uses a different software.     ... View more

Oh wow it worked!! I honestly was close to losing hope. I cannot thank you enough for your knowledge and patience with this!!! proc import out=work.IAT2016_raw datafile="C:\Users\tjoseph6\Documents\My SAS Files\IAT2016.sav" dbms=sav replace; run; data IAT2016; set work.IAT2016_raw (keep=year birthyear sex_5 raceomb D_biep_White_Good_all countrycit occupation_self politicalid_7); Age=year-birthyear; where left(countrycit)='1' & occupation_self in ('29-1000','31-1000') & sex_5 in (1,2); if D_biep_White_Good_all ne .; if politicalid_7 eq . then delete; if Age lt 16 then delete; if raceomb eq . then delete; label sex_5='Gender' raceomb='Race' D_biep_White_Good_all='Overall IAT D Score' politicalid_7='Political Ideology Spectrum' occupation_self='Occupation' countrycit='Country'; run; proc contents data=IAT2016; run; proc means data=IAT2016; class occupation_self; var D_biep_White_Good_all; output out = Summary mean = n = / autoname; run; ... View more

I am honestly unsure how to see what my expected sample size should (I've only seen this in proc reg, proc glm, etc statements but this doesn't work since it says no observations), but it definitely should be in the thousands. I've run data from the years 2017-2020 so far and they were in the 10s of thousands for those. Someone previously told me to add the PUT function along with the formatted value in the where statement, but I'll remove it and run again! ... View more

Someone previously sent me a link to a macro to use and I didn't use it correctly because I've never heard of them before. Do I include it at the beginning of my code? Is there something that I need to change within it so it coincides with my data? ... View more

I just applied each step one after the other one: 954 data step1; 955 set IAT2016_raw; 956 where left(countrycit)='1'; 957 run; NOTE: There were 502384 observations read from the data set WORK.IAT2016_RAW. WHERE LEFT(countrycit)='1'; NOTE: The data set WORK.STEP1 has 502384 observations and 534 variables. NOTE: DATA statement used (Total process time): real time 38.80 seconds cpu time 14.09 seconds 958 data step2; 959 set step1; 960 set IAT2016_raw; 961 where occupation_self in ('29-1000','31-1000'); 962 run; NOTE: There were 9106 observations read from the data set WORK.STEP1. NOTE: There were 9105 observations read from the data set WORK.IAT2016_RAW. WHERE occupation_self in ('29-1000', '31-1000'); NOTE: The data set WORK.STEP2 has 9105 observations and 534 variables. NOTE: DATA statement used (Total process time): real time 35.55 seconds cpu time 9.37 seconds 963 data step3; 964 set step2; 965 where sex_5 in (1,2); 966 run; NOTE: There were 8364 observations read from the data set WORK.STEP2. WHERE sex_5 in (1, 2); NOTE: The data set WORK.STEP3 has 8364 observations and 534 variables. NOTE: DATA statement used (Total process time): real time 1.55 seconds cpu time 1.50 seconds ... View more

Thank you for stating this. Even if I am unable to get this important data for my thesis, I am extremely grateful for everyone that has been attempting to help me so far! ... View more

