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Systematic review help!


User: spuddy - 12 August 2017 00:19

Hi!

I am trying to synthesize the results of my systematic review and had a question regarding the participants count.

If a study reports to have, for eg, 100 ppts, 80 of which answered a particular question (agree/disagree), of which 50 selected "agree" - does that mean 50 out of 80 "agree" or 50 out of 100? I need to know this so I can further figure out the % of ppts who "Agree" and combine this with the other study with the same finding.

I have tried to read through other SR's but I have not yet seen one that makes any sense to me with regards to my question!

Any help would be much appreciated!

Thank you!

User: Thesisfun - 12 August 2017 15:17


If a study reports to have, for eg, 100 ppts, 80 of which answered a particular question (agree/disagree), of which 50 selected "agree" - does that mean 50 out of 80 "agree" or 50 out of 100? I need to know this so I can further figure out the % of ppts who "Agree"

Both-
50/80 of those that answered the question selected that response
50/100 of those that took the survey selected that response

You don't know what the other 20 would have chosen (? attrition bias)- the proportion that you select was hopefully defined a priori in your protocol!

User: pm133 - 19 August 2017 14:26

Quote From spuddy:
Hi!

I am trying to synthesize the results of my systematic review and had a question regarding the participants count.

If a study reports to have, for eg, 100 ppts, 80 of which answered a particular question (agree/disagree), of which 50 selected "agree" - does that mean 50 out of 80 "agree" or 50 out of 100? I need to know this so I can further figure out the % of ppts who "Agree" and combine this with the other study with the same finding.

I have tried to read through other SR's but I have not yet seen one that makes any sense to me with regards to my question!

Any help would be much appreciated!

Thank you!

I would agree with thesisisfun under normal circumstances but only one of them can be correct for your usage and that is because you are combining with another study. You need to use exactly the same method they used or you will get bogus results.