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SAS Homework that I need a whole code for this project. The data and the project instructions are attached

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/****************************************************************************** This macro will report all variable information, the the summary of all numerical variables, and the frequency of values in every categorical variables Parameters: Dataset: name of the SAS dataset Out : the directory and the .rtf file name to store the output file; Author : ****************************************************************************** Log: ... - 05/01/2017: Added features to only report the first 10 levels when the number of levels >=100; - becomes -V3 - 11/20/2019: added a new parameter 'out='; - becomes -V4 - 10/18/2020: added original order of variables so can produce table for char variables in the original order; - 10/19/2021: edited for 2021 mid-term project ******************************************************************************/ /*-------- Start the Macro --------------------------------------------------*/ %macro DataInfo (Dataset=, out=); /****** find the levels and frequency for all character variables ************/ /* initiate these datasets to null */ data FreqFinal FreqFinal1 FreqFinal2 FreqFinal3 summ; set _null_; run; /* for all categorical variables, want frequency and % */ ods output OneWayFreqs=FreqFinal Nlevels=Nlevels; proc freq data=&Dataset nlevels order=data; table _character_/missing; /* want the freq of all character variables */ run; /*---'FreqFinal' has this structure: --- -------------------------------------------------- Table | F_Name | F_Sex | Frequency | Percent | ----------|--------|-------|-----------|---------| Table Name| Thomas | | 1 | 5.26 | Table Name| William| | 1 | 5.2 | ... Table Sex | | F | 9 | 47.37 | Table Sex | | M | 11 | 52.63 | ------------------------------------------------*/ /* --- But want this structure in report: --- ------------------------------------------------- Variable | Level | Number | Nlevels | Order | ----------|--------|----------|-----------------| Name |Thoms |1(5.26) | 19 | 1 | Name |William |1(5.26) | 19 | 2 | ... Sex |F |9(47.37) | 2 | 1 | Sex |M |11(52.63) | 2 | 2 | -----------------------------------------------*/ /* --- first, want to find out how many categorical variable and put the number to a macro variable --*/ /* want to count how may variables start with F_, therefore the number of variable in the original dataset */ data Fn; set FreqFinal (keep=F_:); /* only keep all the char variables */ run; /* -- use proc contents to get the number of variables -- */ ods output Attributes=Att; proc contents data=Fn;* out=VarN; run; data Att2; set Att(where=(Label2="Variables")); /* put the nubmer of variables into a macro variable */ call symput("VarN", nValue2); run; /*--------------------------------------------------------------------------*/ /* Now, if the values in "Table" matches the name of a variable, then put its values into a commmon new variable */ /* first, extract the variable name */ data FreqFinal1a; set FreqFinal; Variable = scan(Table,-1,' '); order = _n_; /* want the original order for report */ run; /*--------- added this to have a new column 'Nlevels', 05/01/2017 --------*/ proc sort data=FreqFinal1a; by Variable; run; data Nlevels2; set Nlevels(rename=(TableVar = Variable)); run; proc sort data=Nlevels2; by Variable; run; data FreqFinal1b; merge FreqFinal1a Nlevels2; by Variable; run; /*------------------------------------------------------------------*/ /* then, put the levels in a common varialbe called 