SAS Support Communities

kcvaldez98 · ‎05-09-2024

Hi SAS Coders: I am trying to change numeric observations into character so I can do my analysis, but it is showing blank observations for these variables: Obs fast purge language age_group sex_category ethnicity USBorn slimfast DescribeWt HomeEnv 1 . . E <11 Male NonH Life No VeryOver PrettyT 2 . . E <11 Male NonH Life No SlghtOve VeryTru 3 . . E <11 Male Hisp Miss Mis Right Missing 4 . . E <11 Female NonH Life No Right VeryTru 5 . . E <11 Male Hisp Life No SltUnder PrettyT 6 . . E <11 Female Hisp Life No Right VeryTru 7 . . E <11 Female NonH Life No Right PrettyT 8 . . E <11 Female NonH Life No SlghtOve PrettyT 9 . . E <11 Female NonH Life No SltUnder VeryTru 10 . . E <11 Female NonH Life No Right VeryTru I know the observations are in fact numeric as it says "1" and "2" in the dataset My code is this: DATA WORK.CLEANDATA; SET YRRSIMPT.import; /* Categorize age */ IF age < 11 THEN age_group = "<11"; ELSE IF age = 12 THEN age_group = "12"; ELSE IF age = 13 THEN age_group = "13"; ELSE IF age = 14 THEN age_group = "14"; ELSE IF age >= 15 THEN age_group = "14+"; ELSE age_group = "Missing"; /* Categorize sex */ IF sex = 1 THEN sex_category = "Female"; ELSE IF sex = 2 THEN sex_category = "Male"; ELSE sex_category = "Missing"; IF v4 = 1 THEN ethnicity = "Hisp"; ELSE IF v4 = 2 THEN ethnicity = "NonHisp"; ELSE ethnicity = "Missing"; /* Categorize v66 (USBorn) */ IF v66 = 1 THEN USBorn = "<1Yr"; ELSE IF v66 = 2 THEN USBorn = "1-3Yrs"; ELSE IF v66 = 3 THEN USBorn = "4-6Yrs"; ELSE IF v66 = 4 THEN USBorn = "6+Yr"; ELSE IF v66 = 5 THEN USBorn = "Life"; ELSE USBorn = "Missing"; /* Categorize v51 */ IF v51 = 1 THEN fast = "Yes"; ELSE IF v51 = 2 THEN fast = "No"; ELSE fast = "Missing"; /* Categorize v52 */ IF v52 = 1 THEN purge = "Yes"; ELSE IF v52 = 2 THEN purge = "No"; ELSE purge = "Missing"; /* Categorize v53 */ IF v53 = 1 THEN slimfast = "Yes"; ELSE IF v53 = 2 THEN slimfast = "No"; ELSE slimfast = "Missing"; IF v49 = 1 THEN DescribeWt = "VUnderWt"; ELSE IF v49 = 2 THEN DescribeWt = "SltUnder"; ELSE IF v49 = 3 THEN DescribeWt = "Right"; ELSE IF v49 = 4 THEN DescribeWt = "SlghtOver"; ELSE IF v49 = 5 THEN DescribeWt = "VeryOver"; ELSE DescribeWt = "Missing"; /* Categorize v71 (HomeEnv) */ IF v71 = 1 THEN HomeEnv = "NotTrue"; ELSE IF v71 = 2 THEN HomeEnv = "LilTrue"; ELSE IF v71 = 3 THEN HomeEnv = "PrettyTrue"; ELSE IF v71 = 4 THEN HomeEnv = "VeryTrue"; ELSE HomeEnv = "Missing"; KEEP age_group ethnicity sex_category HomeEnv purge fast USBorn DescribeWt language slimfast; RUN;

