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Analyses for cross-sectional associations were performed using repeated measures with adjustment for the correlation between measurements in a given individual using mixed effects models (PROC MIXED) for continuous outcomes (FEV1, FVC, FEV1/FVC) and generalised estimating equations (PROC GENMOD) for binary outcomes (COPD).
Mixed models take into account the correlation between measurements in a given subject and more importantly use the whole information (i.e. all the measurements), providing a greater power than when the outcome is dichotomised as, for example, in logistic regression analysis.
When conducting research on laboratory animals, experimentalists often strive for the following [1]: replicability (low variation between measurements in a given test), repeatability (low variation among replicate tests within a laboratory), and reproducibility (similar outcomes in comparable experiments from different laboratories).
CD4 cell gains were modeled using piecewise linear mixed-effects models in order to take into account the correlation between measurements in a given subject.
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Electrode surfaces were deactivated in-between measurements in a complex liquid, like tea.
Assuming that BG changes at a constant rate between measurements in response to a constant insulin dose, we used the following model to examine time to hypoglycemia and time spent in hypoglycemia: for each hypoglycemic measure, we assumed a constant decrease of 0.05 mmol/L/min from the previous BG measure, based on usual protocol performance.
Going forward, further emphasis should be placed on understanding the interdependencies between measurements in conjunction with a rational selection of tracers and the overarching philosophy of isotopic experiment design.
The degree of such G × E interaction can be estimated using the genetic correlation (rg) between measurements in two environments for a given trait.
The results indicated a good correlation between measurements in serum and citrate plasma for all hormones measured (0.9899 ≤ r2 ≤ 0.9997).
The debate about differences between measurements in the mid-infrared, which suggest a possible expansion and contraction of the star, and the near-infrared, which advocates a relatively constant photospheric diameter, remains to be resolved.
Preliminary analyses showed that the correlations between measurements in individual children were best modelled using an exchangeable correlation structure.
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