I am running into a problem. First of all, I have a panel dataset consisting of 10 waves and I use Stata 16.1.
I want to compile my dataset in such a manner, that I am only left with people who have got a child somewhere in the 10 waves. An example of my dataset is as follows:
Code:
input float wave long(pidp hidp) byte(pno jbstat lnprnt marstat sex_dv) int(age_dv doby_dv) long ppid byte scghq1_dv double sf12mcs_dv byte(racel_dv father nchild pregout1 pregout2 pregout3) double fimnnet_dv float(gotABaby gotTwinOrTriplet) 4 22445 280942006 5 2 -8 1 2 27 1984 -8 -8 -8 1 -8 -8 -8 -8 -8 1140 0 . 5 22445 279255608 5 2 -8 1 2 28 1984 -8 29 30.22 1 -8 -8 -8 -8 -8 1602.6700439453125 0 . 6 22445 278664010 3 2 -8 1 2 29 1984 -8 25 32.59 1 -8 -8 -8 -8 -8 2012 0 . 7 22445 278447092 1 2 -8 1 2 30 1984 -8 19 29.57 1 -8 -8 4 -8 -8 1840 0 . 8 22445 278092814 1 5 -8 1 2 31 1984 -8 15 39.03 1 -8 -8 1 -8 -8 2089.699951171875 1 . 9 22445 277344816 1 2 -8 2 2 33 1984 -8 11 46.08 1 -8 -8 -8 -8 -8 1289.699951171875 0 . 10 22445 277059218 1 2 -8 2 2 33 1984 277059298 11 33.83 1 -8 -8 3 -8 -8 1289.699951171875 0 . 4 29925 622866406 3 6 2 -7 2 35 1977 -8 -7 -7 1 -7 -7 -7 -7 -7 0 0 . 6 29925 620547610 1 1 -8 4 2 37 1977 -8 11 35.67 1 -8 -8 1 1 -8 2378.4599609375 0 1 7 29925 620316412 1 1 -8 5 2 38 1977 -8 16 28.16 1 -8 -8 -8 -8 -8 2076.8701171875 0 . 8 29925 619935614 1 2 -8 5 2 39 1977 -8 12 46.08 1 -8 -8 -8 -8 -8 2811.669921875 0 . 9 29925 619024416 1 2 -8 5 2 40 1977 -8 9 41.06 1 -8 -8 -8 -8 -8 2904.530029296875 0 . 10 29925 618630018 1 2 -8 5 2 41 1977 -8 17 37.69 1 -8 -8 -8 -8 -8 2760 0 . 7 76165 142378412 1 2 -8 2 2 32 1982 142378492 10 46.94 1 -8 -8 -8 -8 -8 1804.1700439453125 0 . 8 76165 142235614 1 2 -8 2 2 33 1982 142378492 14 46.45 1 -8 -8 4 -8 -8 2208.330078125 0 . 9 76165 141657616 1 2 -8 2 2 34 1982 142378492 8 62.49 1 -8 -8 2 -8 -8 3378.669921875 1 . 10 76165 141460418 1 2 -8 2 2 35 1982 142378492 11 51.24 1 -8 -8 -8 -8 -8 2862 0 . 7 223725 619140012 3 2 -8 -7 1 40 1975 -8 -7 -7 1 -7 -7 -7 -7 -7 869.2899780273438 0 . 8 223725 618772814 1 2 -8 -7 1 41 1975 -8 -7 -7 1 -7 -7 -7 -7 -7 1020.2999877929688 0 . 2 280165 783876802 2 2 1 1 2 31 1979 -8 -8 -8 1 -8 -8 -8 -8 -8 2165.75 0 . 3 280165 759532804 2 2 1 -7 2 32 1979 -8 -7 -7 1 -7 -7 -7 -7 -7 2189.889892578125 0 . 4 280165 758492406 2 2 1 -7 2 33 1979 -8 -7 -7 1 -7 -7 -7 -7 -7 2183.080078125 0 . 5 280165 756833208 2 2 -8 1 2 34 1979 -8 24 35.62 1 -8 -8 -8 -8 -8 2324.169921875 0 . 