kcvaldez98 · ‎02-28-2024

1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 68 69 DATA LAB.STUDY_COHORT_2; 70 FORMAT race_eth $30.; 71 SET LAB.STUDY_COHORT; 72 73 /* Gestational diabetes */ 74 IF RFDiabGest = "True" THEN GestDiab= "Y"; 75 ELSE GestDiab= "N"; 76 77 /* Race/Ethnicity variable */ 78 IF MatRace = " " OR MatEthnicity = " " THEN race_eth=" "; 79 ELSE IF SUBSTR(MatEthnicity,1,1) = "2" THEN race_eth="Hispanic (any race)"; 80 ELSE IF SUBSTR(MatRace,2,1)="1" THEN race_eth = "Non-Hispanic White"; 81 ELSE race_eth="Non-Hispanic Non-White"; 82 83 /* Previous live births need to be converted to numeric variable */ 84 prev_alive2 = INPUT(PREV_ALIVE, 2.); 85 IF PREV_ALIVE= . THEN PREV_ALIVE = .; 86 87 /* Convert mother's height to height in inches */ 88 IF MotherHeight= . THEN Ht_inches = .; 89 ELSE Ht_inches=(INPUT(SUBSTR(MotherHeight,2,1),1.)*12)+(INPUT(SUBSTR(MotherHeight,4,2),2.)); 90 91 /* Convert prior weight to a numeric variable */ 92 IF priorweight = . THEN priorweight2 = .; /* Set to missing if unknown */ 93 ELSE priorweight2= INPUT(priorweight,4.); 94 95 /* Calculate BMI */ 96 IF priorweight2= . or Ht_inches= . THEN BMI = .; /* Set to missing if height or weight is missing */ 97 ELSE BMI = ((priorweight2)/(Ht_inches**2))*703; 98 99 /* Categorize into Obese status */ 100 IF BMI = . THEN ObesePrior = " "; /* Set to missing if BMI is missing */ 101 ELSE IF BMI < 30 THEN ObesePrior = "N"; 102 ELSE ObesePrior = "Y"; 103 104 /* Variable for preterm birth */ 105 IF EstGest > 36 THEN Preterm = "N"; 106 ELSE Preterm = "Y"; 107 108 /* Labeling new variables */ 109 LABEL GestDiab = "Gestational Diabetes" 110 race_eth = "Race/Ethnicity" 111 prev_alive2 = "Previous Live Births" 112 Ht_inches = "Mother's Height (in inches)" 113 priorweight2 = "Prior Weight Before Pregnancy" 114 BMI = "Body Mass Index" 115 ObesePrior = "Obese Prior (Y/N)" 116 Preterm = "Gestation Age Before 37 Weeks"; 117 RUN; NOTE: Character values have been converted to numeric values at the places given by: (Line):(Column). 85:7 88:8 92:8 105:8 NOTE: Numeric values have been converted to character values at the places given by: (Line):(Column). 85:39 NOTE: Invalid numeric data, MotherHeight='05:07' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012000176 MotherHeight=05:07 PriorWeight=170 PREV_ALIVE=2 RFDiabGest= EstGest=39 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=31 GestDiab=N prev_alive2=2 Ht_inches=. priorweight2=170 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=1 NOTE: Invalid numeric data, MotherHeight='05:02' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012000324 MotherHeight=05:02 PriorWeight=220 PREV_ALIVE=1 RFDiabGest=True EstGest=38 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=280 MatRace=01 M_AGE=32 GestDiab=Y prev_alive2=1 Ht_inches=. priorweight2=220 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=2 NOTE: Invalid numeric data, MotherHeight='05:01' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012000510 MotherHeight=05:01 PriorWeight=123 PREV_ALIVE=0 RFDiabGest= EstGest=39 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=20 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=123 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=3 NOTE: Invalid numeric data, MotherHeight='05:02' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012001165 MotherHeight=05:02 PriorWeight=145 PREV_ALIVE=0 RFDiabGest= EstGest=38 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=22 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=145 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=4 NOTE: Invalid numeric data, MotherHeight='05:04' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012001472 MotherHeight=05:04 PriorWeight=194 PREV_ALIVE=3 RFDiabGest= EstGest=39 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=35 GestDiab=N prev_alive2=3 Ht_inches=. priorweight2=194 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=5 NOTE: Invalid numeric data, MotherHeight='05:07' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012001710 MotherHeight=05:07 PriorWeight=123 PREV_ALIVE=0 RFDiabGest= EstGest=41 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=30 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=123 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=6 NOTE: Invalid numeric data, MotherHeight='05:04' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012001836 MotherHeight=05:04 PriorWeight=132 PREV_ALIVE=0 RFDiabGest= EstGest=40 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=30 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=132 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=7 NOTE: Invalid numeric data, MotherHeight='05:03' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012001863 MotherHeight=05:03 PriorWeight=149 PREV_ALIVE=1 RFDiabGest= EstGest=40 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=30 GestDiab=N prev_alive2=1 Ht_inches=. priorweight2=149 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=8 NOTE: Invalid numeric