We then used a linear mixed-effects regression model to refine this comparison and to compensate for data attrition linked to differences in the numbers of serial samples analyzed for each patient (n = 1 9).
Potential trends in position over the 4-year period were evaluated using a linear mixed-effects regression model.
Using a linear mixed-effects model, there was no interaction between wing orientation and substrate (F3,105 = 1.66, p = 0.18, Supplementary file 1; Table 1a for model estimates).
Using a linear mixed-effects model to statistically analyze the data in Figure 6B, we found that the Atelp3-10 mutation did not have statistically significant effect on SAR treatment-induced resistance to Psm ES4326 (p = 0.279).
Using a linear mixed-effects model to statistically analyze the data in Figure 5B, we found that the Atelp3-10 anpr1pr1 mutations did not have statistically significant genetic interaction in resistance against Pst DC3000/ avrRpt2 (p = 0.064); therefore, AtELP3 and NPR1 appear to function largely independently of each other in ETI-mediated resistance to Pst DC3000/ avrRpt2.
To better understand the relationship between human population density and growth, rates of change in forest cover, and protection status, we used a linear mixed-effects modeling approach to predict the rate of change in forest cover between 1992 and 2001.
The BAER approach (Bremen AErosol Retrieval), von Hoyningen-Huene et al., 2003, uses a linear mixing model of spectra for 'green vegetation' and 'bare soil', tuned by the NDVI, determining an apparent surface to enable this separation of aerosol and surface properties from VIS and NIR channels.
The OTUs responding significantly to experimental treatment were detected using a linear mixed-effects model followed by a test to account for false discovery rates.
Statistical analysis used a Linear Mixed Model (random effects) univariate ANOVA to determine if the pupil light reflex components varied significantly with circadian time.
Differences in superoxide production were tested using a Linear Mixed Model with sex used as a fixed factor and session number as a random factor since measures have been performed in 3 different sessions.
