About MSALKAR

MSALKAR · ‎11-17-2017

Hello, Below is my code and output that I am getting from the code. My main independent variable is race and it has 2 levels(Hispanics and others). However, even after including the class statement, i do not get the estimates for the sublevels of any variable such as race, region, sex etc. Can you please tell me why so? PROC SURVEYREG DATA=MEPS.finalxx; weight PERWT15F; Strata VARSTR; Cluster VARPSU; class REGION15(ref="1") sex(ref="1") RACE(ref="1") MARRY15X(ref="1") EDUYRDG(ref="1") TMTKUS42 (ref="1")chronic (ref="1")/ param=ref; MODEL MPR= REGION15 sex RACE MARRY15X EDUYRDG TMTKUS42 AGE15X chronic FAMINC15 TOTAL_COST TTLP15X; domain race=1; RUN; Please see the attachment for the result I am getting. Thank you.

MSALKAR · ‎11-09-2017

Sorry, yes cost is my dependent variable. Also, as per your suggestion i put the subject variables into my class statement. I still have the following warning: NOTE: Class levels for some variables were not printed due to excessive size. WARNING: The negative of the Hessian is not positive definite. The convergence is questionable. WARNING: The procedure is continuing but the validity of the model fit is questionable. WARNING: The specified model did not converge. WARNING: Negative of Hessian not positive definite. this is my code: proc genmod data=MEPS.MERGEDX; class VARPSU varstr; MODEL COST=REGION15 AGE15X SEX RACETHX MARRY15X EDUYRDG TMTKUS42 TTLP15X INSCOV15 / DIST=GAMMA LINK=LOG; weight PERWT15F; repeated subject =VARPSU(VARSTR); run; Shouldn't the class statement only include categorical variables? Varstr is continuous (it is the strata variable). I am very confused as to what the problem is. Also, my earlier question was that since cost is not normally distributed so we use GLM model, however since I am using MEPS dataset which has complex sampling design, so can SAS account for complex sampling design (using strata and cluster) using proc genmod or should I use any other software? Sorry my questions may be silly, but I am new to this. Thank you.

MSALKAR · ‎11-09-2017

Hello, I am trying to use proc genmod for cost as my independent variable. here is my code; proc genmod data=MEPS.MERGEDX; class VARPSU(REF="1") REGION15(REF="1") SEX(REF="1") RACETHX(REF="1") MARRY15X(REF="1") TMTKUS42(REF="1") INSCOV15(REF="1") / PARAM = REF; MODEL COST=REGION15 AGE15X SEX RACETHX MARRY15X EDUYRDG TMTKUS42 TTLP15X INSCOV15 / DIST=GAMMA LINK=LOG; weight PERWT15F; repeated subject =VARPSU(VARSTR); run; I get the error : ERROR: Nesting of continuous variable not allowed. I am using the MEPS dataset. Also can proc genmod in SAS account for complex sampling designs? I know it accounts for in the above procedure but I just want to double check and see if it is possible or if I need to use STATA. Thank you.

MSALKAR · ‎03-08-2017

Hello, is there any way of treatming missing values in the dataset? I have a lot of missing values because of which my results are not reliable. SAS shows me that 71% of the data is missing, which is a large number. Pleas elet me know how this can be solved.

MSALKAR · ‎03-06-2017

I see that there is a problem with these lines use monika.covar; read all var _num_ into V; use monika.cont1; read all var _num_ into DC1DB; use monika.cont2; read all var _num_ into DC2DB; use monika.cont3; read all var _num_ into DC3DB; use monika.cont4; read all var _num_ into DC4DB; use monika.cont5; read all var _num_ into DC5DB; use monika.cont6; read all var _num_ into DC6DB; My log states that all of the above datasets do not have numeric variables. Is there a way to code the above same code for categorical variables? Please let me know. ##- Please type your reply above this line. Simple formatting, no attachments. -##

MSALKAR · ‎03-06-2017

This is the error I can see in my log. I am still not understanding where the error is. Let me know what else you need inroder to help me fix this problem. Thank you ERROR: (execution) Matrix has not been set to a value. operation : * at line 17659 column 121 operands : DC4DB, V DC4DB 0 row 0 col (numeric) V 15 rows 15 cols (numeric) statement : ASSIGN at line 17659 column 111