data, MotherHeight='04:08' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012002184 MotherHeight=04:08 PriorWeight=128 PREV_ALIVE=0 RFDiabGest= EstGest=41 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=23 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=128 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=9 NOTE: Invalid numeric data, MotherHeight='05:00' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012002326 MotherHeight=05:00 PriorWeight=160 PREV_ALIVE=0 RFDiabGest= EstGest=37 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=281 MatRace=01 M_AGE=20 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=160 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=10 NOTE: Invalid numeric data, MotherHeight='04:11' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012002393 MotherHeight=04:11 PriorWeight=122 PREV_ALIVE=8 RFDiabGest= EstGest=38 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=38 GestDiab=N prev_alive2=8 Ht_inches=. priorweight2=122 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=11 NOTE: Invalid numeric data, MotherHeight='04:11' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012002548 MotherHeight=04:11 PriorWeight=143 PREV_ALIVE=1 RFDiabGest= EstGest=37 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=28 GestDiab=N prev_alive2=1 Ht_inches=. priorweight2=143 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=12 NOTE: Invalid numeric data, MotherHeight='05:02' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012003049 MotherHeight=05:02 PriorWeight=125 PREV_ALIVE=1 RFDiabGest= EstGest=41 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=20 GestDiab=N prev_alive2=1 Ht_inches=. priorweight2=125 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=13 NOTE: Invalid numeric data, MotherHeight='04:11' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012003074 MotherHeight=04:11 PriorWeight=195 PREV_ALIVE=1 RFDiabGest= EstGest=35 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=28 GestDiab=N prev_alive2=1 Ht_inches=. priorweight2=195 BMI=. ObesePrior= Preterm=Y _ERROR_=1 _N_=14 NOTE: Invalid numeric data, MotherHeight='05:04' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012003126 MotherHeight=05:04 PriorWeight=160 PREV_ALIVE=1 RFDiabGest= EstGest=40 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=210 MatRace=01 M_AGE=23 GestDiab=N prev_alive2=1 Ht_inches=. priorweight2=160 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=15 NOTE: Invalid numeric data, MotherHeight='05:06' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012003186 MotherHeight=05:06 PriorWeight=130 PREV_ALIVE=0 RFDiabGest= EstGest=39 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=30 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=130 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=16 NOTE: Invalid numeric data, MotherHeight='05:07' , at line 88 column 8. race_eth=Non-Hispanic White ID=2012003306 MotherHeight=05:07 PriorWeight=137 PREV_ALIVE=0 RFDiabGest= EstGest=37 EstGestOb=True EstGestClin= Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=21 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=137 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=17 NOTE: Invalid numeric data, MotherHeight='05:01' , at line 88 column 8. race_eth=Hispanic (any race) ID=2012003437 MotherHeight=05:01 PriorWeight=130 PREV_ALIVE=0 RFDiabGest= EstGest=39 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=281 MatRace=01 M_AGE=16 GestDiab=N prev_alive2=0 Ht_inches=. priorweight2=130 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=18 NOTE: Invalid numeric data, MotherHeight='05:02' , at line 88 column 8. NOTE: Invalid numeric data, PriorWeight='?' , at line 92 column 8. race_eth=Non-Hispanic Non-White ID=2012003508 MotherHeight=05:02 PriorWeight=? PREV_ALIVE=3 RFDiabGest= EstGest=39 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=100 MatRace=10 M_AGE=24 GestDiab=N prev_alive2=3 Ht_inches=. priorweight2=. BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=19 NOTE: Invalid numeric data, MotherHeight='05:01' , at line 88 column 8. WARNING: Limit set by ERRORS= option reached. Further errors of this type will not be printed. race_eth=Non-Hispanic White ID=2012003665 MotherHeight=05:01 PriorWeight=180 PREV_ALIVE=1 RFDiabGest= EstGest=40 EstGestOb= EstGestClin=True Plurality=1 MatEthnicity=100 MatRace=01 M_AGE=23 GestDiab=N prev_alive2=1 Ht_inches=. priorweight2=180 BMI=. ObesePrior= Preterm=N _ERROR_=1 _N_=20 NOTE: There were 292 observations read from the data set LAB.STUDY_COHORT. NOTE: The data set LAB.STUDY_COHORT_2 has 292 observations and 20 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds user cpu time 0.01 seconds system cpu time 0.01 seconds memory 1009.37k OS Memory 23464.00k Timestamp 02/28/2024 03:40:49 PM Step Count 34 Switch Count 2 Page Faults 0 Page Reclaims 173 Page Swaps 0 Voluntary Context Switches 44 Involuntary Context Switches 0 Block Input Operations 32 Block Output Operations 280 118 119 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 129