'Level' */ data FreqFinal2; set FreqFinal1b; /* put all column names in dataset 'FreqFinal1b' starting with 'F_' to an array */ array var(&VarN) F_:; /* each variable starting with 'F_' contains its value of each level */ do i=1 to &VarN; if "F_"||Variable = vname(var(i)) then do; /* create a new variable 'Level' to house all levels of each variable */ Level = var{i}; end; end; run; /* now refine the dataset for reporting: */ data FreqFinal2a (keep=Variable Level Number Nlevels order); retain Variable Level Number Nlevels; set FreqFinal2; /* Concatenate these components: */ pct = put(Percent,4.1); Number = Frequency||' '||'('||strip(pct)||')'; label Number ='Number (%)'; run; /* --- Added this so if the Nlevels > 100, only keep the first 10 levels: 05/01/2017 --*/ data FreqFinal3; set FreqFinal2a; by Variable notsorted; if first.Variable then order2 = 1; else order2 + 1; if Nlevels > 100 then do; *Nlevels2 = ">100"; /* don't really need this line */ if order2 =100 */ end; else do; *Nlevels2 = Nlevels; /* don't really need this line */ output; end; run; /* re-order to the original order for reporting: */ proc sort data=FreqFinal3; by order; /* Not 'order2' */ run; /****** ready to report the categorical variables ****************************/ /************ Now use ods rtf to report all three tables: ********************/ OPTIONS center orientation = portrait;*landscape; title; ods noproctitle; /* want to use Tilde sign ~ as the escape character for inline editing */ ods escapechar = '~'; ods rtf file= &out style=journal3a; /* --- Title of the report: --- */ ods rtf text = "~S={just=center font=('arial', 11pt)} ~3n"; ods rtf text = "~S={just=center font=('arial', 16pt,bold) textdecoration=underline} {Information about dataset - &Dataset}"; /* --- Table 1: The features about the dataset and all variable attributes - */ ods rtf STARTPAGE = Now; ods rtf text = "~S={just=center font=('arial', 11pt)} ~2n"; ods rtf text = "~S={just=center font=('arial', 14pt,bold)} {Table 1: Metadata and Variable information in dataset - &Dataset}"; ods rtf text = "~S={just=center font=('arial', 11pt)} "; ods select all; proc contents data=&Dataset; run; /* --- Table 2: Statistics of all continuous variables --- */ ods rtf STARTPAGE = Now; ods rtf text = "~S={just=center font=('arial', 14pt,bold)} {Table 2: Summary of all numerical variables in dataset - &Dataset}"; ods rtf text = "~S={just=center font=('arial', 11pt)} "; ods select summary; proc means data= &Dataset n nmiss mean std stderr median min max maxdec=1; run; /* --- Table 3: Now report the frequency dataset FreqFinal2 ---*/ ods rtf STARTPAGE = Now; ods rtf text = "~S={just=center font=('arial', 14pt,bold)} {Table 3: Levels and frequency for all categorical variables in dataset - &Dataset}"; ods rtf text = "~S={just=center font=('arial', 11pt)} "; ods select Report; proc report data=FreqFinal3 nowd headline headskip spacing=4 style(header)={font=('arial',12pt,bold)}; column Variable Level Number Nlevels; define Variable / "Variable" order=data group style(column) = {cellwidth = 3.0in font=("arial", 11pt, bold) just=right rightmargin=0.4in}; define Level / "Levels" order = data Style(column) = {just = left cellwidth = 1.6in leftmargin=0.2in}; define Number / "n (%)" order=data style(column) = {just = center cellwidth = 1.2in rightmargin = .1in}; /* added this to report number of levels, 04/18/2017 */ define NLevels / "Number of Levels" order = data group Style(column) = {just = left cellwidth = 1.0in leftmargin=0.2in}; compute before Variable; line ' '; /* add a blank line above every variable name */ endcomp; run; /* when at least one char variable contains > 100 