hi I am trying to think through this problem: I need to calculate 'in each unique pregnancy, at which week in pregnancy a woman got a vaccine.'  - a unique eposide is defined as:  distinct person_id, condition_id (so if two records for person 1, person_id = 1, condition_id =1 and person_id =1, condition_id = 2, means this women has two distinct pregnancies; if one record of person_id = 1, condition_id =2, this person has one distinct pregnancy)    I want to fill in a table that looks like: All pregnancy episodes week0-12 week13-19 week 20 week21 number under all pregnancy episodes should = sum of all the week column.   BUT my data shows that during some pregnancy episodes, some women got more than one vaccine, and I only want each unique pregnancy being count once, so that the sum of all weeks can equal to all unique pregnancies. I want to calculate according to this rule:   For all the episodes that has more than one vaccines weeks (week when they got their vaccine) - If 1 vaccine is in 27-36 week, and others are not in week 27-36, then use the week in 27-36 - if multiple vaccine in 27-36, then use the earliest week - if neither vaccine is in 27-36, then use the earliest week   My input data looks like: person_id condition_id week 1 1 26 1 2 4 1 2 30 2 1 15 3 1 14 3 1 28 3 2 28 3 2 32 4 1 18 5 2 32 6 1 33 6 2 34 6 2 17   My desired output is the red rows in input table above, in other words, I want to leave only one row per unique pregnancy after applying the rule for multiple week entries under one pregnancy.   Any suggestion is appreciated! Thank you! ... View more

Hi I come across a task that requires the final output of the data to be one big summary table (all the rows are categorical variables, want to see the distribution break down; and the columns reflect different population group, I want to see the count), it looks like:    If there is a missing variable, report missing as well.     Patients who got vaccine   Patients who didn't get vaccine             Number %  Number %  Gender         Male         Female         Race         American Indian         Asian         Black         White         Multi-Race         NA         Ethinicity         Hispanic         Non-Hispanic         Age         18-39         40-64         65+           The input data looks like: patient_ID Race Gender Ethnicity Age Group Followup_Flag Vaccine_Flag 1 American Indian F Hispanic 18-39 1 1 2 Asian M Non-Hispanic 18-39 0 0 3 Black F NA 40-64 0 1 4 White   Hispanic 65+ 1 1 5 Multi-Race F Non-Hispanic 18-39 0 1 6 NA M Hispanic 18-39 1 1 7 American Indian F Non-Hispanic 40-65 0 0 8 Asian F   65+ 1 0 9 Black M Non-Hispanic 18-39 0 0 10 American Indian F NA 18-39 0 1 11 Asian M Hispanic 40-66 1 1 12 Black F Non-Hispanic 65+ 0 1     The methods I know, proc report, proc mean, etc, only give me summary statistics for one category at a time, and I am not interested in how different categories intersects with each other, don't need something like Race*Age. The real data I work with have way more different population categories like the two big columns, but the rows that need to be reported are the same across population groups.   I am wondering if there is any way to systematically 'stack' summary statistics of each row category, so that I won't need to stack them by hand for my real data (10 row categories, 20 column population categories).   Any suggestion is greatly appreciated.   Thank you! ... View more