kcvaldez98 · ‎02-28-2024

Hi SAS users! I am doing some SAS homework and ran into this warning which won't let me convert character into numeric and therefore I am unable to run half this code. My goal is for prev_alive2 to be numeric and Ht_Inches to be numeric so I can calculate the BMI so I can have the BMI to look at mothers who are obese prior to pregnancy. Let me show you my code: and please let me know where I went wrong. DATA LAB.STUDY_COHORT_2; FORMAT race_eth $30.; SET LAB.STUDY_COHORT; /* Gestational diabetes */ IF RFDiabGest = "True" THEN GestDiab= "Y"; ELSE GestDiab= "N"; /* Race/Ethnicity variable */ IF MatRace = " " OR MatEthnicity = " " THEN race_eth=" "; ELSE IF SUBSTR(MatEthnicity,1,1) = "2" THEN race_eth="Hispanic (any race)"; ELSE IF SUBSTR(MatRace,2,1)="1" THEN race_eth = "Non-Hispanic White"; ELSE race_eth="Non-Hispanic Non-White"; /* Previous live births need to be converted to numeric variable */ prev_alive2 = INPUT(PREV_ALIVE, 2.); IF PREV_ALIVE= . THEN PREV_ALIVE = .; /* Convert mother's height to height in inches */ IF MotherHeight= . THEN Ht_inches = .; ELSE Ht_inches=(INPUT(SUBSTR(MotherHeight,2,1),1.)*12)+(INPUT(SUBSTR(MotherHeight,4,2),2.)); /* Convert prior weight to a numeric variable */ IF priorweight = . THEN priorweight2 = .; /* Set to missing if unknown */ ELSE priorweight2= INPUT(priorweight,4.); /* Calculate BMI */ IF priorweight2= . or Ht_inches= . THEN BMI = .; /* Set to missing if height or weight is missing */ ELSE BMI = ((priorweight2)/(Ht_inches**2))*703; /* Categorize into Obese status */ IF BMI = . THEN ObesePrior = " "; /* Set to missing if BMI is missing */ ELSE IF BMI < 30 THEN ObesePrior = "N"; ELSE ObesePrior = "Y"; /* Variable for preterm birth */ IF EstGest > 36 THEN Preterm = "N"; ELSE Preterm = "Y"; /* Labeling new variables */ LABEL GestDiab = "Gestational Diabetes" race_eth = "Race/Ethnicity" prev_alive2 = "Previous Live Births" Ht_inches = "Mother's Height (in inches)" priorweight2 = "Prior Weight Before Pregnancy" BMI = "Body Mass Index" ObesePrior = "Obese Prior (Y/N)" Preterm = "Gestation Age Before 37 Weeks"; RUN; The dataset looks like this: Obs ID MotherHeight PriorWeight PREV_ALIVE RFDiabGest EstGest EstGestOb EstGestClin Plurality MatEthnicity MatRace M_AGE 1 2012000176 05:07 170 2 39 True 1 210 01 31 2 2012000324 05:02 220 1 True 38 True 1 280 01 32 3 2012000510 05:01 123 0 39 True 1 210 01 20 4 2012001165 05:02 145 0 38 True 1 210 01 22 5 2012001472 05:04 194 3 39 True 1 100 01 35 6 2012001710 05:07 123 0 41 True 1 100 01 30 7 2012001836 05:04 132 0 40 True 1 100 01 30 8 2012001863 05:03 149 1 40 True 1 100 01 30 9 2012002184 04:08 128 0 41 True 1 210 01 23 10 2012002326 05:00 160 0 37 True 1 281 01 20 11 2012002393 04:11 122 8 38 True 1 210 01 38 12 2012002548 04:11 143 1 37 True 1 210 01 28 13 2012003049 05:02 125 1 41 True 1 210 01 20 14 2012003074 04:11 195 1 35 True 1 100 01 28 15 2012003126 05:04 160 1 40 True 1 210 01 23 16 2012003186 05:06 130 0 39 True 1 100 01 30 17 2012003306 05:07 137 0 37 True 1 100 01 21 18 2012003437 05:01 130 0 39 True 1 281 01 16 19 2012003508 05:02 ? 3 39 True 1 100 10 24 20 2012003665 05:01 180 1 40 True 1 100 01 23 21 2012003987 05:06 178 0 39 True 1 100 01 31 22 2012004002 05:03 154 0 True 36 True 1 100 01 27 23 2012004481 04:07 131 0 40 True 1 210 01 36 24 2012004529 05:09 175 1 39 True 1 100 01 31 25 2012004620 05:08 219 2 39 True 1 210 15 22 26 2012004670 05:06 190 1 39 True 1 100 01 34 27 2012004797 05:04 145 1 40 True 1 210 01 22 28 2012005112 05:04 174 2 39 True 1 210 01 30 29 2012005419 05:05 141 0 40 True 1 100 01 29 30 2012005472 05:03 120 0 38 True 1 100 01 27 31 2012005558 05:08 261 1 39 True 1 100 01 29 32 2012005704 05:04 ? 2 40 True 1 210 01 27

