1-20 of 19041
Sort by
Journal Article
Bryan Blette
Published: 18 April 2025
Image
Published: 12 April 2025
FIGURE 2 UpSet plot showing the number of significant single nucleotide polymorphisms (SNPs) by each method (in the rows) combining all chromosomes. It also shows different intersections (in the columns) of the rejected hypotheses by different methods (intersections with a minimum size of 15 are shown only).
Journal Article
Rajesh Karmakar and others
Biometrics, Volume 81, Issue 2, June 2025, ujaf035, https://doi.org/10.1093/biomtc/ujaf035
Published: 12 April 2025
Image
Published: 12 April 2025
FIGURE 1 The left column displays scatter plots of , while the right column shows the density estimates of for . The -score vector is generated according to model ( 7 ) with , , , and . Rows represent various covariance structures: Row (a) correspond to an AR(1) covariance with ;
Journal Article
Aristidis K Nikoloulopoulos
Biometrics, Volume 81, Issue 2, June 2025, ujaf037, https://doi.org/10.1093/biomtc/ujaf037
Published: 08 April 2025
Image
Published: 08 April 2025
FIGURE 1 Graphical representation of the D-vine copula with 5 variables and 4 levels.
Image
Published: 08 April 2025
FIGURE 2 Graphical representation of the 5-dimensional 1-truncated D-vine copula model.
Journal Article
Fengyu Zhao and others
Biometrics, Volume 81, Issue 2, June 2025, ujaf036, https://doi.org/10.1093/biomtc/ujaf036
Published: 07 April 2025
Image
Published: 07 April 2025
FIGURE 1 Numerical study I: simulated power of the conventional Wald tests and the adjusted tests for relative risk (RR) with Model 1.1, , and . The curves represent the power of conventional tests ( and ) under complete randomization (CR); conventional tests under covariate-adaptive randomizatio
Image
Published: 07 April 2025
FIGURE 2 Numerical study II: simulated power of the conventional Wald tests and the adjusted tests for relative risk (RR) with Model 2.3, , and . The curves represent the power of conventional tests with and under complete randomization (CR); the conventional tests with and under covari
Journal Article
Shuo Sun and others
Biometrics, Volume 81, Issue 2, June 2025, ujaf038, https://doi.org/10.1093/biomtc/ujaf038
Published: 07 April 2025
Image
Published: 07 April 2025
FIGURE 2 Comparison of pointwise 95% confidence intervals versus uniform bands for the point QTE estimates of a realization. The left panel is in homogeneous QTE setting. The right panel is in heterogeneous QTE setting. Pointwise confidence intervals were estimated using the asymptotic and bootstrap variance
Image
Published: 07 April 2025
FIGURE 1 Pointwise relative bias and 95% confidence interval coverages of QTE estimates across quantile levels. Row (A): Homogeneous QTE setting. Row (B): Heterogeneous QTE setting. Left and middle columns: Relative bias. Right column: Pointwise 95% confidence interval coverage Estimators (I)-(V) denote the
Image
Published: 07 April 2025
FIGURE 3 (A) The =13 514 samples. (B) Stratified by diabetes status. (C) Stratified by dyslipidemia diagnosis. Left column: Pointwise QTE estimates and 95% pointwise bootstrap CIs across quantile levels; point estimates are marked with dots. Right column: Comparison of 95% pointwise bootstrap CIs versus u
Image
Published: 02 April 2025
FIGURE 1 Bar plots and density plots of the normalized mean differences in real data analysis.
Journal Article
Danning Li and others
Biometrics, Volume 81, Issue 2, June 2025, ujaf034, https://doi.org/10.1093/biomtc/ujaf034
Published: 02 April 2025
Journal Article
Li-Pang Chen
Published: 01 April 2025
Journal Article
Li-Pang Chen
Published: 31 March 2025
Image
Published: 24 March 2025
FIGURE 1 Comparison of existing and proposed methods to estimate regression to the mean and treatment effects from simulated data.
Journal Article
Manzoor Khan and Jake Olivier
Biometrics, Volume 81, Issue 1, March 2025, ujaf033, https://doi.org/10.1093/biomtc/ujaf033
Published: 24 March 2025