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These estimates will allow other researchers using these variables to plan their studies by performing a priori power analyses for any of four common analytic options.
Both additive and multiplicative models were tested using these variables to predict carriage of C79F, and the additive model provided a better fit (p = 0.019).
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Either way, we can still use these variables to make predictions.
A logistic regression analysis that uses these variables to predict whether a senator supports same-sex marriage yields the following results: The two variables that show up as highly statistically significant are the senator's ideology rating and the estimated support for same-sex marriage among voters in his state.
We use these variables to capture family income levels which are also potentially important variables that affect achievement.
One interesting indication in this context would be to use these variables to monitor therapy of bone metastases.
Such an approach increases the reliability of measures and statistical analyses that use these variables to answer fundamental research questions.
To be clear, we did not use these variables to map the known physiological limits.
Taken together with PCNM, we used these variables to operationally define the thermal niche experienced by the individuals.
We used these variables to perform Canonical Correspondence Analysis (CCA) using OTUs at a 99% similarity cut-off with both samples and sites.
Researchers will use these variables to individualise weekly step goals to increase walking.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com