Thank you! Option 1 has one obs that is over 200 d of age. Option 2 still has every gilt obs with a weight over 136 kg like before.   ... View more

My apologies. Here are 5 obs.  data WORK.ESFEXPERIMENT1; infile datalines dsd truncover; input GiltID:32. entrydate:DATE9. dayOT:32. Trt:$8. _TYPE_:$1. _FREQ_:32. avgwt:32. totalfeed:32. totalfv:32. totalnfv:32. totalvisits:32. block:32. DOB:DATE. Age:32. Estrus1B:DATETIME. Estrus1E:DATETIME. AgeatPuberty:32. Estrus1Length:32. Estruswt1:32. Estrus2b:DATETIME. Estrus2e:DATETIME. Estrus2Length:32. Estruswt2:32. Eint:32. cycling:32. estrus3b:DATETIME. estrus3e:DATETIME. estrus3Length:32. estruswt3:32. Eint2:32. e160d:32. e170d:32. e180d:32. e190d:32. e200d:32. avgwtkg:32. Rep:32. ageOT:32. wt300by200d:32. wt136by200d:32. dayofestrous:32. where:32.; format entrydate DATE9. DOB DATE. Estrus1B DATETIME. Estrus1E DATETIME. Estrus2b DATETIME. Estrus2e DATETIME. estrus3b DATETIME. estrus3e DATETIME.; datalines4; 220810,09SEP2022,1,RS,1,1,193.12296,5.4938632,1,0,1,6,27MAR22,220,12SEP22:20:00:00,13SEP22:09:00:00,170,13,198,03OCT22:10:00:00,04OCT22:20:00:00,34,241,20.58,1,,,,,,0,1,1,1,1,87.67782384,1,166,0,0,1, 220810,10SEP2022,2,RS,1,2,,1.5696752,1,1,2,6,27MAR22,220,12SEP22:20:00:00,13SEP22:09:00:00,170,13,198,03OCT22:10:00:00,04OCT22:20:00:00,34,241,20.58,1,,,,,,0,1,1,1,1,,1,167,0,0,12, 220810,11SEP2022,3,RS,1,2,198.85492,5.9987166,1,1,2,6,27MAR22,220,12SEP22:20:00:00,13SEP22:09:00:00,170,13,198,03OCT22:10:00:00,04OCT22:20:00:00,34,241,20.58,1,,,,,,0,1,1,1,1,90.28013368,1,168,0,0,13, 220810,12SEP2022,4,RS,1,3,197.53216,5.9987166,3,0,3,6,27MAR22,220,12SEP22:20:00:00,13SEP22:09:00:00,170,13,198,03OCT22:10:00:00,04OCT22:20:00:00,34,241,20.58,1,,,,,,0,1,1,1,1,89.67960064,1,169,0,0,14, 220810,13SEP2022,5,RS,1,6,202.05159,1.7460432,3,3,6,6,27MAR22,220,12SEP22:20:00:00,13SEP22:09:00:00,170,13,198,03OCT22:10:00:00,04OCT22:20:00:00,34,241,20.58,1,,,,,,0,1,1,1,1,91.73142186,1,170,0,0,15, ;;;; In this instance, the new variable "Dayofestrous" would be, from top to bottom, -3,-2,-1,0,1... Note the estrus2b of 03oct22, Where when entrydate is 03oct22, dayofestrous would be 0 again. On average these animals exhibit a 21 day cycle, but that is not always true, which is why I bring up the idea of using estrus1b, 2b, 3b, etc to develop an observation based on information specific to that estrous cycle. Either way, when entrydate = estrus1b, estrus2b, or estrus3b, then dayofestrous=0 and goes either up or down from there until the next estrus date. Hope this gives the information you are looking for.  ... View more

In words, it would be when the estrus1b, estrus2b, or estrus3b variables are equal to the entrydate, that observation would be day 0. Any entrydate before estrus1b would be 20, 19, 18 and so on. Any entrydate after estrus1b and before estrus2b would be 1, 2, 3, 4 and so on. Any entrydate after estrus2b and before estrus3b would be 1, 2, 3, 4 and so on. Any entrydate after estrus3b would be 1, 2, 3, 4 and so on. ... View more

