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We stand behind our fixed estimates for projects, so if we are off, we lose money.
We estimated divergence times based on two fixed estimates of 2% and 5% divergence per million years in COI and 0.194% in RAG2.
The additional file 4 shows how practically these fixed estimates can be obtained with an example of the different output given in additional file 5. *Treatment effect estimates in presence of a center effect.
Using realistic fixed estimates of the mean and standard deviation of effects and costs at population level (based on Hakkaart-van Roijen et al., 2006), we simulated a large number of trials in which we systematically varied sample sizes between n = 10 to n = 500 per group (n = 10, 25, 50, 75, 150, 500).
Each parameter corresponds to the predicted value for each individual, using both random and fixed estimates.
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The ratio is then denoted by "Fixed estimate MSE".
Therefore, in every table below, in addition to the fixed effect estimates, we also report IV estimates using separate columns.
Also reported are the fixed effect estimates, in terms of the associated odds ratio estimates, with 95% confidence intervals.
No significant differences on the fixed effect estimates however were observed after re-estimation of the model on data that excluded any prescriptions from this specific pharmacy.
The fixed model estimates in-use degradation for those fixed time points of closed container where the in-used experimental data is collected.
When D ≈ 0 we get the corresponding fixed effects estimates, whereas when D ≠ 0 we get the random effects 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