Hi,  I am having an issue with this problem where I can't set the reference group. I am trying to get Odds Ratios for my project. I have a variable called Timeline that is divided into four different timeframes: All of 2019, and the first three quarters of 2020. I am trying to compare the each of the three quarters of 2020 to all of 2019 to see if there are any notable differences. The first variable I wanted to compare is Ethnicity. Ethnicity is made up of three subgroups of Hispanic/Latino, Non-Hispanic, and Missing. This is the table I am hoping to fill in:      Here is what I have so far:   proc logistic data= caphs12 descending ; class Ethnicity (ref='1') Timeline (ref='1') / param=ref ; model ethnicity = timeline; run; However, I get this error in the log and I cannot fill in for a different reference group:  NOTE: The REF= option for the response variable is ignored. NOTE: PROC LOGISTIC is fitting the cumulative logit model. The probabilities modeled are summed over the responses having the lower Ordered Values in the Response Profile table. NOTE: Convergence criterion (GCONV=1E-8) satisfied. Is there anything I can do here to change the reference group or am I thinking about this in the wrong way?    ... View more

Hi. I was wondering if someone could help me with my code. Here it is: data 6; set 5; if Q34 = "White" then Race = 1; if Q34 = "Black or African American" then Race = 2; if Q34 = "Asian" then Race = 3; Else Race = 4; run; However, in the proc print, I have noticed it does not work correctly as you can see here:    White should be 1 under race but it comes up as 4, do you know why this is?   ... View more

I have been working on this homework assignment all day and still have three questions I just cannot solve: 1)  There is a data file called VIRUS_PROLIF. Three variables: SAMPLE_NUMBER CELL_TYPE, and COUNT.  COUNT is a value for the initial count of the number of virions in a cell.  If we assume that the virions replicate at a rate such that the total number of virions will increase by 10% per minute, write the SAS code using DO UNTIL to calculate how long one would predict it would take (in minutes) for the number of virions to exceed 100,000 for each cell. Then, write the SAS code using a data step and accumulating variables to calculate the minimum, maximum, and average time to exceed 100,000 virions for the cells of each CELL_TYPE. Here is what I have for that one:   data VIRUS_PROLIF2; set VIRUS_PROLIF;    do until(COUNT>100000);       Count+(Count*.01);    end; run; proc sort data=VIRUS_PROLIF2 out=VIRUS_PROLIF3; by SAMPLE_NUMBER CELL_TYPE COUNT; run;   data CELL_TYPE_DATA (keep = SAMPLE_NUMBER CELL_TYPE COUNT n_cell_type min_cell_type max_Cell_type avg_cell_type sum_Cell_type);       set Virus_Prolif3;       by SAMPLE_NUMBER CELL_TYPE COUNT;       retain min_cell_type max_Cell_type sum_Cell_Type n_Cell_type;       if first.Cell_Type then do;             min_Cell_type = Cell_Type;             max_Cell_Type = Cell_Type;              sum_Cell_Type = 0;             n_Cell_TYPE = 0;             end;       sum_Cell_TYPE = sum(sum_Cell_TYPE, Cell_TYPE);       n_CELL_TYPE = sum(n_CELL_TYPE, 1);       min_CELL_TYPE = min(min_CELL_TYPE, CELL_TYPE);       max_CELL_TYPE = max(max_Cell_TYPE, CELL_TYPE);       avg_CELL_TYPE = sum_CELL_TYPE / n_CELL_TYPE;                if last.CELL_TYPE; run;   2. There is  data set 'HW3_Items'  contains the students' answers to a 25-question test (variables = answer_01 to answer_25).  On each student's observation, we also have variables for the correct answers (variables = correct_01 to correct_25).  Write a data step in which you will use arrays and a DO loop to determine each student's score on the test (1 point for each correct answer). Here is what I have for that:  data HW3_ITEMS2; Set HW3_ITEMS;       array Answer {25} answer_01 - answer_25;       array Correct_Answer {25} correct_01 - correct_25;       array Answer_Correct {25} Answer_correct_01 - Answer_correct_25;    do x = 1 to 25;  if Answer[X] - Correct_Answer[X] = 0 then Answer_Correct[X] = 1 + x ;  else Answer_Correct[X] = 0;       end;   run;   proc print data=HW3_ITEMS2; run;   3. Last one is looking at overweight and normal weight individuals using data set sashelp.heart and I write the SAS code  to test whether the mean cholesterol level for normal weight subjects differed significantly from that of overweight subjects. I know that it is a ttest. But every time I try to do proc ttest data=sashelp.heart; class Weight_Status; var Chol_STATUS; run; There is an error and I am not sure why or how to fix it.    Please advise! Any advice would be greatly appreciated.  ... View more

