About DavidsM

DavidsM · ‎05-17-2019

DATA HAVE; INPUT ID YEAR WEIGHT HEIGHT SMOKING EXERCISE DATELINES; 01 2000 . 175 . 1 01 2001 57 175 1 1 01 2002 . 175 . 1 01 2003 57 175 1 1 01 2004 . 175 . 1 02 2000 57 . 1 1 02 2001 . 168 . 1 02 2004 57 169 1 1 DATA HAVE; INPUT ID YEAR WEIGHT HEIGHT SMOKING EXERCISE DATELINES; 01 2000 57 175 1 1 02 2000 57 168 1 1

DavidsM · ‎05-17-2019

The are both continuous an categorical variables. The data is arranged with person Data structure before ID YEAR WEIGHT HEIGHT SMOKING EXERCISE 01 2000 . 175 . 1 01 2001 57 175 1 1 01 2002 . 175 . 1 01 2003 57 175 1 1 01 2004 . 175 . 1 02 2000 57 . 1 1 02 2001 . 168 . 1 02 2004 57 169 1 1 Data structure after(Only one observation per person with missing values for year 2000 values imputed . ID YEAR WEIGHT2000 HEIGHT2000 SMOKING2000 EXERCISE2000 01 2000 57 175 1 1 02 2000 57 168 1 1 I want to have the values for the first year imputed so that I use the information for the first year in my analysis. There many observations per person and the number of observations is not similar but I want to have one summary of imputed data for each person(One entry per person). Thank you for assistance.

DavidsM · ‎05-15-2019

Hello community, I have a very large data set with many years of repeatedly measured data an over 180 variables per observations. I want to impute missing data for the first two years but converting these variables to wide format to capture record for every time of measurement and then impute is extremely tasking and the imputations are computationally demanding. Is there any way to directly impute longitudinal data in long format using sas? I will be glad to be advised and assisted and I wish to use FCS method in the imputaion. Thank in advance

DavidsM · ‎04-07-2019

This is the log file from the code I tried. The variable Time is the follow up time but its excluded from the output data created and selection procedure is ignored. Below is the log file. NOTE: The SELECTION= option (MODEL statement) is ignored for the Fine and Gray competing-risks analysis. NOTE: SLSTAY= is ignored since SELECTION=NONE. NOTE: DETAILS is ignored since SELECTION=NONE. NOTE: Data for variable Time in the COVARIATES= data set are not copied to the OUT= data set in the BASELINE statement.

DavidsM · ‎04-06-2019

Hello our esteemed advisers, I am trying to select a parsimonious model from my predictors using Fine and Gray model and saving the output data. The problem is that SAS is telling me that the selection procedure is ignored and the time variable is excluded from the output data and I want to use the time variable in that output data set. Below is the code am trying proc phreg data=Disease plots(overlay)=cif; class Group BMI (ref='1') Smoking (ref='1') Alcohol (ref='1') Exercise (ref='1') DB (ref='1') model Time*Status(0)=BMI Smoking Alcohol Exercise HTN DB / eventcode=1; Selection=Backward Slstay=0.05 details; baseline covariates=Predictors out=Out1 cif=_all_ timelist=6 9; run; I will be glad to be advised.

DavidsM · ‎11-12-2018

The data sets are directed to the external hard drive and I have them read but plotting them is the problem. But I have not understood exactly how to increase my memsize. Which procedure do i use? Thanks.

DavidsM · ‎11-11-2018

I am using SAS 9.4 University Edition and I will take any advise you give me so that I can solve the problem. I also think visualizing reduced number of observation would be best and I was trying to reduce the data using proc KDE and save the output data but this error didn't allow. Thank for responding.

DavidsM · ‎11-11-2018

How to increase memory usage in SAS will be of good help for the start and I see if its memory problem. I think all the 3 above can solve the problem am encountering. I dont know exactly what the problem is because the data is extremity big more than 8,000,000,000 observations. If possible help me with method to increase memory and plotting all points. Thank you for the quick response and assistance.