MSALKAR · ‎03-03-2017

Hello, I keep getting these two error messages when I run my simulation. I cannot figure out where the error is. I am just posting some part of my code where I feel there may be an error. I know the data looks long but it is pretty much just same line with different numbers. So please go through. If required I will post the complete code. Thank you. ERROR: (execution) Matrix has not been set to a value. ERROR: No numeric variables in the dataset data monika.combined; set monika.combined; %let newvars= &group1 &group2 &group3 &group4 &group5 &group6; array newcoefsa (&k) &group1 &group2 &group3 &group4 &group5 &group6; array x0a(&k) &wgroup1 &wgroup2 &wgroup3 &wgroup4 &wgroup5 &wgroup6; array x1a(&k) &mgroup1 &wgroup2 &wgroup3 &wgroup4 &wgroup5 &wgroup6; array x2a(&k) &mgroup1 &mgroup2 &wgroup3 &wgroup4 &wgroup5 &wgroup6; array x3a(&k) &mgroup1 &mgroup2 &mgroup3 &wgroup4 &wgroup5 &wgroup6; array x4a(&k) &mgroup1 &mgroup2 &mgroup3 &mgroup4 &wgroup5 &wgroup6; array x5a(&k) &mgroup1 &mgroup2 &mgroup3 &mgroup4 &mgroup5 &wgroup6; array x6a(&k) &mgroup1 &mgroup2 &mgroup3 &mgroup4 &mgroup5 &mgroup6; xb0=intercept; xb1=intercept; xb2=intercept; xb3=intercept; xb4=intercept; xb5=intercept; xb6=intercept; * perform white to minority variable distribution switches; do i=1 to &k; xb0=xb0+x0a(i)*newcoefsa(i); xb1=xb1+x1a(i)*newcoefsa(i); xb2=xb2+x2a(i)*newcoefsa(i); xb3=xb3+x3a(i)*newcoefsa(i); xb4=xb4+x4a(i)*newcoefsa(i); xb5=xb5+x5a(i)*newcoefsa(i); xb6=xb6+x6a(i)*newcoefsa(i); end; pred0=exp(xb0)/(1+exp(xb0)); pred1=exp(xb1)/(1+exp(xb1)); pred2=exp(xb2)/(1+exp(xb2)); pred3=exp(xb3)/(1+exp(xb3)); pred4=exp(xb4)/(1+exp(xb4)); pred5=exp(xb5)/(1+exp(xb5)); pred6=exp(xb6)/(1+exp(xb6)); fhat0=pred0*(1-pred0); fhat1=pred1*(1-pred1); fhat2=pred2*(1-pred2); fhat3=pred3*(1-pred3); fhat4=pred4*(1-pred4); fhat5=pred5*(1-pred5); fhat6=pred6*(1-pred6); dc1db0=fhat0*one-fhat1*one; dc2db0=fhat1*one-fhat2*one; dc3db0=fhat2*one-fhat3*one; dc4db0=fhat3*one-fhat4*one; dc5db0=fhat4*one-fhat5*one; dc6db0=fhat5*one-fhat6*one; array dc1dba(&k) dc1db1-dc1db&k; array dc2dba(&k) dc2db1-dc2db&k; array dc3dba(&k) dc3db1-dc3db&k; array dc4dba(&k) dc4db1-dc4db&k; array dc5dba(&k) dc5db1-dc5db&k; array dc6dba(&k) dc6db1-dc6db&k; * create other variable components to derivatives; do i=1 to &k; dc1dba(i)=fhat0*x0a(i)-fhat1*x1a(i); dc2dba(i)=fhat1*x1a(i)-fhat2*x2a(i); dc3dba(i)=fhat2*x2a(i)-fhat3*x3a(i); dc4dba(i)=fhat3*x3a(i)-fhat4*x4a(i); dc5dba(i)=fhat4*x4a(i)-fhat5*x5a(i); dc6dba(i)=fhat5*x5a(i)-fhat6*x6a(i); end; proc logistic data=monika.regdata outest=monika.orgcoefs2 covout descending noprint; model y=&gendervars &newvars / link=logit; weight wt / normalize; data monika.covar (drop=&gendervars _link_ _type_ _status_ _name_ _lnlike_); set monika.orgcoefs2; * delete coefs and rows associated with racevars; if _n_=1 or (3<=_n_<=(&r+2)) then delete; proc means