I am so lost with this homework assignment but hopefully this will be the last question! The problem instructs us to Use a DO loop and the SUBSTR function to write the SAS code (a complete SAS data step) that would do the same thing as ANYSPACE Function. We have to use two different statements one with a do index and another with a do while. I am just working on the first one for now and made a fake data set. This is what I have but it is completely wrong: data Question4; length City $10; input City $; datalines; New York New Mexico Las Vegas ; run; data new2; set Question4 (drop = x y); do x = 1 to 3; y = substr(City,x,4); y = ANYSPACE; end; run; Proc Print data=new2; run;   What should I be focusing on to correct it? ... View more

Here is the Problem:  Assume you have a SAS data set (called CLAIMS) that contains pharmacy claims. Each claim should be uniquely identified by the patient's identification number (ID_NUM) and a transaction number (Claim_Num). (E.g., patient 001 should not have more than one record with Claim_Num = 123).  You want to be able to inspect any claims for which there are possible duplicate records.  Write the SAS code to separate the observations into 2 new SAS data sets.  One data set will hold all the observations where the combination of ID_NUM and Claim_Num are unduplicated (that is, there is only one claim with a particular ID_NUM and Claim_Num combination), and a second data set that will hold all the records (including the first) where there are duplicates of Claim_Num for a given ID_NUM.  (HINT: you will need to use first. and last. to do this). Here is what I have:   proc sort data=CLAIMS;        by ID_NUM CLAIM_NUM; run;   data CLAIMS1 Claims2;        set CLAIMS;        by ID_NUM CLAIM_NUM;        if first.ID_NUM = 1; Output Claims1;        if first.ID_NUM = 1 and last.ID_NUM = 1; Output Claims2; run;   I know this is wrong because I tried  a sample data set and there was no output for claims2. I think the error is first.id_num being = to 1 in both cases but I just can't think of how to properly separate the two sets of data. If anyone can help me figure out this problem, it would be greatly appreciated. Thank you.  ... View more

Have a final next week and I am not sure how to answer this question:  Assume you have a SAS data set called 'GPA_DATA' that contains the variables STUDENT_NUM SCHOOL GRADE GENDER and GPA. Write all of the SAS code necessary to find the minimum, maximum and average GPA separately for each combination of gender, school and grade. You must use accumulating variables to accomplish all of this (NOT Proc Means).    Here is the code I have so far (I added notes to help me stay oriented). Am I on the right track? Do I need to add anything else? :   data GPA_Data2; set GPA_DATA; where STUDENT_NUM ne . and Gender ne '' and Grade ne . and SCHOOL ne '' and GPA ne .; run;   proc sort data=GPA_DATA2 out=GPA_DATA3; by STUDENT_NUM SCHOOL GRADE GENDER GPA; run;   data NEW_GPA_DATA (keep = STUDENT_NUM SCHOOL GRADE GENDER n_gpa min_gpa max_gpa avg_gpa sum_gpa); set GPA_DATA3; by STUDENT_NUM SCHOOL GRADE GENDER GPA; retain min_gpa max_gpa sum_gpa n_gpa; if first.STUDENT_NUM then do; min_gpa = GPA; * Since we sorted in ascending order the first record will have the min GPA.; max_gpa = GPA; * After this we will look for larger GPAs.; sum_GPA = 0; n_GPA = 0; end; sum_gpa = sum(sum_gpa, GPA); n_gpa = sum(n_gpa, 1); max_gpa = max(max_gpa, GPA); avg_gpa = sum_gpa / n_gpa; * Do not have to worry about divide by zero since we added 1 three lines up.; if last.STUDENT_NUM; run;   proc print data=NEW_GPA_DATA; run;     ... View more