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2 votes

Analyzing an experiment which consists of many "small" experiments

dimitry (+1 to his answer) has the right idea here. Treat the cakes as nuisance variables and use a Poisson model to estimate the risk ratio between bakers A and B. In R, you can handle a million ...
Demetri Pananos's user avatar
4 votes
Accepted

Analyzing an experiment which consists of many "small" experiments

This is a standard A/B test if you view cakes as the sample from a population of products (rather than customers), with a varying number of taste tests (aka trials) for each cake. Your proposed ...
dimitriy's user avatar
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1 vote
Accepted

Robust Variance Estimation or Cluster Wild Bootstrapping on a multivariate meta-analysis

Cluster robust inference methods can most certainly be used for models without moderators. Whether RVE 'works' in your case (i.e., the Type I error rate is controlled / the coverage of confidence ...
Wolfgang's user avatar
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2 votes
Accepted

Understanding correlated and hierarchical effects models in meta-analysis

Yes, anova(model, model.reduced) and anova(che.model.6, che.model.60) serve the same purpose - they provide likelihood ratio ...
Wolfgang's user avatar
  • 17.2k
0 votes

I was trying to calculate standard error from log odd ratio, Is this calculation correct?

Here's what I calculated in Excel and RevMan: Blockquote
abousetta's user avatar
  • 1,240
0 votes
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Pooled Hazard Ratio or Crude events (M-H to RR or OR) for mortality outcomes in Meta-Analysis?

A time-to-event model such as Cox regression accounts for differences in follow-up. E.g. if one arm has more people not being followed to the end because of unpleasant side effects, you avoid counting ...
Björn's user avatar
  • 33.2k

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