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Performing the integration is computationally demanding, especially in the presence of multivariate random effects.
Here, we take the multivariate random effects model as the standard model.
Data extraction Study results relating to diagnostic accuracy were extracted and synthesised using multivariate random effects meta-analysis methods.
19 We used multivariate random effects logistic regression to estimate the association of demographic variables with home births.
Network meta-analysis was performed using a frequentist based approach with the use of multivariate, random effects meta-analysis.
25 We then combined the study specific estimates, using the restricted maximum likelihood method in a multivariate random effects meta-analysis.
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The imputation involves estimating E(X | W ), which in turn requires estimating variance components from a multivariate random effect model applied to unbalanced data, in order to acknowledge variation between and within matched sets, in a similar fashion to [ 5].
Only time from intervention to last follow-up remained statistically significant after adjustment using multivariate random-effects meta-regression modelling.
A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (ρ B ).
Bipat et al [ 11] discussed a multivariate random-effects approach for meta-analysis of cancer staging.
Multivariate random-effects logistic regression analyses showed different risk factors for the 2 infections.
More suggestions(11)
multivariate random processes
multivariate significant effects
multivariate maternal effects
multivariate main effects
multivariate random parameters
multivariate covariate effects
multivariate prognostic effects
multivariate mixed effects
multivariate random Forests
multivariate random inputs
multivariate random variables
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