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Discover LudwigSuggestions(5)
"make causal inferences" is correct and usable in written English.
You can use it when you are trying to explain how certain conclusions were reached through analyzing data or evidence. For example: "The researchers used the data to make causal inferences about the underlying causes of the observed trends."
Exact(59)
Again, we cannot make causal inferences from the data.
Because it was a cross-sectional study, it is not possible to make causal inferences.
The correlation analyses of this study restrict our ability to make causal inferences on the relationship between insomnia and headaches.
Lacking of an experimental design, this study cannot make causal inferences on the relation between CIL and e-communication.
Another limitation is the cross sectional nature of the census which limits the ability to make causal inferences.
This article explores strengths of randomization to enhance the appropriateness of using statistical theory to make causal inferences.
We describe how to make causal inferences more robust to misspecification of covariates in such analyses and how to summarize and present these interactive intervention effects clearly.
One limitation is its cross-sectional design which limits the ability to make causal inferences and examine how the regional inequalities evolve over time.
The authors have presented baseline (i.e, cross-sectional) data from this larger prospective cohort meaning we were unable to make causal inferences.
In keeping with his project of providing a naturalistic account of how our minds work, Hume has given empirical explanations of our propensity to make causal inferences, and the way those inferences lead to belief.
Similar(1)
Moreover, to make causal inference more convincing, we ensured that, except for year variables, all explanatory variables are lagged by one period.
More suggestions(15)
make statistical inferences
make novel inferences
make causal interpretations
make causal laws
make causal conclusions
make correct inferences
make causal links
make causal attributions
make causal connections
make direct inferences
make valid inferences
make accurate inferences
make reliable inferences
make strong inferences
make reasonable inferences
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com