unique levels, will note like this: */ proc sql noprint; select max(NLevels) into :Level_max from NLevels2; quit; %if &Level_max > 100 %then %do; ods rtf text = " "; ods rtf text = "~S={font = ('arial',9pt, bold) just = left} Note:"; ods rtf text = "~S={font = ('arial',9pt) just = left} When number of unique levels in a variable is >=100, only report the first 10 levels;"; %end; /*-------------------------------------------------------------------------------*/ ods rtf close; %mend; /*------------ The end of the Macro ---------------------------------------------*/ /*--- test this macro: ---*/ *%DataInfo (dataset=sashelp.class, out="/folders/myfolders/my SAS results/Dataset info and summary of SAS dataset &Dataset (&sysdate9).rtf"); /* Note: this sashelp.class dataset has no "label, formate" information */
/*~~~ 10/19/2021: ~~~*/ /******************************************************************************* How to use the 'Data info and summary macro - V4 (for SPS course 2021).sas': ******************************************************************************/ /*--- 1. First save that Macro to a folder and do the following: ---*/ /*--- 2. Invoke the macro now: ---*/ /*-----------------------------------------------------------------------------*/ /* - In SAS Studio, use %include to run the .sas file in the background: */ %include "/home/ /SAS class 2021 fall/Mid-term/ Data info and summary macro - V4 (for SPS course 2021).sas"; /*-----------------------------------------------------------------------------*/ /*--- 3. Now use the macro: ------*/ /*-----------------------------------------------------------------------------*/ /*--- Here use the SAS build-in dataset 'class' ---*/ %DataInfo (Dataset=sashelp.class, /* Provide the location and the name of the report (a .rtf file): */ /* Note: this directory is in cloud if you are using SAS OnDemand */ out="/home/ /SAS class 2021 fall/Mid-term/ Dataset info and summary of SAS dataset sashelp.class.rtf"); /* After running this, go to the folder and find the .rtf report, download it to your local computer, open it in MS Word to view results. */ /*-----------------------------------------------------------------------------*/ /*--- Other form of usage: -------*/ /* If want a subset of 'Class' */ *%DataInfo (Dataset=sashelp.class(keep=Name Age), out="/home/ /SAS class 2021 fall/Mid-term/ Dataset info and summary of SAS dataset sashelp.class-2.rtf"); /* If want a subset of 'Class' */ *%DataInfo (Dataset=sashelp.class(where=(Sex='F')), out="/home/ /SAS class 2021 fall/Mid-term/ Dataset info and summary of SAS dataset sashelp.class-3.rtf"); /* another SAS dataset, > 5k obs */ *%DataInfo (Dataset=sashelp.heart, out="/home/ /SAS class 2021 fall/Mid-term/ Dataset info and summary of SAS dataset sashelp.heart.rtf"); /* there is no categorical variable, will have empty table */ *%DataInfo (Dataset=sashelp.air, out="/home/ /SAS class 2021 fall/Mid-term/ Dataset info and summary of SAS dataset sashelp.air.rtf"); /* another SAS dataset, > 70k obs, many unique levels, will only report the first 100 levels for each variable: */ /* - Large data, may run for a while: */ *%DataInfo (Dataset=sashelp.ztc, out="/home//SAS class 2021 fall/Mid-term/ Dataset info and summary of SAS dataset sashelp.ztc.rtf"); /*----------------------------------------------------------------------------*/
