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All data were analyzed by ANOVA using a fixed model testing the main effect of diet.
We performed Mantel-Haenszel meta-analysis using a fixed model to calculate the OR and P values for the combined cohorts [33].
Results from these studies were first pooled by using a fixed model and then included in the overall risk estimate.
Table 8 shows that for the proteobacteria dataset when the optimal models were used to infer the trees, the median RF distance was lower than using a fixed model in the majority of cases.
The combined mean difference between probes, using a fixed model,was 0.9 mmHg, with a 95%% confidence interval (CI) for the mean of 0.4 1.5 mmHg across Group 1 studies and 1.8 mmHg (95 % CI 1.5 2.2 mmHg) across Group 2 studies.
If anything, using a fixed model shifts the outcome from equal survival towards a small benefit for diabetic patients in the medical and mixed ICU cohorts for in-hospital mortality, which can be attributed to the inclusion of two very large cohorts [ 26, 101].
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Bent's pooled LR indexes were calculated using a random effects model, whereas ours were calculated using a fixed effects model with corresponding differences in confidence intervals.
The pooled OR was estimated using a fixed effects model under dominant and co-dominant heredity models.
STATA 8.0 was used to calculate Mantel-Haenszel (M-H) pooled ORs and test for heterogeneity between datasets, using a fixed effects model in the absence, and a random effects model in the presence, of heterogeneity.
We intended to report results using a fixed effects model throughout, but we had to use a random effects model for symptom score and peak urine flow rate because of statistical heterogeneity, explored by χ tests and I statistics.
Analyses were undertaken using a fixed effects model; in case of substantial heterogeneity (I ≥50%) a random effects model was used.
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