A Semi-Supervised Method for Prediction of Phenotype Event Times

Evaluating Geographic Sampling Bias in Biological Collections

Comparing and Visualizing Differences Between Surveys

Sampling Strategies for Constructing Core Collections

Sample Design, Drawing & Data Analysis Using Data Frames

R package sampleSelection version 1.2-14

Sample Size Calculation for Various t-Tests and Wilcoxon-Test

Sample Size Calculation for the Comparison of Means or
Proportions in Phase III Clinical Trials
R package SampleSize4ClinicalTrials version 0.2.3

Sample Size Calculations for Complex Surveys
R package samplesize4surveys version 4.1.1

Sample Size Calculator under Complex Survey Design
R package SampleSizeCalculator version 0.1.0

Power and Sample Size Calculation for the
Cochran-Mantel-Haenszel Test

Choosing Sample Size for Evaluating a Diagnostic Test
R package SampleSizeDiagnostics version 0.1.1

Calculate Sample Size for Various Scenarios
R package samplesizeestimator version 1.0.0

Sample Size and Power Calculations for Case-Control Studies
R package samplesizelogisticcasecontrol version 2.0.2

Sample Size Calculations for Normal Means

Calculating Sample Size Requirements when Estimating the
Difference Between Two Binomial Proportions
R package SampleSizeProportions version 1.1.3

Calculate Sample Size for Single-Arm Survival Studies
R package SampleSizeSingleArmSurvival version 0.1.0

Draw Stratified Samples from the VADIR Database

Generate Samples with a Variety of Probability Distributions

Optimal Stratification of Sampling Frames for Multipurpose
Sampling Surveys

Compare Human Performance to Sampling Algorithms

Sample Size for Validation of Risk Models with Binary Outcomes

SAM: Significance Analysis of Microarrays

Merge-Split Samplers for Conjugate Bayesian Nonparametric Models

Sensitivity Assessment to Unmeasured Confounding with Multiple
Treatments
R package SAMTx version 0.3.0

Stochastic Augmentation of Matched Data Using Restriction
Methods
R package SAMUR version 1.1

Fitting Shared Atoms Nested Models via MCMC or Variational Bayes