Outlier adjustment estimation — tryx.adjustment • tryx

How much of the heterogeneity due to the outlier can be explained by alternative pathways?

tryx.adjustment(tryxscan, id_remove = NULL)

Arguments

tryxscan

tryxscan	Output from `tryx.scan`
id_remove	List of IDs to exclude from the adjustment analysis. It is possible that in the outlier search a candidate trait will come up which is essentially just a surrogate for the outcome trait (e.g. if you are analysing coronary heart disease as the outcome then a variable related to heart disease medication might come up as a candidate trait). Adjusting for a trait which is essentially the same as the outcome will erroneously nullify the result, so visually inspect the candidate trait list and remove those that are inappropriate.

Output from tryx.scan

id_remove

List of IDs to exclude from the adjustment analysis. It is possible that in the outlier search a candidate trait will come up which is essentially just a surrogate for the outcome trait (e.g. if you are analysing coronary heart disease as the outcome then a variable related to heart disease medication might come up as a candidate trait). Adjusting for a trait which is essentially the same as the outcome will erroneously nullify the result, so visually inspect the candidate trait list and remove those that are inappropriate.

Value

data frame of adjusted effect estimates and heterogeneity stats