Project instruction Original column Original column name New column name (SAS V7 names) New column values Label Comments A Patient ID Patient_ID as original Patient ID character B Age at Diagnosis (yrs) Age as original but should be numeric numerical C Date of Diagnosis (2 digit month/2digit dat/4 digit year Date_of_Dx as original Date of Dx numerical D Sex (M/F) Sex F, M E ECOG PS (0-4, or U for unknown) ECOG_PG 0,1,2,3,4 ECOG Performance numerical; 'U' or 'unknown' should be set to missing F Any prior or concurrent cancers (Y/N). If yes, describe Prior_or_concurrent_cancers N,Y 'U' should be set to missing; Others should extract the first letter and upcase it; G History of solid organ transplant or autoimmune disorder (Y/N/Unk) Solid_organ_transplant N,Y,U H History of allogeneic stem cell transplant (Y/N/Unk) Allogeneic_stem_cell N,Y,U I On Immunosuppressors? (Y/N/Unk) Immunosuppressors N,Y,U J If on immunosuppressors, please list. K Classified as PTLD (Y/N) PTLD N,Y L If PTLD, 1=monomorphic, 2=polymorphic M Histology (1=DLBCL, 2=MZL, 3=other - specify) Histology DLBCL,MZL,Other 1=DLBCL, 2=MZL, 3=Other, 'U' set to missing N If other, specify O If DLBCL, COO (1=Germinal Center (GC), 2=Non-GC (nonGC), 3=Unknown, Other) COO 1_GC, 2_non-GC, 3_Other 1=1_GC, 2=2_non-GC, 3=Other P CMYC >40% by IHC (1=y, 2=n, 3=unknown) cMyc >40%, ≤40% 1= >40%, 2= ≤40%, 3 set to missing Q BCL2-positive >50% by IHC (1=y, 2=n, 3=unknown) BCL2 >50%, ≤50% 1= >50%, 2= ≤50%, 3 set to missing R CMYC FISH translocated (1=y, 2=n, 3=unknown) cMyc_Fish N,Y S BCL2 translocated by FISH (1=y, 2=n, 3=unknown) BCL2_Fish N,Y 1=Y, 2=N, 3 set to missing T BCL6 IHC (1=Pos, 2=Neg, 3=Unk) BCL6 Pos, Neg 1=Pos, 2=Neg, 3 set to missing U MUM1 (1=Pos, 2=Neg, 3=Unk) MUM1 Pos, Neg 1=Pos, 2=Neg, 3 set to missing V CD5 (1=Pos, 2=Neg, 3=Unk) CD5 Pos, Neg 1=Pos, 2=Neg, 3 set to missing W CD10 (1=Pos, 2=Neg, 3=Unk) CD10 Pos, Neg 1=Pos, 2=Neg, 3 set to missing X CD20 positive (1=Pos, 2=Neg, 3=Unk) CD20 Pos, Neg 1=Pos, 2=Neg, 3 set to missing Y Ki67 (%) Z EBER (1=Pos, 2=Neg, 3=Unk) EBER Pos, Neg 1=Pos, 2=Neg, 3 set to missing AA EBV PCR serum (1=Pos, 2=Neg, 3=Unk) AB If pos, viral load AC EBV PCR CSF (1=Pos, 2=Neg, 3=Unk) AD if pos, viral load AE Brain parenchyma involved (Y/N/) Brain_parenchyma N,Y AF If parenchyma involved, 1= single site OR 2 = > single site Parenchyma_sites Single site, >Single site 1=Single site, 2= >Single site AG Specify parenchyma locations (1=temporal, 2=frontal, 3=parietal, 4=occipital, 5=brainstem, 6=thalamus, 7=cerebellum, 8=corpus callosum, 9=basal ganglia, 10=nos, 11=pons AH CSF involved (Y/N/Unknown) CSF N,Y 'M' or 'U' set to missing AI Spinal cord involved (Y/N/Unknown) Spinal_cord N,Y 2 should be N AJ Eyes involved (Y/N/Unknown or unchecked) Eye N,Y 2 should be N AK Did patient relapse after (or refractory to) initial therapy: (Y/N)? Relapse N,Y AL If YES relapse or refractory, list the date (s). (2 digit month/2 digit date/4 digit year) AM Date of last follow-up (2 digit month/2 digit date/4 digit year) AN Patient alive (Y/N) OS_event 0, 1 Overall Survival Event numerical; Y,y = 1 N,n = 0 AO If applicable, date of death (2 digit month/4 digit year) AP Lenth of Followup (mos) AQ PFS (mos) PFS_mo as original but should be numeric Progression-free Survival (months) numerical AR OS (mos) OS_mo as original Overall Survival (months) numerical Project Instruction: Due: 03Nov2021, 3:30pm, don't be late! This mid-term project is NOT a group project, please do NOT share ideas or codes with your peers! **************************************************************************************************** The data were from patients with Primary CNS Lymphoma (PCNSL). They are EBV positive or EBV negative as determined by EBER staining (column Z: Pos = Positive; Neg = Negative; Unk = Unknown). For this Mid-term project, please: 1. Import the 'Raw data' worksheet in this Excel file to create a SAS dataset (raw SAS dataset); Don't edit