The term "summary coefficient" may not be accurately or commonly used in written English
It is possible that you mean "summary statistic" or "summary measure", which are more commonly used phrases in statistics and data analysis. A summary coefficient is a numerical value that summarizes a dataset and provides an overall understanding of its key features. For example, the mean, median, and standard deviation are all summary statistics commonly used to describe a set of data.
(D ) Summary of coefficient of variation (C.V). of the DMSO control.
In the corresponding analyses with ln RR) as the outcome, the summary regression coefficient was also not statistically significant (β = −0.00018; 95% CI: −0.00107, 0.00072; P = 0.64).
We used these regression coefficients to calculate inverse variance weighted summary β coefficients for PFOS and PFOA.
To control for all other variables and illustrate the relative influence of each variable on student incoming understanding of natural selection, we conducted a multiple linear regression (see Table 5 for a summary of coefficients, standard errors, and statistical significance): R 2 = .24 (R = .49); F (6, 169) = 8.788, p < .001 (Adjusted R 2 = .21).21
To control for all other variables and illustrate the relative influence of each variable on students' incoming acceptance of evolution, we conducted a multiple linear regression (see Table 4 for a summary of coefficients, standard errors, and statistical significance): R 2 = .50 (R = .71); F (6, 169) = 28.50, p < .001 (Adjusted R 2 = .49).49
Also, the summary H coefficients, here equal to 0.55 (well-being) and 0.63 (distress), suggests that both subscales are homogeneous enough to be considered as unidimensional measures.
The summary β coefficients for grams birth weight per nanograms per milliliter increase in PFOA and PFOS levels were –14.7 g (95% CI: –21.7, –7.8) and –5.0 g (95% CI: –8.9, –1.1), respectively.
In addition, all kidney disease-specific domains were significantly correlated with two generic component summaries, with coefficients ranging from 0.333 to 0.511.
With an application to the case study of Danyang, China, we measure the distantial functions of the urban environment (e.g. the surrounding land uses) including both the most influential scopes and the relative contributions by means of model summary and regression coefficient comparisons.
Predicted interologs from STRING experimental PPIs and a summary of Jaccard coefficient, precision and recall between the interologs datasets and two benchmarks.
