Increased and decreased proteins. by Diego Iacono (10785756)

Subjects:

Odds and risk for MT in patients with ΔSI ≥ the defined value than those with ΔSI < the defined value. by Shao-Chun Wu (478105)

Values for all quantifications. by Sravya Paluri (5475260)

Within-subject comparison of AUC values for HR, HRV parameters, and cortisol between stress and non-stress conditions. by Rui Cao (800989)

AIC values of each model fit for the analyses on the density values of all considered tracts. by Stefania Conte (9349517)

Model AUC score as a function of the number of estimators (RF trees). by Julia Livermore (17098084)

Model AUC score as a function of the maximum decision tree depth. by Julia Livermore (17098084)

Example of SHAP value distribution for all of the tested patients. by Bartek Rajwa (127236)

Mean values of cell lineages, standard deviation and n-values of all experimental groups. by Tim Pock (12072152)

AUC of different variables to predict 1 year MACCE and mortality. by Chun-Hung Su (184505)

Delete one edge on Karate network to change the consensus opinion—<i>β</i> = 1. by Xi Chen (35903)

Add one edge on Karate network to change the consensus opinion—<i>β</i> = 1. by Xi Chen (35903)

Box plots showing the normalized abundances of the four serum proteins with the highest AUC values in non-PSC controls and PSC patients. by Matilda Holm (5076659)

Results of paired, one-tailed <i>z</i> tests comparing AUC values for echo decorrelation prediction of treated regions in liver and VX2 tumor vs. chance (AUC = 0.5). by Mohamed A. Abbass (8087744)

Estimated parameter values of all competitive models. by Govinda Prasad Dhungana (9154004)

Results of AUC analysis. by Ji Yoon Ban (18611051)

Percent increase in BLL for every 10% increase in environmental lead levels in household samples for all children. by M. J. Brown (7602548)

Costs and Benefits of Popular <i>P</i>‑Value Correction Methods in Three Models of Quantitative Omic Experiments by Steven R. Shuken (14500192)

“…Overall, permutation had better FDR and sensitivity than BH. We show how increasing sample size, decreasing variability, or increasing effect size can enable the detection of all true changes while still correcting <i>p</i>-values, and we present basic guidelines for omic experimental design. …”

Critical ratio value and item-total correlation of all items. by Yiqing He (542544)

All raw data values shown in this study. by Emily E. Whitaker (17935732)