#instrumentalvariable — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #instrumentalvariable, aggregated by home.social.
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Asking for help/refs: I have observational data where some patients always get treatment T=A due to their diagnosis (D) while the rest get either T=A or T=B based on clinical judgement. It seems to me that it might be possible to get closer to causal claims for T by exploiting the (lack of) differences between the "T=A, D=1" and "T=A, D=0" groups. This seems akin to IV analysis with D as instrument. Any ideas? A bit more detail at: https://discourse.datamethods.org/t/observational-data-with-diagnosis-partially-determining-treatment-imperfect-instrumental-variable/6983 #stats #instrumentalVariable #biostats
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Asking for help/refs: I have observational data where some patients always get treatment T=A due to their diagnosis (D) while the rest get either T=A or T=B based on clinical judgement. It seems to me that it might be possible to get closer to causal claims for T by exploiting the (lack of) differences between the "T=A, D=1" and "T=A, D=0" groups. This seems akin to IV analysis with D as instrument. Any ideas? A bit more detail at: https://discourse.datamethods.org/t/observational-data-with-diagnosis-partially-determining-treatment-imperfect-instrumental-variable/6983 #stats #instrumentalVariable #biostats
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Asking for help/refs: I have observational data where some patients always get treatment T=A due to their diagnosis (D) while the rest get either T=A or T=B based on clinical judgement. It seems to me that it might be possible to get closer to causal claims for T by exploiting the (lack of) differences between the "T=A, D=1" and "T=A, D=0" groups. This seems akin to IV analysis with D as instrument. Any ideas? A bit more detail at: https://discourse.datamethods.org/t/observational-data-with-diagnosis-partially-determining-treatment-imperfect-instrumental-variable/6983 #stats #instrumentalVariable #biostats
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Asking for help/refs: I have observational data where some patients always get treatment T=A due to their diagnosis (D) while the rest get either T=A or T=B based on clinical judgement. It seems to me that it might be possible to get closer to causal claims for T by exploiting the (lack of) differences between the "T=A, D=1" and "T=A, D=0" groups. This seems akin to IV analysis with D as instrument. Any ideas? A bit more detail at: https://discourse.datamethods.org/t/observational-data-with-diagnosis-partially-determining-treatment-imperfect-instrumental-variable/6983 #stats #instrumentalVariable #biostats
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Asking for help/refs: I have observational data where some patients always get treatment T=A due to their diagnosis (D) while the rest get either T=A or T=B based on clinical judgement. It seems to me that it might be possible to get closer to causal claims for T by exploiting the (lack of) differences between the "T=A, D=1" and "T=A, D=0" groups. This seems akin to IV analysis with D as instrument. Any ideas? A bit more detail at: https://discourse.datamethods.org/t/observational-data-with-diagnosis-partially-determining-treatment-imperfect-instrumental-variable/6983 #stats #instrumentalVariable #biostats
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All of America tryin get #TaylorSwiftTickets all day today
The next great #econometric or #PoliSci #InstrumentalVariable?
Gotta be more powerful than how rainy
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All of America tryin get #TaylorSwiftTickets all day today
The next great #econometric or #PoliSci #InstrumentalVariable?
Gotta be more powerful than how rainy
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All of America tryin get #TaylorSwiftTickets all day today
The next great #econometric or #PoliSci #InstrumentalVariable?
Gotta be more powerful than how rainy
-
All of America tryin get #TaylorSwiftTickets all day today
The next great #econometric or #PoliSci #InstrumentalVariable?
Gotta be more powerful than how rainy