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Results from Trial 1, comparing outcomes of patients invited to participate in the SNS in a telephone interview and provided with choice of participation mode (n = 391) are summarized in Table 3.> -wrap-foot> Abbreviations: X = chi square, RR = relative risk.
Bottom right square: rr.
Bottom left square: Rr.
Top right square: Rr.
In our example, we would fill in our squares like this: Top left square: RR.
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When modelled, RRs for month (RR for month 12 relative to month 1 and 95% CI = 1.02 (0.99, 1.06)) and month squared (RR = 0.999 0.9988, 0.999)) indicated a rise in admissions until February 2012, followed by a fall.
The relative resources squared (rrs) is considered a proxy variable of the shadow price of informal care for non-working caregivers (inactive or taking care leave) because individuals with higher income tend to spend less hours in informal caregiving.
Results were obtained by calculating SNP effects for a single replicate of the training data; FR-LS: fixed regression-least squares; RR-BLUP: random regression-BLUP; Bayes-R: Bayesian regression; SVR: support vector regression; PLSR: partial least squares regression.
The training data set included animals born before 1998; ASI: Australian Selection Index; PPT: protein percentage; FR-LS: fixed regression-least squares; RR-BLUP: random regression-BLUP; Bayes-R: Bayesian regression; SVR: support vector regression; PLSR: partial least squares regression.
ASI: Australian Selection Index; PPT: protein percentage; FR-LS: fixed regression-least squares; RR-BLUP: random regression-BLUP; Bayes-R: Bayesian regression; SVR: support vector regression; PLSR: partial least squares regression.
We calculated the root mean square reduction (rr), which is defined as mathrm{r}mathrm{r}=1-sqrt{frac{{displaystyle sum_i{left[Sleft {t}_iright -Oleft {t}_iright -Oleft {t}_irightlaystyle sum_i{left[Oleft({t}_iright)right]}^2}}}, (5)where S(t) and O(t) are the calculated and observed instrument responses, respectively.
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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