data=monika.combined noprint; var yw ym pred0-pred6 dc1db0 dc1db1-dc1db&k dc2db0 dc2db1-dc2db&k dc3db0 dc3db1-dc3db&k dc4db0 dc4db1-dc4db&k dc5db0 dc5db1-dc5db&k dc6db0 dc6db1-dc6db&k ordgroup1-ordgroup6; output out=means1 mean=; data monika.cont1 (keep=dc1db0 dc1db1-dc1db&k) monika.cont2 (keep=dc2db0 dc2db1-dc2db&k) monika.cont3 (keep=dc3db0 dc3db1-dc3db&k) monika.cont4 (keep=dc4db0 dc4db1-dc4db&k) monika.cont5 (keep=dc5db0 dc5db1-dc5db&k) monika.cont6 (keep=dc6db0 dc6db1-dc6db&k); set monika.means1; proc iml; use monika.covar; read all var _num_ into V; use monika.cont1; read all var _num_ into DC1DB; use monika.cont2; read all var _num_ into DC2DB; use monika.cont3; read all var _num_ into DC3DB; use monika.cont4; read all var _num_ into DC4DB; use monika.cont5; read all var _num_ into DC5DB; use monika.cont6; read all var _num_ into DC6DB; VAR1=DC1DB*V*t(DC1DB); VAR2=DC2DB*V*t(DC2DB); VAR3=DC3DB*V*t(DC3DB); VAR4=DC4DB*V*t(DC4DB); VAR5=DC5DB*V*t(DC5DB); VAR6=DC6DB*V*t(DC6DB); create monika.vardata var {var1 var2 var3 var4 var5 var6}; append; data monika.means1 (keep=yw ym pred0-pred6 var1-var6 cont1-cont6 ordgroup1-ordgroup6); merge monika.means1 monika.vardata; cont1=pred0-pred1; cont2=pred1-pred2; cont3=pred2-pred3; cont4=pred3-pred4; cont5=pred4-pred5; cont6=pred5-pred6; data monika.means1 (keep = yw ym contg1-contg6 vargroup1-vargroup6); set monika.means1; array ordgroupa{6} ordgroup1-ordgroup6; array contgroupa{6} contg1-contg6; array vargroupa{6} vargroup1-vargroup6; array conta{6} cont1-cont6; array vara{6} var1-var6; do j = 1 to 6; do i = 1 to 6; if ordgroupa[j] = i then do; contgroupa[j] = conta[i]; vargroupa[j] = vara[i]; end; end; end; data monika.means2; set monika.means2 monika.means1; run; %end; %mend; run; options nonotes; %simulate; run; proc means data=monika.means2; title2 'Mean Values of Contribution Estimates from Simulations'; var yw ym contg1-contg6 vargroup1-vargroup6; output out=monika.meandecomp mean=; data monika.meandecomp; merge monika.meandecomp monika.ywdata monika.ymdata; gap=ymfull-ywfull; perc1=contg1/gap; perc2=contg2/gap; perc3=contg3/gap; perc4=contg4/gap; perc5=contg5/gap; perc6=contg6/gap; se1=sqrt(vargroup1); se2=sqrt(vargroup2); se3=sqrt(vargroup3); se4=sqrt(vargroup4); se5=sqrt(vargroup5); se6=sqrt(vargroup6); label contg1=&labelgroup1; label contg2=&labelgroup2; label contg3=&labelgroup3; label contg4=&labelgroup4; label contg5=&labelgroup5; label contg6=&labelgroup6; options label; proc means data=monika.meandecomp mean; title2 'Final Output for Table - Means Values for Contribution Estimates'; var ywfull ymfull gap contg1 se1 perc1 contg2 se2 perc2 contg3 se3 perc3 contg4 se4 perc4 contg5 se5 perc5 contg6 se6 perc6; run;

MSALKAR · ‎03-02-2017

This is how my dataset merge2011 looks with the two variables. I did not much follow as to how I include the variables RO6 and LB18 in my &mvars.Let me know.