DavidsM · ‎11-11-2018

Hello community, I am trying to save a very big data set into smaller data set so that I can draw a graph but am encountering this error "An Exception has been encountered".. I request for advise on how to solve this problem. I also have 8GB ram but am wondering why drawing graphs beyond 1,000,000 observations ends into an error ' Insufficient memory', How can I increase my memory utilization? Below is the procedure i have been running ods select none; proc kde data=Calibration; bivar x y / out=Want; run; ods select all; I will be glad to be assisted.

DavidsM · ‎11-04-2018

Am using Proc phreg like the code below. Proc phreg data=Variation; class Gender(ref='Male') INCOME(ref='HIGH'): model Time * Status (0)= Gender INCOME / rl; Selection=None details; Output Out=Variations Survival=Survest; run; How can I obtain R2 if am using proc phreg? I will be glad for your assistance.

DavidsM · ‎11-01-2018

Hello community, I am looking for ways to calculate explained variation for survival model of cox proportional Hazard regression. I request for assistance so that I can obtain (R2) for any of the common measures of variation except Schemper's R2. I will be glad to receive assistance

DavidsM · ‎10-31-2018

Thank you Ksharp for the assistance. The procedure below works and I have been able to draw one of the graphs from a large dataset. proc kde data=octane; bivar Rater Customer / plots=CONTOUR; run; There is one more assitance am requesting you to help me. The graph produced has a black back ground and I would like to change the back ground to other colors like white and make the plotted points clear. And also if possible place a line at 45 angle to indicate the straight line for a perfect calibration so that it clearly shows the devaition from the line. I have attached the output graph on this reply, I request you to check it and advise me on how to improve its appearance. I will be glad if am assisted to make it look better.

DavidsM · ‎10-28-2018

Hello my advisors, The Heat map and scatter also return the same messages of exceeded 2000000 observations. I have tried PROC KDE + BIVAR statement and I says out of memory but the procedure had started running. This out of memory problem has also prevented Heat map approach. I will be glad for additional advise.

DavidsM · ‎10-27-2018

Hello our esteemed advisers and community, I am seeking assistance about plotting graph for large data sets. I have very big data set with over 100,000,000 observations but I have tried plotting these calibration graphs and SAS returns an error of maximum observations exceeded. I tried using the option of changing maximum observations so that I can plot but still I cannot draw beyond 2,000,000 observations. I will be glad to be advised on how to handle this problem.

DavidsM · ‎10-08-2018

I am really so grateful for your assistance. Just so grateful and so thankful to you FreelanceReinhard.

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Re: imputation of cohort data in long format without converting to wid...

Re: imputation of cohort data in long format without converting to wid...

imputation of cohort data in long format without converting to wide fo...

Re: Model selection and saving probabilities using fine and gray model

Model selection and saving probabilities using fine and gray model

Re: An Exception has been encountered.

Re: An Exception has been encountered.

Re: An Exception has been encountered.

An Exception has been encountered.

Re: Calculation of explained variation for cox model

Re: imputation of cohort data in long format without converting to wid...

Re: imputation of cohort data in long format without converting to wid...

imputation of cohort data in long format without converting to wide fo...

Re: Model selection and saving probabilities using fine and gray model

Model selection and saving probabilities using fine and gray model

Re: An Exception has been encountered.

Re: An Exception has been encountered.

Re: An Exception has been encountered.

An Exception has been encountered.

Re: Calculation of explained variation for cox model

Calculation of explained variation for cox model

Re: RE: PLOTTING GRAPH FOR DATA CONTAINING MANY OBSERVATIONS

Re: RE: PLOTTING GRAPH FOR DATA CONTAINING MANY OBSERVATIONS

RE: PLOTTING GRAPH FOR DATA CONTAINING MANY OBSERVATIONS

Re: RESTRICTING RECURRENCE STATUS BASED ON TIME TIME INTERVALS BETWEE...