Meta-Regression using MetaXL and STATA

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Meta-Regression using MetaXL and STATA – Prevalence with categorical moderators. Download and ... Open STATA -> Data -> Data Editor -> Data Editor (Edit) ...
META-REGRESSION USING METAXL AND STATA Prevalence with categorical moderators

Dr Janni Leung National Drug and Alcohol Research Centre (NDARC) UNIVERSITY OF NEW SOUTH WALES 2018

Adapted from: MetaXL User Guide *https://www.epigear.com/index_files/metaxl.html

Meta-Regression using MetaXL and STATA – Prevalence with categorical moderators

Download and install MetaXL: https://www.epigear.com/index_files/metaxl.html

Open example: MetaXL -> MetaXL User Guide -> ThyCancerMetaRegres.xls

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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Set up data:

Get input data for meta-regression: MetaXL -> Results -> Meta-Regression data

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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Options -> Copy to Clipboard

Input data in STATA: Open STATA -> Data -> Data Editor -> Data Editor (Edit)

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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Edit - > Paste - > Variable names

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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Run analysis In Command, enter: regress t_es ib0.whole [aweight=weight], vce(robust)

Notes: • • •

“t_es” is the Transformed effect size; “whole” is the moderator variable, coded as 0 = not whole, 1 = whole; “ib0” specifies 0 as the reference; use “ib1” if 1 is the reference;

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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View results Results are presented for the comparison groups •

Compared to studies in the not whole group, studies in the whole group had significantly higher prevalence, coef = .27 (.14 to .41), p < .001

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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Subgroup analysis results We can use the meta-regression to view subgroup analysis results by the moderator variables •



The “_cons” result is the pooled prevalence in the reference subgroup; that is in this case, the not whole subgroup; o the pooled prevalence for the not whole subgroup is .41 (.35 to .47) If do “regress t_es ib1.whole [aweight=weight], vce(robust)”, the “_cons” result is the pooled prevalence in the whole subgroup; o the pooled prevalence for the whole subgroup is .68 (.56 to .81)

Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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Analysis with more than one moderator Add moderator variables in, specifying reference groups as “ib” In the below code, the 3 moderators are • • •

whole (1 as reference) year (2 as reference age_cat (1 as reference)

Enter in Command: regress t_es ib1.whole ib2.year_cat ib1.age_cat [aweight=weight], vce(robust)

All the best! Adapted from MetaXL User Guide: https://www.epigear.com/index_files/metaxl.html

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