1 Merging with SQL HRP223 – 2012 October 29, 2012 Copyright © 1999-2012 Leland Stanford Junior...
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Transcript of 1 Merging with SQL HRP223 – 2012 October 29, 2012 Copyright © 1999-2012 Leland Stanford Junior...
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Merging with SQL
HRP223 – 2012October 29, 2012
Copyright © 1999-2012 Leland Stanford Junior University. All rights reserved.Warning: This presentation is protected by copyright law and international treaties. Unauthorized reproduction of this presentation, or any portion of it, may result in severe civil and criminal penalties and will be prosecuted to maximum extent possible under the law.
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Combining
• When you have data in two tables, you need to tell SQL how the two tables are related to each other.– Typically you have a subject ID number in both
files. The variable that can be used to link information is called the key.
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Demographics
Diagnosis
Here the two tables have different variables except the common ID.
I want to know the diagnosis for this cohort.
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Merging
• Merging is trivially easy with EG. Choose a table and do the Query Builder…. And push the Join Tables button.
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Double click on the dividing lines to make the columns wide
enough to read.
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Notice the name t1. In the SQL statements, variables from this
table will have the prefix t1.
This table will be referred to as t2.
It noticed that the two tables have the common variable ID. Therefore it is going to match records that have a common
value in ID.
Double click the link for details.
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Joins
• You will typically do inner joins and left joins.– Inner Joins: select the marching records– Left Joins: select all records on the left side and
any records that match on the right.
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Inner Joins
• Inner Joins are useful when you want to keep the information from the tables, if and only if, there are matches in both tables.– Here you keep the records where you have
demographic and response to treatment information on people.
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Left Joins
• Left joins are useful when you have a table with everybody on the left side of the join and not everyone has records in the right table.– A typical example has the left side with the IDs of
everyone in a family and the right table has information on diagnoses. Not everyone is sick so you want to keep all the IDs on the left and add in diagnoses where you can.
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Typical Left Join
Notice the numeric variable is formatted to
display with words.
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More Complete
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Coalesce
• The previous example leaves NULL for the people who are disease free. You probably want to list the rest as healthy.
• The coalesce function returns the first non-missing value. – Coalesce works on numeric lists.– CoalesceC works on character lists.
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Expand the tree
Use the query builder with an advanced expression….
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Complex Coalesce
• If you are using left joins from multiple tables, coalesce can be really useful.– Say you have people who have reported disease,
other people have verified disease and the rest are assumed to be healthy. You can coalesce an indicator variable from the verified table and reported table and call everybody else healthy.
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If the tables have indicator variables, once the tables are linked, the coalesce function is easy:COALESCEC(t3.status2 , t2.status1, "Healthy"))
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No indicator variables?
• If the tables you are coalescing do not have indicator variables, just make them as part of the query by adding a column which has the ID in the child tables (e.g., reported and verified) recoded to a word like “reported” or “verified”.
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The two new indicator columns.
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Coalesce the new columns
• Once the new columns are created, create a new variable using the Advanced expression option for a new computed column. Then do coalesce on the new variables. Double click on the new variables and it will insert the code.
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After double clicking the ver variable the
code is inserted.
Don’t forget the comma before double clicking
the rep variable.
After inserting reported and verified, put in
another comma and the “healthy” option.
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