Dear Statalist,
given a do-file ,such as the one that follows , is there any capability to
save the valid variables before the program gets to the next < set obs
`1' > ,and thus be able to find the relevant variables again after the
program is through ?
. capture program drop meansd
. program define meansd
1. quietly {
2. set more off
3. local i = 1
4. while `i'<= 1000 {
5. clear
6. set obs `1'
7. gen a`i' = 50+10*invnorm(uniform())
8. save a`i',replace
9. summ
10. set obs 1000
11.
. gen mean = .
12. gen sd = .
13. gen i = .
14. replace mean = r(mean) in `i'
15. replace sd = r(sd) in `i'
16. replace i = `i' in `i'
17. keep mean sd i
18. keep in `i'
19. sort i
20. save i`i',replace
21. local i = `i'+1
22. }
23. use i1,clear
24. local i = 1
25. while `i'<= 1000 {
26. merge i using i`i'
27. drop _merge
28. sort i
29. local i = `i'+1
30. }
31. }
32. keep if mean>49.9 & mean<50.1 & sd>9.9& sd<10.1
33. list
34. end
. meansd 100
(995 observations deleted)
+---------------------------+
mean sd i
---------------------------
1. 49.92186 10.07411 2
2. 50.06145 9.908244 88
3. 49.94671 10.08397 109
4. 50.0706 9.960301 215
5. 50.01047 9.9222 722
+---------------------------+
. meansd 200
(984 observations deleted)
+---------------------------+
mean sd i
---------------------------
1. 49.96996 9.978514 76
2. 49.92636 10.07861 118
3. 49.97271 10.07149 122
4. 50.07562 10.07239 218
5. 49.94316 9.913686 220
---------------------------
6. 50.02873 10.05811 346
7. 50.01596 10.04384 442
8. 50.00026 9.943673 513
9. 49.91186 9.95947 533
10. 50.00311 10.00525 629
---------------------------
11. 50.09705 9.929688 653
12. 49.98079 10.04592 678
13. 49.93727 9.962771 686
14. 49.98563 10.07247 694
15. 50.08827 9.936735 833
---------------------------
16. 49.97584 10.05994 854
+---------------------------+
. meansd 300
(977 observations deleted)
+---------------------------+
mean sd i
---------------------------
1. 50.02181 9.933003 66
2. 49.90105 10.02149 94
3. 49.91893 9.919211 124
4. 50.04763 9.961384 138
5. 50.097 10.07813 206
---------------------------
6. 50.05898 9.987234 259
7. 50.03423 9.955764 274
8. 49.90948 10.01387 304
9. 49.94732 9.985778 335
10. 49.90786 10.08386 338
---------------------------
11. 50.0072 9.95091 399
12. 49.93724 10.00748 426
13. 49.95889 10.09958 470
14. 50.0049 9.944254 488
15. 49.92678 10.05883 499
---------------------------
16. 50.00874 10.00746 500
17. 50.00669 9.937348 531
18. 50.07028 9.987976 532
19. 49.96707 10.06919 623
20. 50.06363 10.0947 757
---------------------------
21. 50.06802 10.03914 778
22. 50.07304 9.979012 830
23. 49.99155 9.969816 839
+---------------------------+
. meansd 400
Break--
r(1);
Thank you before hand,
Victor Michael Zammit
*
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