6 280165 756200810 2 2 -8 -7 2 35 1979 756200970 -7 -7 1 -7 -7 -7 -7 -7 2085.639892578125 0 . 7 280165 755847212 1 2 -8 1 2 36 1979 756200970 17 28.5 1 -8 -8 -8 -8 -8 2289.699951171875 0 . 8 280165 755643214 1 2 -8 2 2 37 1979 756200970 9 48.77 1 -8 -8 -8 -8 -8 2352.699951171875 0 . 9 280165 754793216 1 2 -8 2 2 38 1979 756200970 7 52.43 1 -8 -8 -8 -8 -8 2317.699951171875 0 . 10 280165 754371618 1 2 -8 2 2 39 1979 756200970 7 52.53 1 -8 -8 -8 -8 -8 3093.699951171875 0 . 6 333205 416683610 3 2 -8 1 2 24 1990 -8 5 54.2 1 -8 -8 -8 -8 -8 1604.1700439453125 0 . 7 333205 416466012 3 2 -8 1 2 25 1990 -8 6 50.65 1 -8 -8 -8 -8 -8 1525.8299560546875 0 . 8 333205 415935614 1 2 -8 1 2 26 1990 -8 7 65.95 1 -8 -8 -8 -8 -8 1558.3299560546875 0 . 9 333205 415106696 1 2 -8 1 2 27 1990 -8 7 54.2 1 -8 -8 -8 -8 -8 1658.3299560546875 0 . 10 333205 414800018 1 2 -8 1 2 28 1990 414800098 7 68.33 1 -8 -8 -8 -8 -8 1741.6600341796875 0 . 4 387605 349690006 3 3 -8 1 2 24 1988 -8 18 39.89 1 -8 -8 3 -8 -8 .07999999821186066 0 . 5 387605 348044408 3 3 -8 1 2 25 1988 -8 22 22.31 1 -8 -8 3 -8 -8 .17000000178813934 0 . 6 387605 347486810 3 3 -8 1 2 26 1988 -8 22 19.88 1 -8 -8 -8 -8 -8 309.8299865722656 0 . 7 387605 347194412 3 2 -8 1 2 27 1988 -8 6 37.02 1 -8 -8 -8 -8 -8 866.6699829101563 0 . 9 469205 415059096 1 5 1 1 2 27 1990 415059176 13 58.300000000000004 1 -8 -8 -8 -8 -8 1853.31005859375 0 . 10 469205 414738818 1 2 -8 1 2 28 1990 415059176 12 45.56 1 -8 -8 -8 -8 -8 708.6699829101563 0 . 3 541285 146730404 4 2 -8 -7 1 25 1985 -8 -7 -7 1 -7 -7 -7 -7 -7 593.9000244140625 0 . 4 541285 145989206 4 3 -8 -7 1 26 1985 -8 -7 -7 1 -7 -7 -7 -7 -7 0 0 . 5 541285 144146408 3 3 -8 -7 1 27 1985 -8 -7 -7 1 -7 -7 -7 -7 -7 0 0 . 6 541285 143384810 2 1 -8 1 1 28 1985 -8 18 24.76 1 2 -8 -8 -8 -8 1126.800048828125 0 . 3 541965 146730404 3 2 -8 -7 2 23 1987 -8 -7 -7 1 -7 -7 -7 -7 -7 332.6700134277344 0 . 4 599765 214798406 3 2 -8 -7 2 25 1986 -8 -7 -7 1 -7 -7 -7 -7 -7 1644.489990234375 0 . 5 599765 213057608 3 2 -8 1 2 26 1986 -8 7 60.29 1 -8 -8 -8 -8 -8 1769.3399658203125 0 . 9 599765 211282816 1 2 -8 1 2 30 1986 -8 6 54.74 1 -8 -8 -8 -8 -8 2084 0 . 10 599765 210881618 1 2 -8 1 2 31 1986 -8 7 58.15 1 -8 -8 -8 -8 -8 2353.639892578125 0 . 3 665045 215192804 4 2 -8 1 1 29 1981 -8 -8 -8 1 2 -8 -8 -8 -8 563.3300170898438 0 . 4 665045 214812006 4 2 -8 1 1 30 1981 -8 -8 -8 1 2 -8 -8 -8 -8 598 0 . 