kcvaldez98 · ‎12-07-2023

PROC REG DATA=WORK.FIGURE (RENAME=outcomes_adults_mental_distr='Frequent Mental Distress'n) PLOTS(ONLY) = FITPLOT; LABEL Marijuana_Use = 'Percent of People Who Used Marijuana 1+ Days out of 30 Days'; 'Linear Regression'n: MODEL 'Frequent Mental Distress'n = Marijuana_Use / CLM CLI ALPHA=0.05; TITLE "Linear Regression of Frequent Mental Distress and Marijuana Use"; ODS SELECT FitPlot; RUN;

kcvaldez98 · ‎12-07-2023

I figured it out, thank you

kcvaldez98 · ‎12-07-2023

This makes a lot more sense now, yes I was using ODS OUTPUT to create that particular dataset and I named the datasets TABLEONE TABLETWO AND TABLETHREE as part of the work library because I wanted to not confuse myself, but I guess I confused SAS communities. so that table that I presented has 4 observations so only the last one will be presented when I run that code you provided? That's interesting and I appreciate the explanation because now it's becoming clear to me what I need to do. I may be overthinking how to get the end result but that is extremely helpful!

kcvaldez98 · ‎12-07-2023

Yes, here is my code to get that table that I presented: ODS TRACE ON; PROC GLM DATA=ANOVA; CLASS Quartiles; MODEL riskfactors_quartiles = Marijuana_Use Education_Status Poverty_Percent Frequent_Mental_Dist; RUN; QUIT; ODS TRACE OFF; ODS OUTPUT ModelANOVA=TableTwo; PROC GLM DATA=ANOVA; CLASS Quartiles; MODEL riskfactors_quartiles = Marijuana_Use Education_Status Poverty_Percent Frequent_Mental_Dist; RUN; QUIT; Then I cleaned up the table and merged it with my first table which has the means and standard deviations that was presented, but I mostly used ODS OUTPUT to manipulate my tables so it has the p value.

