PubMed · 495787
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
D R Barker, L M Diana. 1979. Measurement errors and curve fitting.. https://doi.org/10.1152/ajpregu.1979.237.5.r366
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
MOTIVATION: Compositional data are frequently encountered in many disciplines, such as in next-generation sequencing experiments widely used in biomedical studies. Regression analysis with compositional data as either responses or predictors has been well studied. However, when both responses and predictors are compositional, the inventory of analysis tools is surprisingly limited, especially in the high-dimensional setting. Among the few existing methods, most of them rely on a log-ratio transformation to move compositional data from the simplex to real numbers. Yet, a serious weakness of these methods is their failure to handle the substantial fraction of zeroes observed in data collected from next-generation sequencing experiments. RESULTS: To investigate associations between two high-dimensional multi-omics compositions, we propose a composition-on-composition (COC) regression analysis method which does not require log-ratio transformations and hence can handle zeroes in the data. To account for high dimensionality, we estimate regression coefficients using a penalized estimation equation approach. Finally, inference procedures for COC regression are also proposed. Superior performance of COC is demonstrated through both comprehensive numerical simulations and case studies. AVAILABILITY AND IMPLEMENTATION: Source R codes to implement COC method is available at https://github.com/nrios4/COC.
We provide for generalized linear regression models that use natural cubic splines to model predictors an S-Plus function to calculate relative risks (RR), log relative risk (logRR), mean percent change (MPC) for continuous covariates modeled using a logarithmic link as well as adjusted means differences (MD) for the identity link. The function makes explicit use of the natural spline basis functions, the estimated coefficients for each natural spline basis function, and the fitted correlation matrix for the estimated coefficients and can thus accommodate any number of degrees of freedom. The main function produces a publication-quality graph of all of these quantities as compared to a user-specified reference value as well as the associated confidence limits. In another function, specific values of these statistics comparing a vector of values of the independent variable to the reference value can be calculated rather than plotted.
Using data obtained with a full-scale sewage sludge composting facility, this paper studied the effects of ambient air temperature on the composting temperature with varying volume ratios of sewage sludge and recycled compost to bulking agent. Two volume ratios were examined experimentally, 1: 0: 1 and 3: 1: 2. The results show that composting temperature was influenced by ambient air temperature and the influence was more significant when composting was in the temperature rising process: composting temperature changed 2.4-6.5 degrees C when ambient air temperature changed 13 degrees C. On the other hand, the influence was not significant when composting was in the high-temperature and/or temperature falling process: composting temperature changed 0.75-1.3 degrees C when ambient air temperature changed 8-15 degrees C. Hysteresis effect was observed in composting temperature's responses to ambient air temperature. When the ventilation capability of pile was excellent (at a volume ratio of 1:0:1), the hysteresis time was short and ranging 1.1-1.2 h. On the contrary, when the proportion of added bulking agent was low, therefore less porosity in the substrate (at a volume ratio of 3:1:2), the hysteresis time was long and ranging 1.9-3.1 h.