5 665045 213071208 4 2 -8 1 1 31 1981 -8 7 52.82 1 2 -8 -8 -8 -8 652.1699829101563 0 . 6 665045 212588410 4 2 -8 1 1 32 1981 -8 10 50.14 1 2 -8 -8 -8 -8 460 0 . 8 665045 212064814 4 2 -8 1 1 34 1981 -8 7 57.160000000000004 1 2 -8 -8 -8 -8 772.4199829101563 0 . 10 665045 210902018 1 2 -8 1 1 36 1981 -8 7 53.21 1 2 -8 -8 -8 -8 253.5 0 . 9 732365 619371216 1 8 -8 1 1 32 1985 -8 35 12.81 1 2 -8 -8 -8 -8 1110.4200439453125 0 . 10 732365 618949618 1 8 -8 1 1 33 1985 -8 22 11.09 1 2 -8 -8 -8 -8 845 0 . 10 760925 210514418 1 8 -8 1 1 37 1981 -8 -8 -8 -9 2 -8 -8 -8 -8 1252.3299560546875 0 . 4 813285 553343206 3 2 -8 -7 1 42 1970 -8 -7 -7 1 -7 -7 -7 -7 -7 595.8200073242188 0 . 5 813285 551758808 3 2 -8 -7 1 43 1970 -8 -7 -7 1 -7 -7 -7 -7 -7 1628.77001953125 0 . 6 813285 551180810 3 2 -8 -7 1 44 1970 -8 -7 -7 1 -7 -7 -7 -7 -7 1691.18994140625 0 . 7 813285 550902012 3 2 -8 -7 1 45 1970 -8 -7 -7 1 -7 -7 -7 -7 -7 1693.3900146484375 0 . 8 813285 550623214 1 2 -8 -7 1 46 1970 -8 -7 -7 1 -7 -7 -7 -7 -7 1691.8900146484375 0 . 7 850005 211922012 2 2 -8 -7 1 26 1988 -8 -7 -7 1 -7 -7 -7 -7 -7 1071.2900390625 0 . 2 987365 170639202 2 7 -8 -7 2 20 1989 -8 -7 -7 -9 -7 -7 -7 -7 -7 652.5 0 . 3 987365 146472004 2 2 -8 -7 2 21 1989 -8 -7 -7 -9 -7 -7 -7 -7 -7 497.42999267578125 0 . 2 1114525 170802402 7 2 1 -7 1 36 1973 -8 -7 -7 1 -7 -7 -7 -7 -7 2247.02001953125 0 . 2 1126765 442856802 2 3 -8 1 2 21 1989 -8 -8 -8 1 -8 -8 -8 -8 -8 0 0 . 2 1558565 852386802 3 7 -8 1 2 17 1993 -8 10 27.94 1 -8 -8 -8 -8 -8 130 0 . 3 1558565 828349484 1 7 -8 1 2 18 1993 -8 5 48.43 1 -8 -8 -8 -8 -8 702 0 . 6 1587125 619704410 2 8 -8 1 2 48 1965 -8 26 16 13 -8 -8 -8 -8 -8 307.6700134277344 0 . 7 1587125 619493612 2 1 -8 1 2 50 1965 -8 12 45.81 13 -8 -8 -8 -8 -8 3390.820068359375 0 . 8 1587125 619112814 1 1 -8 1 2 50 1965 -8 12 46.22 13 -8 -8 -8 -8 -8 4303.5498046875 0 . 9 1587125 618269616 1 2 -8 1 2 51 1965 -8 12 43.37 13 -8 -8 -8 -8 -8 2802.27001953125 0 . 10 1587125 617895618 1 1 -8 1 2 52 1965 -8 23 41.93 13 -8 -8 -8 -8 -8 3034.159912109375 0 . 8 1697285 211473214 3 2 -8 5 1 43 1972 -8 14 37.03 1 2 -8 -8 -8 -8 1171 0 . 9 1697285 210766016 1 2 -8 5 1 44 1972 -8 10 36.37 1 2 -8 -8 -8 -8 1142 0 . 10 1697285 210364818 1 2 -8 5 1 45 1972 -8 10 31.400000000000002 1 2 -8 -8 -8 -8 1200 0 . 5 1731965 484275608 5 2 -8 1 1 22 1990 -8 7 49.410000000000004 1 2 -8 -8 -8 -8 1958.3299560546875 0 . 2 1833965 782088402 3 1 -8 1 1 45 1965 -8 15 28.740000000000002 1 -8 -8 -8 -8 -8 1580.6199951171875 0 . 