the raw data in the original Excel file in any way! 2. In ONE and only one Data Step, write SAS codes to clean the raw data to create a clean SAS dataset according to the requirements as listed below: - The original column positions and column names are in column A and B here, respectively. Please create new variable for each column with new column name as listed here in 'New column name' (column C); If it is blank in 'New column name', don't need to do anything with that original column; - Each new column takes the values from the corresponding original column but re-coded as shown in column D: 'New column values' (case sensitive) based on instruction in column E: 'Comments' ; - Want permanent lable for some of the new variables as listed in column E: 'Label' , e.g.: 'OS_mo' as this: 'Overall Survival (months)', etc; - Create a new variable called 'Age_group' as this: if younger than 18 (not including 18), then coded as '< 18'; if between 18 - 65 (includes 18 but excludes 65), then coded as '18 - 65', if older than 65 (inclusive), then coded as '>= 65', if age is missing then coded as a character missing; - Create a new variable called 'Days_to_end' by calculating 'Days to end of study' as this: from Date of Diagnosis to the date Oct. 15, 2021 (inclusive); - If there are any other requirements not mentioned in this instruction, please use common sense and make judgement yourself; - Save the cleaned SAS dataset with its new variables only to a permanent library, for example: '.../Mid-term project' to be used for later Final-term project; 3. Use the Macro I provided [in 'Data info and summary macro - V4 (for SPS course 2021).sas' file] to produce one rtf files: summarizes only the new variables (as appeared in 'New column name' column here) in the cleaned SAS dataset; 4. All your SAS codes, including the Macro run, should be in ONE .sas file. 5. Submit your .sas file and the final SAS dataset (cleaned SAS dataset) containing only the new variables and all their observations; Also submit the rtf summary files; 6. So there are total of 3 files you should submit to finalize your mid-term project. Please include your CWID in the file names and name each of your 3 files as these: Mid-term project_your CWID.sas Cleaned data_your CWID.sas7bdat Sumamry of cleaned data_your CWID.rtf **************************************************************************************************** ------- Bonus point (2 points towards your final grade of this course): --------------------------------------------------------------------- The Macro I provided is not able to produce summary statistics for character variable whose name is not a V7 SAS name. If you can modify the Macro so that when you use it on the raw SAS dataset to produce the 'Summary of raw data_your CWID.rtf' file, you see all the original variables names (non-V7 names, with options validvarname=any, which is the default now) in the .rtf file tables with their correct summary statistics. DON'T change the default 'validvarname' option in your SAS Studio! In other words, your modified Macro should work on any variable names. In the log with the Macro, write what you did to the Macro. Submit two file: this modified Macro as 'Data info and summary macro - V4 (for SPS course 2021)_your CWID.sas' AND the new .rtf file for raw SAS dataset as: Summary of raw data_your CWID (for bonus point).rtf ------------------------------------------------------------------------------------------------------------------------------------------------------------------ - Dr. Zhengming Chen Oct 2021 Raw data PCNSL raw data Only if EBER =1 (positive) Patient ID Age at Diagnosis (yrs) Date