kcvaldez98 · ‎12-07-2023

My code is: OPTIONS VALIDVARNAME=ANY; PROC REG DATA=WORK.FIGURE (RENAME = outcomes_adults_mental_distr = Frequent_Mental_Distress) PLOTS(ONLY) = FITPLOT; LABEL Marijuana_Use = 'Percent of People Who Used Marijuana 1+ Days out of 30 Days'; 'Linear Regression'n: MODEL Frequent_Mental_Distress = Marijuana_Use / CLM CLI ALPHA=0.05; TITLE "Linear Regression of Frequent Mental Distress and Marijuana Use"; ODS SELECT FitPlot; RUN; TITLE; Thank you so much! I thought there was only like two procedures but good to know that there are more!

kcvaldez98 · ‎12-07-2023

Hello! Let me see if I can explain this well. I am working on a project in my SAS class and my professor wants us to create a macro that extracts p values from our tables and use that macro to basically put in our rtf file this code: ods rtf text="Insert here an interpretation of your parameter estimates with your macro variable"; She wants us to create the macro using call syntax and it has to just be inserted into that rtf text that I provided. My p values are in a dataset called WORK.TABLETWO and it is the p values I got from using PROC GLM and using an ANOVA test. Here is my table two for reference: So I guess my professor wants the p value column to be extracted using a MACRO variable using CALL SYNTAX to use in a RTF TEXT to be inserted into our RTF File. I hope that makes sense, any advice would be helpful on how to do any of this since I am very new to macros

kcvaldez98 · ‎12-07-2023

Hi Sas coders! I create a linear regression that looks like this: I am trying to change the Frequent_Mental_Distress in the Fit plot title to say: Fit Plot for Frequent Mental Distress without any of the underscores, I tried doing IF THEN statements and renaming statements but I don't know if I can use labels to be displayed in the fit plot title. Is that possible? My label would be "Percent of people with Frequent Mental Distress" Thank you!

kcvaldez98 · ‎12-07-2023

Hi SAS Coders! I created a box plot that looks like this: My quartiles are out of order and I have tried everything. Here is my code for reference: ODS NOPROCTITLE; PROC SGPLOT DATA=WORK.FIGURE; VBOX outcomes_adults_mental_distr / GROUPORDER = DATA CATEGORY=Quartiles FILLATTRS=(COLOR=LIGHTBLUE) BOXWIDTH=0.8; TITLE BOLD "Boxplot of Quartiles of Marijuana Use and Frequent Mental Distress"; XAXIS DISPLAY=(NOLABEL) LABELATTRS=(WEIGHT=BOLD); YAXIS LABEL="Frequent Mental Distress" VALUES=(0 TO 100 BY 10) OFFSETMIN=0; XAXIS LABEL="Quartiles"; REFLINE 70 / AXIS=Y LINEATTRS=(COLOR=BLUE); REFLINE 90 / AXIS=Y LINEATTRS=(COLOR=BLUE); YAXIS GRID; INSET "Data Source: Colorado Study Data"/ POSITION=NW BORDER; RUN; How do I get it where it goes from "First Quartile, Second Quartile, Third Quartile and Fourth Quartile" ? Please advise

kcvaldez98 · ‎12-07-2023

Thank you everyone, it appears that it is working again. Thank you for all the solutions!

