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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

3 votes
1 answer
1k views

Linear Model Residual Bootstrapping

I am having some issues how to figure out what the second iteration of a fixed-x resampling bootstrap would be. For instance if I have this data Y x1 x2 7 2 3 6 3 5 5 4 1 9 5 4 …
Alex's user avatar
  • 65
2 votes
1 answer
306 views

How can you analyze how post-treatment covariates impact the outcome variable in a randomize...

My initial solution would be a regression model similar to below: Total Favorites = α + β1 (enabled_high_profile_visits) + β2(organic_enabled_profile_visits) + β3 (test_treatment) + β4 (test_x_enabled_high_profile_visits … test_treatment- binary condition if you are part of the test group, and therefore have been exposed to a profile with the banner My concern is that I will run into post-treatment bias by conditioning the regression
Alex's user avatar
  • 65
1 vote
1 answer
233 views

P-Values based on Experiment Data Aggregation

I'm trying to understand which interpretation of p-values for a linear regression model is correct given different levels of aggregation. … I can either aggregate the data to the level of the test (5 week period) or at the weekly grain and run a regression to determine the effect size. …
Alex's user avatar
  • 65