# factorial2x2 v0.1.0

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## Design and Analysis of 2x2 Factorial Trial

Used for the design and analysis of a 2x2 factorial trial for
a time-to-event endpoint. Performs power calculations and significance
testing. Important reference papers include
Slud EV. (1994) <https://www.ncbi.nlm.nih.gov/pubmed/8086609>
Lin DY, Gong J, Gallo P, Bunn PH, Couper D. (2016) <DOI:10.1111/biom.12507>
Leifer ES, Troendle JF, Kolecki A, Follmann DA. (2019)
<https://github.com/EricSLeifer/factorial2x2/blob/master/Leifer%20et%20al%20Factorial.pdf>.

## Readme

# factorial2x2

The goals of the `factorial2x2`

package are twofold: First, to provide
power calculations for a two-by-two factorial design in which the
effects of the two factors may be sub-additive. Power is provided for
the overall effect test for as well as the multiple testing procedures
described in Leifer, Troendle, Kolecki, and Follmann (2019). Second, to
analyze two-by-two factorial trial data which may include baseline
adjustment covariates. Further details are described in the factorial2x2
vignette.

## Installation

You can install the released version of factorial2x2 from CRAN with:

```
install.packages("factorial2x2")
```

## Example of a power calculation

We reproduce the power calculations for scenario 5 from Table 2 in
Leifer, Troendle, et al. using the `fac2x2design`

function.

```
n <- 4600 # total sample size
rateC <- 0.0445 # one year event rate in the control group
hrA <- 0.80 # simple A effect hazard ratio
hrB <- 0.80 # simple B effect hazard ratio
hrAB <- 0.72 # simple AB effect hazard ratio
mincens <- 4.0 # minimum censoring time in years
maxcens <- 8.4 # maximum censoring time in years
fac2x2design(n, rateC, hrA, hrB, hrAB, mincens, maxcens, dig = 2, alpha = 0.05)
$powerA
[1] 0.7182932 # power to detect the overall A effect at the two-sided 0.05 level
$power23.13
[1] 0.9290271 # power to detect the overall A or simple AB effects using the
# 2/3-1/3 procedure
$power13.13.13
[1] 0.9302084 # power to detect the overall A, simple A, or simple AB effects using
# the 1/3-1/3-1/3 procedure
$power12.12
[1] 0.9411688 # power to detect the simple A or simple AB effects using the
# 1/2-1/2 procedure
$events # expected number of events
[1] 954.8738
$evtprob # event probabilities for the C, A, B, and AB groups, respectively
probC probA probB probAB
0.2446365 0.2012540 0.2012540 0.1831806
```

## References

Leifer, E.S., Troendle, J.F., Kolecki, A., Follmann, D. Joint testing of overall and simple effect for the two-by-two factorial design. 2019. Submitted.

Lin, D-Y., Gong, J., Gallo, P., et al. Simultaneous inference on
treatment effects in survival studies with factorial designs.
*Biometrics*. 2016; 72: 1078-1085.

Slud, E.V. Analysis of factorial survival experiments. *Biometrics*.
1994; 50: 25-38.

## Functions in factorial2x2

Name | Description | |

cor2x2 | Hazard ratios and correlations for the 2x2 statistics | |

fac2x2design | Power for the 2/3-1/3, 1/3-1/3-1/3, 1/2-1/2 procedures | |

power12_12 | Power of the 1/2-1/2 procedure | |

power23_13 | Power of the 2/3-1/3 procedure | |

power13_13_13 | Power of the 1/3-1/3-1/3 procedure | |

lgrkPower | Unstratified (ordinary) logrank power | |

fac2x2analyze | Significance testing for the 2/3-1/3, 1/3-1/3-1/3, 1/2-1/2 procedures | |

crit2x2 | Critical values for the 2/3-1/3, 1/3-1/3-1/3, and 1/2-1/2 procedures | |

eventProb | Calculate event probabilities | |

roundDown | Round down a negative number | |

strLgrkPower | Stratified (overall) logrank power | |

simdata | Simulated 2x2 factorial trial data | |

simdat | Simulated 2x2 factorial trial data | |

No Results! |

## Vignettes of factorial2x2

Name | ||

fac2x2vignette.Rmd | ||

No Results! |

## Last month downloads

## Details

Type | Package |

License | GPL-2 |

Encoding | UTF-8 |

LazyData | true |

VignetteBuilder | knitr |

RoxygenNote | 6.1.1 |

NeedsCompilation | no |

Packaged | 2019-09-05 16:35:23 UTC; leifere |

Repository | CRAN |

Date/Publication | 2019-09-07 09:40:02 UTC |

suggests | knitr , rmarkdown |

depends | mvtnorm , R (>= 3.6.0) , stats , survival |

Contributors | Eric Leifer, James Troendle |

#### Include our badge in your README

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