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#missingdata

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Only 3 days left until the start of the Statistics Globe online workshop, Missing Data Imputation in R.

Kicking off on February 20, this workshop includes eight weekly live sessions, beginning with the basics of handling missing data and advancing to sophisticated imputation techniques in R.

The workshop is limited to 15 participants, so enroll now to secure your spot.

Learn more and sign up here: statisticsglobe.com/online-wor

A #ScopingReview on #MissingData reporting in observational studies that use #MultipleImputation for causal effect estimation:
bmcmedresmethodol.biomedcentra

Informative read beyond the particular application.

As a #NightshiftEditor I am still working more on the problem that most studies do not even report their sampling and take it for granted that complete-data only analyses are fine.

As noted before 😉
mastodon.social/deck/@jrboehnk

I need to fake some #data. It's for a good cause, I swear! My students (intro #statistics & #researchmethods have "class demonstration" surveys posted but few participants. I'd like them to have a better analysis experience.

My preferred platform is #Rstats

can #mice do a forced single-imputation with, say, 80% #MissingData?

Should I just #bootstrap (or something similar)? If so, any suggestions for which package/procedure?

A couple dozen variables, NOIR.

#Advice?