# pseval v1.3.1

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## Methods for Evaluating Principal Surrogates of Treatment Response

Contains the core methods for the evaluation of principal
surrogates in a single clinical trial. Provides a flexible interface for
defining models for the risk given treatment and the surrogate, the models
for integration over the missing counterfactual surrogate responses, and the
estimation methods. Estimated maximum likelihood and pseudo-score can be used
for estimation, and the bootstrap for inference. A variety of post-estimation
summary methods are provided, including print, summary, plot, and testing.

## Readme

# pseval: Methods for Evaluating Principal Surrogates of Treatment Response

## Installation

`pseval`

is an R package aimed at implementing existing methods for surrogate evaluation using a flexible and common interface. Development will take place on the Github page, and the current version of the package can be installed as shown below. First you must install the `devtools`

package, if you haven't already `install.packages("devtools")`

.

```
devtools::install_github("sachsmc/pseval")
```

Check out the vignette for methodological details and information on how to use the package.

Check out the cheat sheet for a quick reference.

## References

- Sachs and Gabriel, 2016.
*An Introduction to Principal Surrogate Evaluation with the pseval Package* - Gabriel and Gilbert, 2014.
*Evaluating principal surrogate endpoints with time-to-event data accounting for time-varying treatment efficacy* - Huang and Gilbert, 2011.
*Comparing Biomarkers as Principal Surrogate Endpoints* - Gilbert and Hudgens, 2008.
*Evaluating Candidate Principal Surrogate Endpoints* - Huang, Gilbert, and Wolfson, 2013.
*Design and Estimation for Evaluating Principal Surrogate Markers in Vaccine Trials*

## Functions in pseval

Name | Description | |

calc_risk | Calculate the risk and functions of the risk | |

empirical_VE | Compute the empirical Treatment Efficacy | |

add_estimate | Estimate parameters | |

add_integration | Integration models | |

empirical_TE | Compute the empirical Treatment Efficacy | |

risk_binary | Risk model for binary outcome | |

TE | Treatment efficacy contrast functions | |

+.ps | Modify a psdesign object by adding on new components. | |

risk_continuous | Risk model for continuous outcome | |

expand_augdata | Expand augmented data using the integration function | |

print.psdesign | Concisely print information about a psdesign object | |

integrate_nonparametric | Nonparametric integration model for the missing S(1) | |

add_bootstrap | Bootstrap resampling parameters | |

integrate_parametric | Parametric integration model for the missing S(1) | |

add_riskmodel | Add risk model to a psdesign object | |

risk_exponential | Exponential risk model for time to event outcome | |

risk_weibull | Weibull risk model for time to event outcome | |

risk_poisson | Poisson risk model for count outcomes | |

integrate_semiparametric | Semiparametric integration model using the location-scale model | |

riskcalc | Calculate risks with handlers for survival data | |

plot.psdesign | Plot summary statistics for a psdesign object | |

verify_trt | Check that a variable is suitable for using as binary treatment indicator | |

sp_locscale | Fit the semi-parametric location-scale model | |

stg | Compute the standardized total gain | |

calc_STG | Calculate the Standardized total gain | |

generate_example_data | Generate sample data used for testing | |

integrate_bivnorm | Bivariate normal integration models for the missing S(1) | |

summarize_bs | Summarize bootstrap samples | |

ps_bootstrap | Estimate parameters from a specified model using bootstrap resampling and estimated maximum likelihood | |

ps_estimate | Estimate parameters from a specified model using estimated maximum likelihood | |

psdesign | Specify a design for a principal surrogate evaluation | |

summary.psdesign | Summary method for psdesign objects | |

wem_test | Test for wide effect modification | |

pseudo_score | Estimate parameters from a specified model using pseudo-score | |

risk.logit | Logit link function | |

risk.probit | Probit link function | |

No Results! |

## Vignettes of pseval

Name | ||

introduction.Rmd | ||

psreferences.bib | ||

No Results! |

## Last month downloads

## Details

Type | Package |

Date | 2019-01-10 |

License | MIT + file LICENSE |

LazyData | TRUE |

VignetteBuilder | knitr |

RoxygenNote | 6.1.1 |

NeedsCompilation | no |

Packaged | 2019-01-28 07:18:52 UTC; micsac |

Repository | CRAN |

Date/Publication | 2019-01-28 07:40:03 UTC |

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