Instructions here: https://communities.sas.com/t5/SAS-Communities-Library/How-to-create-a-data-step-version-of-your-data-AKA-generate/ta-p/258712 will show how to turn an existing SAS data set into data step code that can be pasted into a forum code box using the </> icon or attached as text to show exactly what you have and that we can test code against.   Only need to show enough records to allow us to perform the actions you need.   Since your "predicted" values have no column headings or description any match with the other data is going to rely on a lot of guessing. You should also provide that data in the forum of a data step. Then identify which variables in the "predicted" data are to be used to match the collected data. I don't see a D0 in the collected data so you need to describe how that relates to the collected data.   In this case, you need to provide details as to which variables are used for what. You seem to have potentially 7 columns at least that might be used to identify groups but I am not sure which ones you intend or how. Note that typically using a correct format for a date, time or datetime variable in a procedure like Means or Summary will allow you to group by that ... View more

For example, I want a dayoftest variable where 01sep22 is 2, 02sep22 is 3, and so on. I was looking for a way to base the variable off of the value in the entrydate column. The code I generated in my previous post was something that I came up with based on a numerical format and subtracting the different to January 1,1960 since that is the day 0 that SAS uses, but if something happens to this dataset, it could technically be formatted as a date, although I guess this is negligible. I have another question. This dataset is fairly large to my terms (approx 5700 obs) and I want to make a "processed" dataset where wt is averaged without 0's and feed is summed by day to start. There is further processing that needs to be done. I did this by PROC MEANS which accomplished this task, however I wanted to average the feed by day according to the number of animals on a treatment. If I just do an average of feed it bases the average on the feed per animal, so across feeding events per day it could range from .2 to 5 for instance, and the mean is based off that. My overall goal with this dataset is to remove outliers based on predicted values that I calculated from two real weights recorded at the start and end of test; then I want to average the remaining weights by visualid by entrydate and also sum the feed by the same criteria. Here however, the data only shows one visualid, as this trial is over a period of 6 weeks with 19 animals.   Obs desc entry exit location GiltID RFID Trt Duration Feed1 Feed2 Wt Controller Station FV NFV entry2 exit2 feed entrydate12345678910 Gestation 01JAN60:12:26:45 01JAN60:12:26:45 1 220910 9.85E14 AD 873 2.000 0.000 198.414 1 2 1 0 01SEP22:10:33:36 01SEP22:10:48:00 2.000 01SEP2022 Gestation 01JAN60:12:26:46 01JAN60:12:26:46 1 220910 9.85E14 AD 9 0.183 0.000 0.000 1 2 1 0 01SEP22:18:00:00 01SEP22:18:00:00 0.183 01SEP2022 Gestation 01JAN60:12:26:46 01JAN60:12:26:46 1 220910 9.85E14 AD 1230 2.815 0.000 202.382 1 2 1 0 01SEP22:18:43:12 01SEP22:19:12:00 2.815 01SEP2022 Gestation 01JAN60:12:26:46 01JAN60:12:26:46 1 220910 9.85E14 AD 137 0.000 0.000 0.000 1 2 0 1 01SEP22:20:52:48 01SEP22:20:52:48 0.000 01SEP2022 Gestation 01JAN60:12:26:46 01JAN60:12:26:46 1 220910 9.85E14 AD 1774 3.999 0.000 208.776 1 2 1 0 02SEP22:06:28:48 02SEP22:06:57:36 3.999 02SEP2022 Gestation 01JAN60:12:26:47 01JAN60:12:26:47 1 220910 9.85E14 AD 37 0.000 0.000 0.000 1 2 0 1 02SEP22:18:43:12 02SEP22:18:43:12 0.000 02SEP2022 Gestation 01JAN60:12:26:47 01JAN60:12:26:47 1 220910 9.85E14 AD 51 0.000 0.000 0.000 1 2 0 1 02SEP22:19:12:00 02SEP22:19:12:00 0.000 02SEP2022 Gestation 01JAN60:12:26:47 01JAN60:12:26:47 1 220910 9.85E14 AD 143 0.000 0.000 0.000 1 2 0 1 02SEP22:19:55:12 02SEP22:19:55:12 0.000 02SEP2022 Gestation 01JAN60:12:26:47 01JAN60:12:26:47 1 220910 9.85E14 AD 2 0.000 0.000 0.000 1 2 0 1 02SEP22:20:09:36 02SEP22:20:09:36 0.000 02SEP2022 Gestation 01JAN60:12:26:47 01JAN60:12:26:47 1 220910 9.85E14 AD 215 0.366 0.000 210.539 1 2 1 0 03SEP22:04:19:12 03SEP22:04:33:36 0.366 03SEP2022 ... View more