Sentence examples for model of log from inspiring English sources

We fit a mixed-effects model of log endotoxin levels as a function of room and season adjusting for the correlation of repeated measurements within the same home.

A mixed-effects model of log dust and log gas-phase air concentrations with chemical designated as a random effect also revealed a significant relationship between air and dust (β = 0.34, p < 0.001).

Once comorbidity was taken into account, the hospitalization costs did not differ between children and adults (p < .7).>> Results for the regression analysis for the two part model of log total costs are given in Table  5.

Preliminary data from the ORPS cohort (1,697 sets of urines from 479 subjects) indicated that the log standardized ACR based on the residuals from a regression model of log ACR adjusted for age, gender, age at diagnosis and duration of diabetes at 11-15 years was highly predictive of risk for the development of MA [ 44].

A linear regression model of log-transformed variables over all samples shows a negative association ((beta=-0.48), (p<0.001), more details in SI Table 2), consistent with the results using only disclosing alters of the previous section.

A reduced model of log-transformed rate of antimicrobial prescriptions with time only was then estimated.

To assess the influence of month of blood draw on serum concentrations of vitamin D, a simple mathematical model of log-transformed serum vitamin D concentration by month of blood collection (as a categorical variable) was fitted.

Exposures significantly associated with leptin or adiponectin at a p-value <0.05 were further examined in a multivariate generalized linear regression model of log-transformed exposures and outcomes in order to provide a magnitude of effect.

To determine whether the magnitude of a seasonal dengue epidemic could be predicted by the dengue activity in the previous interepidemic period, we used a linear model of log-transformed dengue incidence during the epidemic period (April December) in each district or province as a function of the incidence during the preceding dry period (January March) in the same district or province.

Results are reported as percent reductions and significance is based on t-tests and ANOVA models of log reductions.

All association p values are from linear models of log(BMI).