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However, one should exercise caution in interpreting these estimates in a causal fashion, as they may still suffer for an omitted variable bias.
Without robust data on the motives, circumstances, and results of every mass shooting in the US and Europe over a long period, it's important to exercise caution in interpreting anecdotal evidence.
Beyond these methodological limitations, one must also exercise caution in interpreting the observed associations as evidence of a causal link, as van Melle et al. imply based on the association between increasing A1C and heart failure risk.
However, we need to exercise caution in interpreting the lack of significance across countries from the multilevel models given the small number of countries (n = 20) and consequent reduced statistical power to detect significant factors at this level.
The reader should exercise caution in interpreting such data as sample sizes are small and not all women provided complete data and the proportion that provided complete data is not equal across groups.
However, we must exercise caution in interpreting these findings because smoking prevalence is higher among psychiatric patients [ 56]; nonetheless, another study controlling for smoking found schizophrenia to be an independent risk factor for COPD [ 57].
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The importance of understanding the effects of UV exclusion in artificial ecosystems and the importance of exercising caution in interpreting the data from artificial enclosed ecosystems in the context of the natural world, is discussed.
We have exercised caution in interpreting our findings given that we were unable to adjust for the presence or severity of comorbid medical conditions or medication usage, which may have been confounders in the relationship between ethnicity and diabetes management (24).
Given that these estimates come from averaging heterogeneous studies, we should exercise some caution in interpreting the rank order of the Gini coefficients.
Therefore, we have exercised considerable caution in interpreting these data and have identified this area as one in which the effects of bias on the final estimates are likely to be most profound (Table 5).
Researchers should exercise caution when interpreting the γ statistic in studies examining diversification rate variation, and should supplement this approach with other methods aimed at detecting rate variation (e.g., [5], [8], [10]).
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CEO of Professional Science Editing for Scientists @ prosciediting.com