The other where statement to remove the space did not result in observations. Did I put it correctly? 925 proc import out=work.IAT2016_raw 926 datafile="C:\Users\tjoseph6\Documents\My SAS Files\IAT2016.sav" 927 dbms=sav replace; 928 run; NOTE: Variable Name Change. D_biep.White_Good_all -> D_biep_White_Good_all NOTE: Variable Name Change. D_biep.White_Good_36 -> D_biep_White_Good_36 NOTE: Variable Name Change. D_biep.White_Good_47 -> D_biep_White_Good_47 NOTE: One or more variables were converted because the data type is not supported by the V9 engine. For more details, run with options MSGLEVEL=I. NOTE: The import data set has 1051105 observations and 534 variables. NOTE: WORK.IAT2016_RAW data set was successfully created. NOTE: PROCEDURE IMPORT used (Total process time): real time 1:09.51 cpu time 25.56 seconds 929 data IAT2016; 930 set work.IAT2016_raw (keep=year birthyear sex_5 raceomb D_biep_White_Good_all countrycit 930! occupation_self politicalid_7); 931 Age=year-birthyear; 932 where left(countrycit)='1' & put( occupation_self,$OCCUPAA. ) in ('29-1000','31-1000') & sex_5 in 932! (1,2); 933 if D_biep_White_Good_all ne .; 934 if politicalid_7 eq . then delete; 935 if Age lt 16 then delete; 936 if raceomb eq . then delete; 937 label sex_5='Gender' 938 raceomb='Race' 939 D_biep_White_Good_all='Overall IAT D Score' 940 politicalid_7='Political Ideology Spectrum' 941 occupation_self='Occupation' 942 countrycit='Country'; 943 run; NOTE: There were 0 observations read from the data set WORK.IAT2016_RAW. WHERE (LEFT(countrycit)='1') and PUT(occupation_self, $OCCUPAA79.) in ('29-1000', '31-1000') and sex_5 in (1, 2); NOTE: The data set WORK.IAT2016 has 0 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 38.19 seconds cpu time 9.75 seconds 944 proc contents data=IAT2016; 945 run; NOTE: PROCEDURE CONTENTS used (Total process time): real time 0.03 seconds cpu time 0.03 seconds 946 proc means data=IAT2016; 947 class occupation_self; 948 var D_biep_White_Good_all; 949 output out = Summary 950 mean = 951 n = / autoname; 952 format occupation_self $OCCUPAA.; 953 run; NOTE: No observations in data set WORK.IAT2016. NOTE: The data set WORK.SUMMARY has 0 observations and 5 variables. NOTE: PROCEDURE MEANS used (Total process time): real time 0.05 seconds cpu time 0.04 seconds ... View more

