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Site-specific estimates were then pooled using fixed-effect meta-analytic models with inverse variance weighting.
This was investigated across trials by using random effects meta-regression models with inverse variance weighting.
We used fixed- and random-effects models with inverse variance weighting to pool the risk estimates, when appropriate.
The 54 RRHCV/HIV were pooled using DerSimonian Laird random-effects models with inverse variance weighting using the metan command [ 12].
To assess independent predictors of the isocaloric exchange of fructose for carbohydrate, we used multiple regression models with inverse variance weighting selected by all possible regression using the R criterion (NCSS [Number Cruncher Statistical System] software, Kaysville, Utah).
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Multivariate analyses of hospital cost were performed using generalized linear models with inverse-transformed costs.
To quantify the impact of adjustment for confounders, we then meta-analysed the individual study ratios of odds ratios for each outcome separately, using random-effects models with inverse-variance methods.
Secondary objective was to assess 6-month prognosis in term of mortality and persistent renal dysfunction by a logistic model with inverse probability of treatment weighting, considering the treatment most received in the first 7 days.
In all analyses a random effects model with inverse variance weights were applied [ 19].
All analyses will be preformed by applying a random effects model with inverse variance weights [ 37].
Some of the parameter estimates were combined using a random effects model with inverse variance weights [[ 7], Sec.
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