All packages

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support.BWS2 — 0.4-0

Tools for Case 2 Best-Worst Scaling

support.BWS3 — 0.2-1

Tools for Case 3 Best-Worst Scaling

support.CEs — 0.7-0

Basic Functions for Supporting an Implementation of Choice Experiments

supportR — 1.4.0

Support Functions for Wrangling and Visualization

sur — 1.0.4

Companion to "Statistics Using R: An Integrative Approach"

surbayes — 0.1.2

Bayesian Analysis of Seemingly Unrelated Regression Models

sure — 0.2.0

Surrogate Residuals for Ordinal and General Regression Models

sureLDA — 0.1.0-1

A Novel Multi-Disease Automated Phenotyping Method for the EHR

SuRF.vs — 1.1.0.1

Subsampling Ranking Forward Selection (SuRF)

surface — 0.6

Fitting Hansen Models to Investigate Convergent Evolution

SurfaceTortoise — 2.0.1

Find Optimal Sampling Locations Based on Spatial Covariate(s)

SurfRough — 0.0.1.1

Calculate Surface/Image Texture Indexes

surreal — 0.0.1

Create Datasets with Hidden Images in Residual Plots

Surrogate — 3.4.1

Evaluation of Surrogate Endpoints in Clinical Trials

SurrogateBMA — 1.0

Flexible Evaluation of Surrogate Markers with Bayesian Model Averaging

SurrogateOutcome — 1.1

Estimation of the Proportion of Treatment Effect Explained by Surrogate Outcome Information

SurrogateParadoxTest — 2.0

Empirical Testing of Surrogate Paradox Assumptions

SurrogateRank — 1.0

Rank-Based Test to Evaluate a Surrogate Marker

SurrogateRegression — 0.6.0.1

Surrogate Outcome Regression Analysis

SurrogateRsq — 0.2.1

Goodness-of-Fit Analysis for Categorical Data using the Surrogate R-Squared

SurrogateSeq — 1.0

Group Sequential Testing of a Treatment Effect Using a Surrogate Marker

SurrogateTest — 1.3

Early Testing for a Treatment Effect using Surrogate Marker Information

surrosurv — 1.1.26

Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data Meta-Analyses

surrosurvROC — 0.1.0

Surrogate Survival ROC

surtvep — 1.0.0

Cox Non-Proportional Hazards Model with Time-Varying Coefficients

surv2sampleComp — 1.0-5

Inference for Model-Free Between-Group Parameters for Censored Survival Data

survAH — 1.0.0

Survival Data Analysis using Average Hazard

survAUC — 1.3-0

Estimators of Prediction Accuracy for Time-to-Event Data

survAWKMT2 — 1.0.1

Two-Sample Tests Based on Differences of Kaplan-Meier Curves

survBootOutliers — 1.0

Concordance Based Bootstrap Methods for Outlier Detection in Survival Analysis

survC1 — 1.0-3

C-Statistics for Risk Prediction Models with Censored Survival Data

survcompare — 0.2.0

Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests

SurvCorr — 1.1

Correlation of Bivariate Survival Times

survCurve — 1.0

Plots Survival Curves Element by Element

SurvDisc — 0.1.1

Discrete Time Survival and Longitudinal Data Analysis

surveil — 0.3.0

Time Series Models for Disease Surveillance

surveillance — 1.24.1

Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

survELtest — 2.0.1

Comparing Multiple Survival Functions with Crossing Hazards

SurvEval — 1.1

Methods for the Evaluation of Survival Models

survex — 1.2.0

Explainable Machine Learning in Survival Analysis

survexp.fr — 1.2

Relative Survival, AER and SMR Based on French Death Rates

survey — 4.4-2

Analysis of Complex Survey Samples

surveybootstrap — 0.0.3

Bootstrap with Survey Data

SurveyCC — 0.2.1

Canonical Correlation for Survey Data

surveyCV — 0.2.0

Cross Validation Based on Survey Design

surveydata — 0.2.7

Tools to Work with Survey Data

SurveyDefense — 0.2.0

Survey Defense Tool

surveydown — 0.11.0

Markdown-Based Programmable Surveys Using 'Quarto' and 'shiny'