I ran the numeric format and this was fine: birthyear=1966 num="0" num_002=. birthsex=. genderidentity="" raceomb=2 raceomb_002=. raceombmulti="." ethnicityomb=2 sex_5=2 D_biep_White_Good_all=-0.36693193 Mn_RT_all_3467=981.70833333 N_3467=120 PCT_error_3467=2.5 Order=1 labels=. Side_Good_34=1 Side_White_34=1 pct_300=0 pct_400=0 pct_2K=3.3333333333 pct_3K=0 pct_4K=0 tblack=8 tblack_1to11=8 tblack_0to10=. twhite=5 twhite_1to11=5 twhite_0to10=. att=3 att_7=3 att7=. D_biep_White_Good_36=-0.552703649 D_biep_White_Good_47=-0.18116021 Mn_RT_all_3=1145.1 Mn_RT_all_4=989.575 Mn_RT_all_6=922.8 Mn_RT_all_7=921.6 SD_all_3=458.21931086 SD_all_4=419.53630615 SD_all_6=309.96342738 SD_all_7=326.81860412 N_3=20 N_4=40 N_5=40 N_6=20 N_7=40 Mn_RT_correct_3=1145.1 Mn_RT_correct_4=960.1025641 Mn_RT_correct_6=922.8 Mn_RT_correct_7=869.42105263 SD_correct_3=458.21931086 SD_correct_4=380.76666393 SD_correct_6=309.96342738 SD_correct_7=237.90102775 N_ERROR_3=0 N_ERROR_4=1 N_ERROR_6=0 N_ERROR_7=2 countrycit=" 1 I ran the $HEX format (first time doing this so hopefully it's right) and I got this: countrycit=20202031 Based on what you said, this should be 3 spaces...? If so, I didn't receive any observations: 896 proc import out=work.IAT2016_raw 897 datafile="C:\Users\tjoseph6\Documents\My SAS Files\IAT2016.sav" 898 dbms=sav replace; 899 run; NOTE: Variable Name Change. D_biep.White_Good_all -> D_biep_White_Good_all NOTE: Variable Name Change. D_biep.White_Good_36 -> D_biep_White_Good_36 NOTE: Variable Name Change. D_biep.White_Good_47 -> D_biep_White_Good_47 NOTE: One or more variables were converted because the data type is not supported by the V9 engine. For more details, run with options MSGLEVEL=I. NOTE: The import data set has 1051105 observations and 534 variables. NOTE: WORK.IAT2016_RAW data set was successfully created. NOTE: PROCEDURE IMPORT used (Total process time): real time 1:12.75 cpu time 27.49 seconds 900 data IAT2016; 901 set work.IAT2016_raw (keep=year birthyear sex_5 raceomb D_biep_White_Good_all countrycit 901! occupation_self politicalid_7); 902 Age=year-birthyear; 903 where countrycit eq ' 1' & put( occupation_self,$OCCUPAA. ) in ('29-1000','31-1000') & sex_5 in 903! (1,2); 904 if D_biep_White_Good_all ne .; 905 if politicalid_7 eq . then delete; 906 if Age lt 16 then delete; 907 if raceomb eq . then delete; 908 label sex_5='Gender' 909 raceomb='Race' 910 D_biep_White_Good_all='Overall IAT D Score' 911 politicalid_7='Political Ideology Spectrum' 912 occupation_self='Occupation' 913 countrycit='Country'; 914 run; NOTE: There were 0 observations read from the data set WORK.IAT2016_RAW. WHERE (countrycit=' 1') and PUT(occupation_self, $OCCUPAA79.) in ('29-1000', '31-1000') and sex_5 in (1, 2); NOTE: The data set WORK.IAT2016 has 0 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 38.00 seconds cpu time 10.96 seconds 915 proc contents data=IAT2016; 916 run; NOTE: PROCEDURE CONTENTS used (Total process time): real time 0.04 seconds cpu time 0.04 seconds 917 proc means data=IAT2016; 918 class occupation_self; 919 var D_biep_White_Good_all; 920 output out = Summary 921 mean = 922 n = / autoname; 923 format occupation_self $OCCUPAA.; 924 run; NOTE: No observations in data set WORK.IAT2016. NOTE: The data set WORK.SUMMARY has 0 observations and 5 variables. NOTE: PROCEDURE MEANS used (Total process time): real time 0.05 seconds cpu time 0.03 seconds I will use the suggestions for the where statement in one moment though! ... View more

Also, this is part of what the code @Tom provided showed: raceomb=East Asian raceomb_002=. raceombmulti="." ethnicityomb=Not Hispanic or Latino sex_5=Female D_biep_White_Good_all=-0.367 Mn_RT_all_3467=981.71 N_3467=120 PCT_error_3467=2.5 Order=White+Good first labels=. Side_Good_34=Good left first Side_White_34=White left first pct_300=0.0 pct_400=0.0 pct_2K=3.3 pct_3K=0.0 pct_4K=0.0 tblack=8 tblack_1to11=8 tblack_0to10=. twhite=5 twhite_1to11=5 neutral twhite_0to10=. att=3 att_7=I slightly prefer African Americans to European Americans. att7=. D_biep_White_Good_36=-0.553 D_biep_White_Good_47=-0.181 Mn_RT_all_3=1145.10 Mn_RT_all_4=989.58 Mn_RT_all_6=922.80 Mn_RT_all_7=921.60 SD_all_3=458.22 SD_all_4=419.54 SD_all_6=309.96 SD_all_7=326.82 N_3=20 N_4=40 N_5=40 N_6=20 N_7=40 Mn_RT_correct_3=1145.10 Mn_RT_correct_4=960.10 Mn_RT_correct_6=922.80 Mn_RT_correct_7=869.42 SD_correct_3=458.22 SD_correct_4=380.77 SD_correct_6=309.96 SD_correct_7=237.90 N_ERROR_3=0 N_ERROR_4=1 N_ERROR_6=0 N_ERROR_7=2 countrycit=" 1" countryres=" 1" edu=. edu_14=. studentornot=No edunotstudent=Ph.D. edustudent=. employment="6" occuself="nul" occupation_self="29-1000" ... View more