of Diagnosis (2 digit month/2digit dat/4 digit year Sex (M/F) ECOG PS (0-4, or U for unknown) Any prior or concurrent cancers (Y/N). If yes, describe History of solid organ transplant or autoimmune disorder (Y/N/Unk) History of allogeneic stem cell transplant (Y/N/Unk) On Immunosuppressors? (Y/N/Unk) If on immunosuppressors, please list. Classified as PTLD (Y/N) If PTLD, 1=monomorphic, 2=polymorphic Histology (1=DLBCL, 2=MZL, 3=other - specify) If other, specify If DLBCL, COO (1=Germinal Center (GC), 2=Non-GC (nonGC), 3=Unknown, Other) CMYC >40% by IHC (1=y, 2=n, 3=unknown) BCL2-positive >50% by IHC (1=y, 2=n, 3=unknown) CMYC FISH translocated (1=y, 2=n, 3=unknown) BCL2 translocated by FISH (1=y, 2=n, 3=unknown) BCL6 IHC (1=Pos, 2=Neg, 3=Unk) MUM1 (1=Pos, 2=Neg, 3=Unk) CD5 (1=Pos, 2=Neg, 3=Unk) CD10 (1=Pos, 2=Neg, 3=Unk) CD20 positive (1=Pos, 2=Neg, 3=Unk) Ki67 (%) EBER (1=Pos, 2=Neg, 3=Unk) EBV PCR serum (1=Pos, 2=Neg, 3=Unk) If pos, viral load EBV PCR CSF (1=Pos, 2=Neg, 3=Unk) if pos, viral load Brain parenchyma involved (Y/N/) If parenchyma involved, 1= single site OR 2 = > single site Specify parenchyma locations (1=temporal, 2=frontal, 3=parietal, 4=occipital, 5=brainstem, 6=thalamus, 7=cerebellum, 8=corpus callosum, 9=basal ganglia, 10=nos, 11=pons CSF involved (Y/N/Unknown) Spinal cord involved (Y/N/Unknown) Eyes involved (Y/N/Unknown or unchecked) Did patient relapse after (or refractory to) initial therapy: (Y/N)? If YES relapse or refractory, list the date (s). (2 digit month/2 digit date/4 digit year) Date of last follow-up (2 digit month/2 digit date/4 digit year) Patient alive (Y/N) If applicable, date of death (2 digit month/4 digit year) Lenth of Followup (mos) PFS (mos) OS (mos) C2385 72 7/11/18 F 1 N N N N N 1 2 2 1 2 2 1 1 2 2 1 90 2 2 3 Y 2 2 Y N N N 4/2/20 Y 20 20 20 C1632 74 7/18/16 F 3 N N N N N 1 2 1 1 1 2 2 1 2 2 1 100 2 2 2 Y 1 3 U N U Y 10/11/16 11/26/16 N 11/26/16 4 2 4 C2975 78 10/4/19 F 1 N N N N N 1 1 3 1 3 3 1 1 2 1 1 90 2 3 3 Y 2 1 N N U N 4/8/20 Y 5 5 5 C3073 62 12/20/19 F 0 N N N N N 1 1 2 2 2 2 1 1 2 1 1 90 2 3 3 Y 2 2 N N U N 5/14/20 Y 5 5 5 C2838 84 6/5/19 F 2 N N N N N 1 1 1 1 2 2 1 1 2 1 1 80 2 3 3 Y 1 3 U N U N 10/26/19 N 10/26/19 4 4 4 C736 9/16/13 F 1 Y, hx breast cancer N N N N 1 3 3 1 2 2 1 1 2 2 1 90 2 3 3 Y 2 3 N N N Y 7/1/14 9/30/14 Y 12 10 12 C3054 60 10/17/19 F 1 N N N N N 1 1 1 1 2 2 1 1 2 1 1 90 2 2 3 Y 1 2 N N N N 5/22/20 Y 7 7 7 C24 68 9/30/10 M 1 N N N N N 1 3 3 1 3 3 1 1 2 2 1 70 3 3 3 N N N U N 9/27/13 Y 36 36 36 C2826 76 4/25/19 M 2 N N N N N 1 2 1 1 2 2 1 1 2 2 1 90 2 3 3 Y 1 10 U N N Y 10/29/19 6/18/20 Y 14 6 14 C2394 62 3/9/18 M 2 N N N N N 1 3 3 3 3 3 3 3 3 3 1 U 3 3 3 Y 2 2 N N N N 7/23/18 Y 4 4 4 C2959 31 6/12/19 M 1 N N N N N 1 2 2 1 2 2 2 2 2 2 1 90 1 2 3 Y 2 5 N N U N 4/6/20 Y 10 1- 10 C1052 54 9/22/14 M 1 N N N N N 1 2 3 3 2 2 1 1 2 2 1 50 2 3 3 N Y N U N 7/15/16 Y 22 22 22 C2563 54 10/18/18 M 2 N N N N N 1 2 1 1 2 2 1 1 2 2 1 95 3 3 3 Y 2 3 N N N N 3/19/20 Y 17 17 17 C2492 53 7/6/18 M 2 N N N N N 1 2 2 1 2 1 2 1 1 2 1 80 2 2 2 Y 2 5 N N N Y 4/23/19 5/2/19 Y 10 10 10 C2698 55 3/12/19 M 1 Y, thymoma N N N N 1 2 1 1 2 2 1 1 1 2 1 90 2 2 3 Y 2 5 U N U N 6/5/20 Y 15 15 15 C2833 52 5/7/19 M 2 N N N N N 1 1 2 2 2 2 1 1 2 1 1 90 2 3 3 Y 2 2 U U U N 5/28/20 Y 13 13 13 C1788 56 1/17/17 M 0 N N N N N 1 2 1 1 2 2 1 1 2 2 1 80 2 2 3 Y 2 5 N N Y N 6/28/17 Y 5 5 5 C2482 54 9/27/18 M 1 N N N N N 1 3 3 3 3 3 3 3 2 1 1 U 3 2 3 Y 2 5 Y N N N 1/28/20 Y 16 16 16 Chicago1 84 10/20/09 M 3 Y, remote history of colon cancer in 1977 s/p resection and adjuvant chemotherapy n n n 1 1 3 1 3 3 1 1 1 1 1 u 3 1
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