@RichardWWard1 @greg_travis @paddleplr @ID_Denmark @mamasaurusMeg @CIDRAP It's not confounding (see the paper below on RCT design). You're right, I've spent far too much time here. Despite the fact that you refused to respond to the majority of the issue
@CuomosCurls @smerconish The links to all of the RCTs are included in the review. However, while all studies have limitations, confounding variables are not typically an issue in RCTs, because such studies control for those variables *by design*. Here is
@mauveTriforce @FiveTimesAugust b) Yes, that's the purpose of randomization in RCTs - to control for any potential confounding variables. Here is some relevant info: https://t.co/pXb4fjVx2G. https://t.co/WSbNb13Zcw
@_00010101_ @aldenolmsted @khadastrophic It doesn't state what efficacy the role of masks plays. That study cannot clearly state what efficacy each layer supports. Too many variables to really prove what effect each layer has. Not the best study. https://
@breadtrader @ScottAdamsSays No consideration or need to balance confounders in RCT’s, right? Wrong! https://t.co/5MEnqvVGAq https://t.co/lxsSXVMILZ
@anfleischman88 RCTs can have either a parallel or crossover design. I suppose you worry about the possible carry-over effect? The data analysis will shed more light. We have to stay patient. Overview: https://t.co/HysYkMrITC and official info on how to d
Randomized controlled trials – a matter of design Peter Markus Spieth, Anne Sophie Kubasch, [...], and Timo Siepmann https://t.co/9D3cF73G0B #MedEd
@mwardle @Laconic_doc @CRegan1964 @kennylinafp @LSEImpactBlog @TheLancet There was a recent 2018 article on this topic 'Randomized controlled trials – a matter of design' by @AnneSophieK et al https://t.co/a8EOvZ7nxM
Randomized controlled trials https://t.co/snvzNItrlt
Randomized controlled trials https://t.co/2rzLKPfDOM