Sorry for the long log below but I just tried it with adding two spaces, then one space, then tab, but they all stated no observations. Also, tried using "1" as well just in case I was wrong about the observation for countrycit but this didn't work either. 726 proc import out=work.IAT2016_raw 727 datafile="C:\Users\tjoseph6\Documents\My SAS Files\IAT2016.sav" 728 dbms=sav replace; 729 run; NOTE: Variable Name Change. D_biep.White_Good_all -> D_biep_White_Good_all NOTE: Variable Name Change. D_biep.White_Good_36 -> D_biep_White_Good_36 NOTE: Variable Name Change. D_biep.White_Good_47 -> D_biep_White_Good_47 NOTE: One or more variables were converted because the data type is not supported by the V9 engine. For more details, run with options MSGLEVEL=I. NOTE: The import data set has 1051105 observations and 534 variables. NOTE: WORK.IAT2016_RAW data set was successfully created. NOTE: PROCEDURE IMPORT used (Total process time): real time 1:09.24 cpu time 25.42 seconds 730 data IAT2016; 731 set work.IAT2016_raw (keep=year birthyear sex_5 raceomb D_biep_White_Good_all countrycit 731! occupation_self politicalid_7); 732 Age=year-birthyear; 733 where countrycit eq ' US' & put( occupation_self,$OCCUPAA. ) in ('29-1000','31-1000') & sex_5 733! in (1,2); 734 if D_biep_White_Good_all ne .; 735 if politicalid_7 eq . then delete; 736 if Age lt 16 then delete; 737 if raceomb eq . then delete; 738 label sex_5='Gender' 739 raceomb='Race' 740 D_biep_White_Good_all='Overall IAT D Score' 741 politicalid_7='Political Ideology Spectrum' 742 occupation_self='Occupation' 743 countrycit='Country'; 744 run; NOTE: There were 0 observations read from the data set WORK.IAT2016_RAW. WHERE 0 /* an obviously FALSE WHERE clause */ ; NOTE: The data set WORK.IAT2016 has 0 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 0.21 seconds cpu time 0.01 seconds 745 proc contents data=IAT2016; 746 run; NOTE: PROCEDURE CONTENTS used (Total process time): real time 0.07 seconds cpu time 0.01 seconds 747 proc means data=IAT2016; 748 class occupation_self; 749 var D_biep_White_Good_all; 750 output out = Summary 751 mean = 752 n = / autoname; 753 format occupation_self $OCCUPAA.; 754 run; NOTE: No observations in data set WORK.IAT2016. NOTE: The data set WORK.SUMMARY has 0 observations and 5 variables. NOTE: PROCEDURE MEANS used (Total process time): real time 0.04 seconds cpu time 0.03 seconds 755 proc import out=work.IAT2016_raw 756 datafile="C:\Users\tjoseph6\Documents\My SAS Files\IAT2016.sav" 757 dbms=sav replace; 758 run; NOTE: Variable Name Change. D_biep.White_Good_all -> D_biep_White_Good_all NOTE: Variable Name Change. D_biep.White_Good_36 -> D_biep_White_Good_36 NOTE: Variable Name Change. D_biep.White_Good_47 -> D_biep_White_Good_47 NOTE: One or more variables were converted because the data type is not supported by the V9 engine. For more details, run with options MSGLEVEL=I. NOTE: The import data set has 1051105 observations and 534 variables. NOTE: WORK.IAT2016_RAW data set was successfully created. NOTE: PROCEDURE IMPORT used (Total process time): real time 1:08.20 cpu time 25.62 seconds 759 data IAT2016; 760 set work.IAT2016_raw (keep=year birthyear sex_5 raceomb D_biep_White_Good_all countrycit 760! occupation_self politicalid_7); 761 Age=year-birthyear; 762 where countrycit eq ' US' & put( occupation_self,$OCCUPAA. ) in ('29-1000','31-1000') & sex_5 in 762! (1,2); 763 if D_biep_White_Good_all ne .; 764 if politicalid_7 eq . then delete; 765 if Age lt 16 then delete; 766 if