Multiple linear regression was used to test the effect of SRCs on systolic and diastolic blood pressure, respectively. As for the exposure-matched study to test the role of SRCs and the serum renin level on prehypertension/hypertension, nonparametric test was used to compare serum renin level ...
Looking at the results, the sum of X2 (Step 1) and the 20 Multiple Linear Regression Viewpoints, 2013, Vol. 39(1) Tests of Moderation square of the sum of X (Step 2) are identical to the simple slopes for the high risk group and the risk x group interaction term. This is true ...
3. Illustration of the effect of increasing questionnaire length on reducing response rates from meta-regression. The y-axis can be interpreted as the multiple of how many more participants would be needed to achieve the same number of responses given how many times larger the questionnaire being...
and the residue was dissolved in 50 µL of acetonitrile and 0.01 mol/L NaOH (3:1, v/v), then the sample was introduced to the CE system and analyzed. The peak areas of Cpx and Ofx were plotted versus their corresponding concentrations, and the curves were fitted using a least-squares...
We consider four methods to correct for multiple comparisons: [FDR] The standard 1995 FDR method. [MAX] The maximum statistics correction. [CS] Cluster-based + permutation inference, using a cluster-sum statistic of squared t values. [CP] Change point detection based on differences in mean and...
A. et al. Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets. Nat. Commun. 11, 4238 (2020). Ravi, S. & Larochelle, H. Optimization as a model for few-shot learning. 5th Int. Conf. Learn. Represent. https://openreview.net/...
Univariate and multivariate analysis of perioperative outcomes utilized the Mann–Whitney U test, Chi‐squared test, Mantel–Haenszel test of trend, and multiple linear regression. Radical nephrectomies were classified in cT1, cT2a, and cT2b‐T3 subgroups and compared to simple nephrectomies. ...
Multiple linear regression statistical models result in predictor equations incorporating interactive and polynomial terms for evaluation of mutual relationships between the input variations and output responses; quoted as second order polynomial with the form:(1)y=b0+b1x1+b2x2+b3x3+b12x1x2+b13x1x3+...
(mean ± standard error of the number of switches between the two sides of the comb, nurses: 15.2 ± 0.26; other bees: 35.6 ± 0.51; generalized linear mixed-effects model (GLMM) with Poisson error & colony identity as random effect, nurses versus all other bees: d.f....
IPF-LASSO: Integrative-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data. Comput Math Meth Med. 2017;1–14. 8. Boulesteix AL, Schmid M. Machine learning versus statistical modeling. Biom J. 2014;56(4):588–93. 9. Boulesteix AL, Janitza S, Hornung R, ...