kcvaldez98 · ‎12-06-2023

1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; NOTE: ODS statements in the SAS Studio environment may disable some output features. 69 70 ODS RTF FILE = "/home/u63558208/Project One/CDPHE Data/5_Results/FinalProject.rtf" 71 STYLE=BARRETTSBLUE; NOTE: Writing RTF Body file: /home/u63558208/Project One/CDPHE Data/5_Results/FinalProject.rtf 72 73 74 TITLE1'Means and Standard Deviations of Demographics, Risk Factors, and Outcomes'; 75 PROC PRINT DATA=COLANLYS.TABLEONE LABEL NOOBS; 76 RUN; NOTE: There were 4 observations read from the data set COLANLYS.TABLEONE. NOTE: PROCEDURE PRINT used (Total process time): real time 0.01 seconds user cpu time 0.01 seconds system cpu time 0.00 seconds memory 1568.40k OS Memory 27812.00k Timestamp 12/06/2023 04:15:29 PM Step Count 533 Switch Count 0 Page Faults 0 Page Reclaims 88 Page Swaps 0 Voluntary Context Switches 5 Involuntary Context Switches 0 Block Input Operations 0 Block Output Operations 0 77 TITLE; 78 79 80 TITLE1'ANOVA of Demographics, Risk Factors, and Outcomes'; 81 PROC PRINT DATA = COLANLYS.TABLETWO LABEL NOOBS; 82 RUN; NOTE: There were 4 observations read from the data set COLANLYS.TABLETWO. NOTE: PROCEDURE PRINT used (Total process time): real time 0.00 seconds user cpu time 0.01 seconds system cpu time 0.00 seconds memory 766.15k OS Memory 27812.00k Timestamp 12/06/2023 04:15:29 PM Step Count 534 Switch Count 0 Page Faults 0 Page Reclaims 64 Page Swaps 0 Voluntary Context Switches 4 Involuntary Context Switches 0 Block Input Operations 0 Block Output Operations 0 83 TITLE; 84 FOOTNOTE "p-values > .05"; 85 FOOTNOTE; 86 87 88 TITLE1"Pearson's Correlation Between Demographics, Risk Factors, and the Outcome"; 89 PROC PRINT DATA=COLANLYS.TABLETHREE LABEL NOOBS; 90 RUN; NOTE: There were 4 observations read from the data set COLANLYS.TABLETHREE. NOTE: PROCEDURE PRINT used (Total process time): real time 0.01 seconds user cpu time 0.01 seconds system cpu time 0.00 seconds memory 687.53k OS Memory 27812.00k Timestamp 12/06/2023 04:15:29 PM Step Count 535 Switch Count 0 Page Faults 0 Page Reclaims 71 Page Swaps 0 Voluntary Context Switches 4 Involuntary Context Switches 0 Block Input Operations 0 Block Output Operations 0 91 TITLE; 92 93 ODS GRAPHICS ON; 94 ODS NOPROCTITLE; 95 PROC SGPLOT DATA=WORK.FIGURE; 96 VBOX outcomes_adults_mental_distr / CATEGORY=Quartiles FILLATTRS=(COLOR=LIGHTBLUE) BOXWIDTH=0.5; 97 TITLE BOLD "Boxplot of Quartiles of Marijuana Use and Frequent Mental Distress"; 98 XAXIS LABEL="Quartiles of Marijuana Use" VALUEATTRS=(WEIGHT=BOLD); 99 YAXIS LABEL="Frequent Mental Distress" VALUES=(0 TO 100 BY 10) OFFSETMIN=0; 100 REFLINE 70 / AXIS=Y LINEATTRS=(COLOR=BLUE); 101 REFLINE 90 / AXIS=Y LINEATTRS=(COLOR=BLUE) LABEL="HYPERTENSION THRESHOLD" LABELPOS=max; 102 YAXIS GRID; 103 INSET "Data Source: Colorado Study Data"/ POSITION=NW BORDER; 104 RUN; NOTE: PROCEDURE SGPLOT used (Total process time): real time 0.13 seconds user cpu time 0.06 seconds system cpu time 0.02 seconds memory 15736.25k OS Memory 40616.00k Timestamp 12/06/2023 04:15:29 PM Step Count 536 Switch Count 2 Page Faults 0 Page Reclaims 3677 Page Swaps 0 Voluntary Context Switches 466 Involuntary Context Switches 0 Block Input Operations 0 Block Output Operations 768 NOTE: There were 64 observations read from the data set WORK.FIGURE. 105 TITLE; 106 107 108 ODS NOPROCTITLE; 109 OPTIONS VALIDVARNAME=ANY; 110 PROC REG DATA=WORK.FIGURE (RENAME = outcomes_adults_mental_distr = Frequent_Mental_Distress) 111 PLOTS(ONLY) = FITPLOT; 112 LABEL Marijuana_Use = 'Percent of People Who Used Marijuana 1+ Days out of 30 Days'; 113 'Linear Regression'n: 114 MODEL Frequent_Mental_Distress = Marijuana_Use / 115 CLM 116 CLI 117 ALPHA=0.05; 118 119 TITLE "Linear Regression of Frequent Mental Distress and Marijuana Use"; 120 ODS SELECT FitPlot; 121 RUN; 122 TITLE; 123 124 ODS GRAPHICS OFF; 125 ODS RTF CLOSE; 126 127 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;