raceomb eq . then delete; 767 label sex_5='Gender' 768 raceomb='Race' 769 D_biep_White_Good_all='Overall IAT D Score' 770 politicalid_7='Political Ideology Spectrum' 771 occupation_self='Occupation' 772 countrycit='Country'; 773 run; NOTE: There were 0 observations read from the data set WORK.IAT2016_RAW. WHERE (countrycit=' US') and PUT(occupation_self, $OCCUPAA79.) in ('29-1000', '31-1000') and sex_5 in (1, 2); NOTE: The data set WORK.IAT2016 has 0 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 38.93 seconds cpu time 7.75 seconds 774 proc contents data=IAT2016; 775 run; NOTE: PROCEDURE CONTENTS used (Total process time): real time 0.06 seconds cpu time 0.01 seconds 776 proc means data=IAT2016; 777 class occupation_self; 778 var D_biep_White_Good_all; 779 output out = Summary 780 mean = 781 n = / autoname; 782 format occupation_self $OCCUPAA.; 783 run; NOTE: No observations in data set WORK.IAT2016. NOTE: The data set WORK.SUMMARY has 0 observations and 5 variables. NOTE: PROCEDURE MEANS used (Total process time): real time 0.10 seconds cpu time 0.04 seconds 784 proc import out=work.IAT2016_raw 785 datafile="C:\Users\tjoseph6\Documents\My SAS Files\IAT2016.sav" 786 dbms=sav replace; 787 run; NOTE: Variable Name Change. D_biep.White_Good_all -> D_biep_White_Good_all NOTE: Variable Name Change. D_biep.White_Good_36 -> D_biep_White_Good_36 NOTE: Variable Name Change. D_biep.White_Good_47 -> D_biep_White_Good_47 NOTE: One or more variables were converted because the data type is not supported by the V9 engine. For more details, run with options MSGLEVEL=I. NOTE: The import data set has 1051105 observations and 534 variables. NOTE: WORK.IAT2016_RAW data set was successfully created. NOTE: PROCEDURE IMPORT used (Total process time): real time 1:09.08 cpu time 26.90 seconds 788 data IAT2016; 789 set work.IAT2016_raw (keep=year birthyear sex_5 raceomb D_biep_White_Good_all countrycit 789! occupation_self politicalid_7); 790 Age=year-birthyear; 791 where countrycit eq ' US' & put( occupation_self,$OCCUPAA. ) in ('29-1000','31-1000') & sex_5 791! in (1,2); 792 if D_biep_White_Good_all ne .; 793 if politicalid_7 eq . then delete; 794 if Age lt 16 then delete; 795 if raceomb eq . then delete; 796 label sex_5='Gender' 797 raceomb='Race' 798 D_biep_White_Good_all='Overall IAT D Score' 799 politicalid_7='Political Ideology Spectrum' 800 occupation_self='Occupation' 801 countrycit='Country'; 802 run; NOTE: There were 0 observations read from the data set WORK.IAT2016_RAW. WHERE 0 /* an obviously FALSE WHERE clause */ ; NOTE: The data set WORK.IAT2016 has 0 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 0.21 seconds cpu time 0.01 seconds 803 proc contents data=IAT2016; 804 run; NOTE: PROCEDURE CONTENTS used (Total process time): real time 0.04 seconds cpu time 0.03 seconds 805 proc means data=IAT2016; 806 class occupation_self; 807 var D_biep_White_Good_all; 808 output out = Summary 809 mean = 810 n = / autoname; 811 format occupation_self $OCCUPAA.; 812 run; NOTE: No observations in data set WORK.IAT2016. NOTE: The data set WORK.SUMMARY has 0 observations and 5 variables. NOTE: PROCEDURE MEANS used (Total process time): real time 0.06 seconds cpu time 0.06 seconds ... View more

I am not sure how to get output from the listing destination, but I found a leading space for countrycit as you stated after using the code suggested by @Tom. Updated the statement, and I will update as soon as it's done running (takes a while since the data is large) ... View more