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We used multilevel logistic regression analysis to estimate the probability of prescribing a recommended statin, while accounting for the hierarchical structure of the data (i.e., patients nested within HCCs nested within HCAs) represented in figure 1[ 17, 17].
For the first part we used logistic regression analysis to estimate the probability of FFS > 0, and for the second part (expected FFS given that FFS > 0) a gamma regression with log link was used.
Subsequently, logistic regression analysis to estimate the probability of DAS28<3.2 at the primary end point as dependent variable by DAS28 at RRR-entry as independent variable was assessed.
Finally, we also conducted a within-subject permutation analysis to estimate the probability of observing significant phase locking (between theta and reactivations) based on the true temporal correlation structure of the reactivation vectors (see Supplemental Information for details and Figure S5 for results).
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A priori power analysis enables researchers to estimate the probability of making a Type II error (i.e., finding no significant difference when one in fact exists).
A Kaplan-Meier survival analysis was used to estimate the probability of improved visual acuity with time after surgery.
Kaplan Meier analysis was used in order to estimate the probability of survival [ 18].
Additionally, multivariate analysis of clinical symptoms and laboratory findings was performed to estimate the probability of LDIE.
These probabilities can be multiplied together to estimate the probability of surviving 20 years.
A Kaplan Meier survival analysis was performed to estimate the probabilities of survival.
We used the Kaplan-Meier analysis to estimate the event-free probability of Crohn's disease after enrollment.
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