kcvaldez98 · ‎12-06-2023

Hello, SAS coders. I am creating an ODS RTF File and it shows up like this But my code is this: ODS RTF FILE = "/home/u63558208/Project One/CDPHE Data/5_Results/FinalProject.rtf" STYLE=BARRETTSBLUE; TITLE1'Means and Standard Deviations of Demographics, Risk Factors, and Outcomes'; PROC PRINT DATA=COLANLYS.TABLEONE LABEL NOOBS; RUN; TITLE; TITLE1'ANOVA of Demographics, Risk Factors, and Outcomes'; PROC PRINT DATA = COLANLYS.TABLETWO LABEL NOOBS; RUN; TITLE; FOOTNOTE "p-values > .05"; FOOTNOTE; TITLE1"Pearson's Correlation Between Demographics, Risk Factors, and the Outcome"; PROC PRINT DATA=COLANLYS.TABLETHREE LABEL NOOBS; RUN; TITLE; ODS GRAPHICS ON; ODS NOPROCTITLE; PROC SGPLOT DATA=WORK.FIGURE; VBOX outcomes_adults_mental_distr / CATEGORY=Quartiles FILLATTRS=(COLOR=LIGHTBLUE) BOXWIDTH=0.5; TITLE BOLD "Boxplot of Quartiles of Marijuana Use and Frequent Mental Distress"; XAXIS LABEL="Quartiles of Marijuana Use" VALUEATTRS=(WEIGHT=BOLD); YAXIS LABEL="Frequent Mental Distress" VALUES=(0 TO 100 BY 10) OFFSETMIN=0; REFLINE 70 / AXIS=Y LINEATTRS=(COLOR=BLUE); REFLINE 90 / AXIS=Y LINEATTRS=(COLOR=BLUE) LABEL="HYPERTENSION THRESHOLD" LABELPOS=max; YAXIS GRID; INSET "Data Source: Colorado Study Data"/ POSITION=NW BORDER; RUN; TITLE; ODS NOPROCTITLE; OPTIONS VALIDVARNAME=ANY; PROC REG DATA=WORK.FIGURE (RENAME = outcomes_adults_mental_distr = Frequent_Mental_Distress) PLOTS(ONLY) = FITPLOT; LABEL Marijuana_Use = 'Percent of People Who Used Marijuana 1+ Days out of 30 Days'; 'Linear Regression'n: MODEL Frequent_Mental_Distress = Marijuana_Use / CLM CLI ALPHA=0.05; TITLE "Linear Regression of Frequent Mental Distress and Marijuana Use"; ODS SELECT FitPlot; RUN; TITLE; ODS GRAPHICS OFF; ODS RTF CLOSE; Is there something I did wrong? I am confused it was working before but now it looks like that.

kcvaldez98 · ‎12-04-2023

Hi SAS coders, I am new to SAS and was wondering if it is possible to use labels as the variable names for a PROC REG? Here's my code: ODS NOPROCTITLE; PROC REG DATA=WORK.FIGURE (RENAME = outcomes_adults_mental_distr = Frequent_Mental_Distress) PLOTS(ONLY) = FITPLOT; MODEL Frequent_Mental_Distress = Marijuana_Use / CLM CLI ALPHA=0.05; TITLE "Linear Regression of Frequent Mental Distress and Marijuana Use"; ODS SELECT FitPlot; RUN; TITLE; The output looks like this: I want it to show that Marijuana_Use and Frequent_Mental_Distress is displayed as their labels and I also was wondering if I can delete the "Model: MODEL1" out? Any help is appreciated. Thank you!