3 1833965 757615204 3 2 -8 1 1 46 1965 -8 8 37.910000000000004 1 2 -8 -8 -8 -8 1329.81005859375 0 . 4 1833965 756846806 3 2 1 -7 1 47 1965 -8 -7 -7 1 -7 -7 -7 -7 -7 1506.2099609375 0 . 5 1833965 755412008 2 2 -8 1 1 48 1965 -8 26 22.650000000000002 1 2 -8 -8 -8 -8 1582.25 0 . 6 1833965 754766010 2 1 -8 1 1 49 1965 -8 20 25.16 1 2 -8 -8 -8 -8 972.3400268554688 0 . 7 1833965 754494012 1 2 -8 1 1 50 1965 -8 7 49.870000000000005 1 2 -8 -8 -8 -8 1704.1700439453125 0 . 8 1833965 754310414 1 97 -8 1 1 51 1965 -8 29 24.22 1 2 -8 -8 -8 -8 1201.6700439453125 0 . 9 1833965 753508016 1 2 -8 1 1 52 1965 -8 12 42.410000000000004 1 2 -8 -8 -8 -8 1000 0 . 6 2067205 74759210 4 3 -8 1 1 25 1988 -8 22 29.150000000000002 1 2 -8 -8 -8 -8 0 0 . 7 2067205 74596012 3 2 -8 1 1 26 1988 -8 11 33.07 1 2 -8 -8 -8 -8 425.2300109863281 0 . 7 2270525 824894412 3 6 1 1 2 18 1997 -8 10 41.71 1 -8 -8 -8 -8 -8 1077.77001953125 0 . 8 2270525 824548294 1 6 -8 1 2 19 1997 824548414 15 50.19 1 -8 -8 4 -8 -8 877.7000122070313 0 . 9 2270525 823677216 1 6 -8 1 2 20 1997 824548414 23 25.38 1 -8 -8 1 -8 -8 1483.030029296875 1 . 3 2292285 556233204 6 8 4 -7 1 36 1975 548026285 -7 -7 1 -7 -7 -7 -7 -7 146 0 . 4 2292285 554988806 6 8 4 -7 1 36 1975 548026285 -7 -7 1 -7 -7 -7 -7 -7 342.3299865722656 0 . 5 2297045 416228008 4 7 -8 -7 1 16 1997 -8 -7 -7 1 -7 -7 -7 -7 -7 0 0 . 6 2297045 415622810 3 2 -8 1 1 17 1997 -8 3 50.050000000000004 1 -8 -8 -8 -8 -8 175 0 . 2 2401085 239339602 4 2 -8 -7 2 26 1983 -8 -7 -7 1 -7 -7 -7 -7 -7 233.3300018310547 0 . 2 2539125 103904002 5 2 -8 1 2 22 1987 -8 20 36.99 1 -8 -8 -8 -8 -8 628.3300170898438 0 . 2 2626845 852033202 4 3 -8 1 1 32 1978 818504445 8 56.47 1 -8 -8 -8 -8 -8 281.6700134277344 0 . 4 2626845 827220006 1 2 -8 1 1 34 1978 818504445 13 48.57 1 2 -8 -8 -8 -8 1025 0 . 6 2626845 824445610 1 2 -8 1 1 36 1978 818504445 11 54.1 1 2 -8 -8 -8 -8 980 0 . end
I did manage to create a gotABaby dummy variable (which is 1 in the periods that an individual got a baby). What I didn't manage to do is the following: I only want to keep observations of individuals who got a baby and I also want to observe these individuals in all other waves(in which they did not have a child).
Thanks in advance and kind regards,
Vincent van Marrewijk
0 Response to Dropping particular observations from a panel dataset
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