Sentence examples for differences in inferences from inspiring English sources

For a subset of our analyses, we tried two different masks (conservative vs. liberal) of ambiguous positions and found no significant differences in inferences from topologies and support (data not shown).

As there were no differences in inferences between unadjusted (for baseline values) and adjusted models, we report only unadjusted results here.

Considering the pair wise heterogeneity variance estimates as the bench mark, we then assessed the extent to which observed differences in inferences between MTC models could be explained by poor estimation of between-study heterogeneity variances and their posterior distributions.

We switched to the method of measuring inferences – a reliable and long-standing indirect measure of mental representations (e.g., Johnson-Laird, 2006) – because our account of differences in the mental representations of causes and counterfactuals commits us to the prediction that there should accordingly be differences in inferences from them.

We document differences in inference in comparing those that were asked one question first versus those that were asked the other.

Differences in inference could be present as RE models can at times be more efficient and have lower standard errors.

These differences in inference probably arose because data from restricted geographical regions or ethnicities were analyzed.

We were interested in differences in inference that could be made from the various models, which integrate information about the point estimates of treatment effects and the precision of their estimation but may vary in their assumptions.

We also compared the inferences people made from a counterfactual in a story with counterexamples, but for which they were provided with a ready made counterfactual, to establish that differences in inference frequency did not occur merely because of the self-generated nature of the counterfactual.

There are substantial differences in the inferences we draw using estimates in column (2), which makes location adjustments, and column (1), which does not.

Prior studies of human harvesting and its effect on wolf dynamics [10], [16] were also based on comparison across populations, so the differences in our inferences are not due to this distinction.