Top Tweets for #instrumentalvariable
Join Thursday's online event for the Quantitative Solutions & Networking Series.
Organised by @Skyler_Xie & @hofer_carlo we will discuss methodological challenges & solutions of #DifferenceInDifferences & #InstrumentalVariable.
Find out more: https://t.co/YpIOvdgBZq @ResearchEx

new in @AmJEpi! McIntosh comments on a recent article questioning whether the #COVID19 pandemic can be used as an #InstrumentalVariable in epi research (https://t.co/Pw2GBWo4cZ) and authors Dimitris & @robertwplatt reply (https://t.co/jXCNamGMBH) @societyforepi #epimethods
can - and should - the #COVID19 #pandemic be used as an instrument in epidemiologic research? check out Diemer & Swanson's discussion of this important question in a new @AmJEpi commentary @societyforepi #InstrumentalVariable #EpiMethods https://t.co/LKoJkuSDV9
Empirical evidence that many #Instrumentalvariable-based studies are plagued by issues like weak instruments, inaccurate p-values, or a failure of the exclusion restriction. #CausalTwitter
Happy to share a new working paper w/ @Apoorva__Lal @lockhartm @zu_gary: https://t.co/bG74rTpLrl We replicated >60 papers using IV strategies published in APSR, AJPS, and JOP and find troubling patterns of weaker IVs, wrong inference, and failure of exclusion restrictions.

In my post this week I talk about the most contentious, capricious but potentially brilliant tool in the econometrician’s toolkit: the instrumental variable. I hope you enjoy! https://t.co/OkawMwo1P3 #Education #Economics #InstrumentalVariable
Contrary to popular belief, an #instrumentalvariable can only provide BOUNDS for the effect. A point estimate (as in Mendelian randomization) requires additional unverifiable assumptions.
Our review of methods for bounds, led by Sonja Swanson, is just out
https://t.co/YaBsfw9nVA
The challenging interpretation of #instrumentalvariable estimates under monotonicity - @IJEeditorial #DecisionMaking #MendelianRandomization https://t.co/3tXzdj3q81
Mendelian randomization estimates are harder to interpret when the IV is non-causal. See our new paper @IJEeditorial https://t.co/o4q0wxx8wt

The ideal setting for #InstrumentalVariable estimation: the instrument is the randomized assignment #SERDigital

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