MSALKAR · ‎03-02-2017

In my actual code i have put K=14, but yet it is not working. ##- Please type your reply above this line. Simple formatting, no attachments. -##

MSALKAR · ‎03-02-2017

This is my code /*fairlie decomposition 2011-2012*/ libname MONIKA "C:\Users\msalkar\Desktop\THESIS-MONIKA"; options obs=max; options nolabel ls=75 ps=140; %let numiterations=100; %let r=2; %let gendervars=male female; %let k=12; %let definegroup1 = MM1W MM2W MM3W; %let definegroup2 = mahila_mandal VI20; %let definegroup3 = religion caste; %let definegroup4 = BHED INCOME occupation; %let definegroup5 = MOTHERS_EDUCATION FHEADAGE; %let definegroup6 = RO6 LB18; %let labelgroup1="media_exposure"; %let labelgroup2="social_events"; %let labelgroup3="cultural_influences"; %let labelgroup4="household_factors"; %let labelgroup5="mothers_age/education"; %let labelgroup6 = "TBA"; %let mdefinegroup1 = mMM1W mMM2W mMM3W; %let mdefinegroup2 = mmahila_mandal mVI20; %let mdefinegroup3 = mreligion mcaste; %let mdefinegroup4 = mBHED mINCOME moccupation; %let mdefinegroup5 = mMOTHERS_EDUCATION mFHEADAGE; %let mdefinegroup6 = mRO6 mLB18; %let wdefinegroup1 = wMM1W wMM2W wMM3W; %let wdefinegroup2 = wmahila_mandal wVI20; %let wdefinegroup3 = wreligion wcaste; %let wdefinegroup4 = wBHED wINCOME woccupation; %let wdefinegroup5 = wMOTHERS_EDUCATION wFHEADAGE; %let wdefinegroup6 = wRO6 wLB18; %let vars= &definegroup1 &definegroup2 &definegroup3 &definegroup4 &definegroup5 &definegroup6; %let mvars= &mdefinegroup1 &mdefinegroup2 &mdefinegroup3 &mdefinegroup4 &mdefinegroup5 &mdefinegroup6; %let wvars= &wdefinegroup1 &wdefinegroup2 &wdefinegroup3 &wdefinegroup4 &wdefinegroup5 &wdefinegroup6; data monika.merge2012; set monika.merge2011; mergeobs=1; y=child_immunization; if y=. or MM1W=. or MM2W=. or MM3W=. or INCOME=. or FHEADAGE=. or VI20=. or mahila_mandal=. or religion=. or caste=. or occupation=. or mothers_education=. then delete; if wt=. or wt<=0 then delete; run; data monika.regdata; set monika.merge2012; if male=1 or female=1; run; data monika.male (keep=ym wtm &mvars mergeobs); set monika.merge2012 ; array varsa(&k) &vars; array mvarsa(&k) &mvars; ym=y; wtm=wt; do i=1 to &k; mvarsa(i)=varsa(i); end; if male=1 then output; run; data monika.female (keep=yw wtw &wvars mergeobs); set monika.merge2012; array varsa(&k) &vars; array wvarsa(&k) &wvars; yw=y; wtw=wt; do i=1 to &k; wvarsa(i)=varsa(i); end; if female=1 then output; run; After running this I do not get an error but in the data set the values of the variables RO6 and LB18 are not seen. Also, in my log window I do not see any errors but I am not get the any output. So i am not sure if my cide is working. I would appreciate your help. Below is the dataset;

