Problem

Randomized study A reports effect \(5\) and \(p~=~0.01\); randomized study B reports effect \(6\) and \(p~=~0.20\). Compare statistical evidence, observed magnitude, causal support, and population scope.

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What this problem is really about

Compare the reports on separate axes rather than forcing one overall ranking. Smaller p-values indicate stronger evidence against a no-effect model, numerical effects describe observed magnitude, random assignment governs participant-level causal support, and sampling or recruitment governs population reach. When different studies lead on different axes, an overall preference requires an explicit decision criterion.

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B has stronger statistical evidence and the larger observed magnitude. Both support causal comparisons among participants, with no stated population scope.

A has stronger statistical evidence and the larger observed magnitude. Both support causal comparisons among participants, and both automatically generalize to a population.

A has stronger evidence and B has larger magnitude, but their p-values establish population generalizability while causal support is unknown.

A has stronger statistical evidence; B has the larger observed magnitude. Both support causal comparisons among participants, and neither has stated population scope.

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Randomized study A reports effect \(5\) and \(p~=~0.01\); randomized study B reports effect \(6\) and \(p~=~0.20\). Compare statistical evidence, observed magnitude, causal support, and population scope.

What this problem is really about

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