surveyexplorer — 0.2.0

Quickly Explore Complex Survey Data

surveygraph — 0.1.2

Network Representations of Attitudes

surveynnet — 1.0.0

Neural Network for Complex Survey Data

surveyplanning — 4.0

Survey Planning Tools

surveyPrev — 1.0.0

Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas

surveysd — 1.3.1

Survey Standard Error Estimation for Cumulated Estimates and their Differences in Complex Panel Designs

surveytable — 0.9.7

Formatted Survey Estimates

surveyvoi — 1.1.1

Survey Value of Information

survHE — 2.0.3

Survival Analysis in Health Economic Evaluation

SurvHiDim — 0.1.1

High Dimensional Survival Data Analysis

survIDINRI — 1.1-2

IDI and NRI for Comparing Competing Risk Prediction Models with Censored Survival Data

survidm — 1.3.2

Inference and Prediction in an Illness-Death Model

SurviMChd — 0.1.2

High Dimensional Survival Data Analysis with Markov Chain Monte Carlo

SurvImpute — 0.1.0

Multiple Imputation for Missing Covariates in Time-to-Event Data

survival — 3.8-3

Survival Analysis

survival.svb — 0.0-2

Fit High-Dimensional Proportional Hazards Models

survivalAnalysis — 0.3.0

High-Level Interface for Survival Analysis and Associated Plots

SurvivalClusteringTree — 1.1.1

Clustering Analysis Using Survival Tree and Forest Algorithms

survivalmodels — 0.1.191

Models for Survival Analysis

survivalMPL — 0.2-4

Penalised Maximum Likelihood for Survival Analysis Models

survivalMPLdc — 0.1.1

Penalised Likelihood for Survival Analysis with Dependent Censoring

survivalPLANN — 0.1

Neural Networks to Predict Survival

survivalREC — 1.1

Nonparametric Estimation of the Distribution of Gap Times for Recurrent Events

survivalROC — 1.0.3.1

Time-Dependent ROC Curve Estimation from Censored Survival Data

survivalSL — 0.97.1

Super Learner for Survival Prediction from Censored Data

survivalsvm — 0.0.6

Survival Support Vector Analysis

SurvivalTests — 1.0

Survival Tests for One-Way Layout

survivalVignettes — 0.1.6

Survival Analysis Vignettes and Optional Datasets

survivoR — 2.3.5

Data from all Seasons of Survivor (US) TV Series in Tidy Format

SurvLong — 1.5

Analysis of Proportional Hazards Model with Sparse Longitudinal Covariates

SurvMA — 1.6.8

Model Averaging Prediction of Personalized Survival Probabilities

SurvMetrics — 0.5.1

Predictive Evaluation Metrics in Survival Analysis

SurvMI — 0.1.0

Multiple Imputation Method in Survival Analysis

survminer — 0.5.0

Drawing Survival Curves using 'ggplot2'

survMisc — 0.5.6

Miscellaneous Functions for Survival Data

survmixer — 1.3

Design of Clinical Trials with Survival Endpoints Based on Binary Responses

survML — 1.2.0

Tools for Flexible Survival Analysis Using Machine Learning

survNMA — 1.1-1

Network Meta-Analysis Combining Survival and Count Outcomes

survobj — 3.1.1

Objects to Simulate Survival Times

survout — 0.1.0

Excel Conversion of R Surival Analysis Output

survParamSim — 0.1.7

Parametric Survival Simulation with Parameter Uncertainty

survPen — 2.0.2

Multidimensional Penalized Splines for (Excess) Hazard Models, Relative Mortality Ratio Models and Marginal Intensity Models

survPresmooth — 1.1-12

Presmoothed Estimation in Survival Analysis

SurvRegCensCov — 1.7

Weibull Regression for a Right-Censored Endpoint with Interval-Censored Covariate

survRM2 — 1.0-4

Comparing Restricted Mean Survival Time

survRM2adapt — 1.1.0

Flexible and Coherent Test/Estimation Procedure Based on Restricted Mean Survival Times

survRM2perm — 0.1.0

Permutation Test for Comparing Restricted Mean Survival Time

survSAKK — 1.3.1

Create Publication Ready Kaplan-Meier Plots

survSens — 1.1.0

Sensitivity Analysis with Time-to-Event Outcomes

survsim — 1.1.8

Simulation of Simple and Complex Survival Data

survSNP — 0.26

Power Calculations for SNP Studies with Censored Outcomes

SurvSparse — 0.1

Survival Analysis with Sparse Longitudinal Covariates

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