Sentence examples for more generalizable conclusions from inspiring English sources

We experiment with random graphs of different natures to derive more generalizable conclusions.

Because of several methodological limitations of the study more research is needed to draw more generalizable conclusions.

While investigations gene expression based on tissue samples was valuable, its use precludes more generalizable conclusions relative to common pathogenic mechanisms.

Immunogenicity in the face of pre-existing immunity and natural boosting will have to be assessed to make more generalizable conclusions.

Consequently, studies across different contexts are needed to allow more generalizable conclusions about emotion regulation, including emotion display in a variety of higher-education teaching and learning settings.

There is likely to be a continued demand for the identification of global research priorities due both to the nature of funding for HPSR and the continued reliance on international funding sources, but also an ongoing need for multi-country research studies that yield more generalizable conclusions.

By introducing the study protocol we hope to stimulate other research groups to replicate and extend the design to ensure comparability between studies, and more valid and generalizable conclusions about the health impacts of implementing PBSP.

However, more studies are needed before generalizable conclusions can be drawn.

Second, the conclusions are more generalizable on account of eligible literature from many different geographic distributions, such as USA, UK, Australia, and China.

(2) A more comprehensive and generalizable conclusion can be achieved in studies that involve various ethnic groups.

When using a larger dataset and running the topic analysis with larger numbers of topics, more-fine-grained topics pointing to specific techniques, skill sets or communities might emerge that would allow to draw conclusions that are more generalizable and point to specific promising citizen science opportunities in the forest monitoring domain.