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In this analysis, we reported the results of models using raw scores for two reasons.
In our analyses, we performed GEE models using raw data and also using data corrected for storage duration.
As a sensitivity analysis, we also re-ran the same mixed models using raw lung function measures (FEV1 and FVC, in liters) further adjusted for baseline age and height.
The models using raw FEV1 and FVC measured in liters additionally adjusted for baseline age and height gave similar results to those found using the percentage of predicted values (data not shown).
State-based models of cognitive change or individual trajectory models using raw scores need multiple waves to help overcome natural variation in MMSE scores and to help identify true cognitive change.
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A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input.
The Kalman filter model is able to better detect relationships between health metrics and the more complex disease progression definition than the logistic regression model using raw observations as inputs.
We aimed to measure the rate and extent of lipolysis in an in vitro duodenum digestion model, using raw and roasted almond materials with potentially different degrees of bioaccessibility.
For comparison, we also computed FDRs resulting from our log-linear model using raw, rather than cube-rooted data, as well as FDRs resulting from computing a paired two-sample t-statistic for each miRNA (using both raw and cube-rooted data).
As this URTK model uses raw observations instead of the ionospheric-free combinations, it is applicable for both dual- and single-frequency users to realize the URTK service.
Alternatively, the LRE method, derived from sigmoidal modeling, uses raw fluorescence data to calculate molecules and amplification efficiency for each sample, and thus has the advantage of not requiring or relying on standard curves.
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