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Each of these was added to a model containing the main variable of interest (in quartiles) and if at least two of the quartile parameter estimates changed by more than 10% then the variable was considered a potential confounder.
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Figure 2 shows the parameter estimates for reading test results by quartiles of VP performance where the reference category is the top quartile (best VP performance).
Table 4 presents the quartiles of the revenue shares of adjustment costs based on the parameter estimates in Table 3. Rather than picking a specification arbitrarily, for each adjustment cost parameter its maximum estimate across all specifications for the case of total value of shipments in Table 3 is used to obtain the estimates in Table 4.
Table 2 Parameter estimates for final model.
All parameter estimates are reported in Supplementary Table 3.
Table 1 summarises relevant parameter estimates.
All parameter estimates showed significant ESS (>300).
All parameter estimates showed significant ESS (>250).
† Parameter estimates can be interpreted as differences in mean gait speed (m/sec) compared male (or female) subjects in the 2nd, 3rd, and 4th quartiles of HOMA-IR to those in the lowest quartile.
†Weighted parameter estimates.
Analysis of Parameter Estimates.
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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