MSALKAR · ‎03-02-2017

This is my code /*fairlie decomposition 2011-2012*/ libname MONIKA "C:\Users\msalkar\Desktop\THESIS-MONIKA"; options obs=max; options nolabel ls=75 ps=140; %let numiterations=100; %let r=2; %let gendervars=male female; %let k=12; %let definegroup1 = MM1W MM2W MM3W; %let definegroup2 = mahila_mandal VI20; %let definegroup3 = religion caste; %let definegroup4 = BHED INCOME occupation; %let definegroup5 = MOTHERS_EDUCATION FHEADAGE; %let definegroup6 = RO6 LB18; %let labelgroup1="media_exposure"; %let labelgroup2="social_events"; %let labelgroup3="cultural_influences"; %let labelgroup4="household_factors"; %let labelgroup5="mothers_age/education"; %let labelgroup6 = "TBA"; %let mdefinegroup1 = mMM1W mMM2W mMM3W; %let mdefinegroup2 = mmahila_mandal mVI20; %let mdefinegroup3 = mreligion mcaste; %let mdefinegroup4 = mBHED mINCOME moccupation; %let mdefinegroup5 = mMOTHERS_EDUCATION mFHEADAGE; %let mdefinegroup6 = mRO6 mLB18; %let wdefinegroup1 = wMM1W wMM2W wMM3W; %let wdefinegroup2 = wmahila_mandal wVI20; %let wdefinegroup3 = wreligion wcaste; %let wdefinegroup4 = wBHED wINCOME woccupation; %let wdefinegroup5 = wMOTHERS_EDUCATION wFHEADAGE; %let wdefinegroup6 = wRO6 wLB18; %let vars= &definegroup1 &definegroup2 &definegroup3 &definegroup4 &definegroup5 &definegroup6; %let mvars= &mdefinegroup1 &mdefinegroup2 &mdefinegroup3 &mdefinegroup4 &mdefinegroup5 &mdefinegroup6; %let wvars= &wdefinegroup1 &wdefinegroup2 &wdefinegroup3 &wdefinegroup4 &wdefinegroup5 &wdefinegroup6; data monika.merge2012; set monika.merge2011; mergeobs=1; y=child_immunization; if y=. or MM1W=. or MM2W=. or MM3W=. or INCOME=. or FHEADAGE=. or VI20=. or mahila_mandal=. or religion=. or caste=. or occupation=. or mothers_education=. then delete; if wt=. or wt<=0 then delete; run; data monika.regdata; set monika.merge2012; if male=1 or female=1; run; data monika.male (keep=ym wtm &mvars mergeobs); set monika.merge2012 ; array varsa(&k) &vars; array mvarsa(&k) &mvars; ym=y; wtm=wt; do i=1 to &k; mvarsa(i)=varsa(i); end; if male=1 then output; run; data monika.female (keep=yw wtw &wvars mergeobs); set monika.merge2012; array varsa(&k) &vars; array wvarsa(&k) &wvars; yw=y; wtw=wt; do i=1 to &k; wvarsa(i)=varsa(i); end; if female=1 then output; run; After running this I do not get an error but in the data set the values of the variables RO6 and LB18 are not seen. Below is the dataset;

MSALKAR · ‎03-01-2017

Hello, I had post about the Fairlie decomposition method. But again I am having an error, I cannot see the variables RO6 and LB18 in my data set. I tried figuring the problem many times but just cannot figure out what the issue is. I am not getting any error message but just the values of variables are not seen. I am attaching my code as well as the how the dataset looks. Please help. Thank you.

MSALKAR · ‎03-01-2017

Hello Reeza, Thank you so much. My code works now. Actually I have never worked on stata so I have no idea how it works. And since I need to finish my thesis I do not have the time to learn a new software. I will base of my analysis off this code and try to work with it. I may have some more posts regarding this test and would really appreciate your help. Thank you.

MSALKAR · ‎02-28-2017

data monika.male (keep=ym wtm &mvars mergeobs); set monika.mergenew3 ; array varsa(&k) &vars; array mvarsa(&k) &mvars; ym=y; wtm=wt; do i=1 to &k; mvarsa(i)=varsa(i); end; if male=1 then output; run; ERROR: Too few variables defined for the dimension(s) specified for the array varsa. How do I solve this error? I am attaching the entire code of Fairlie decomposition. I am working on my thesis and would greatly appreciate any help on this. Thank you.

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