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Table 3 Strengths and limitations of the three approaches for gauging the effective degree of power and precision in indirect comparisons

From: Sample size and power considerations in network meta-analysis

Approach Strengths Limitations
Effective number of trials 1. Easy and fast to calculate 1. Only valid to the extent trial sample sizes are equal and heterogeneity is absent
2. Lacks flexibility for approximate trial count ratios
Effective sample size (ignoring heterogeneity) 1. Easy and fast to calculate 1. Does not account for heterogeneity
2. Exact calculations for all trial count ratios 2. Assumes equal meta-analysis population variances across comparisons
3. Sample size (no. of patients) resonates well with clinicians
Effective sample size (correcting for heterogeneity) 1. Exact calculations for all precision ratios 1. Assumes equal meta-analysis population variances across comparisons
2. Accounts for heterogeneity 2. Depends on precise heterogeneity estimation
3. Easy to calculate
4. Sample size (no. of patients) resonates well with clinicians 1. Statistical information does not resonate well with a clinical audience
Effective statistical information 1. Theoretically statistically exact
2. Not straight forward to calculate
   3. Depends on precise heterogeneity variance estimation or requires elicitation of Bayesian variance priors