continuous.test | R Documentation |

Summarization of the continuous information.

continuous.test (name, x, y, digits = 3, scientific = FALSE, range = c("IQR","95%CI"), logchange = TRUE, pos=1, method=c("non-parametric","parametric"), ...)

`name` |
the name of the feature. |

`x` |
the information to summarize. |

`y` |
the classification of the cohort. |

`digits` |
how many significant digits are to be used. |

`scientific` |
either a logical specifying whether result should be encoded in scientific format. |

`range` |
the range to be visualized. |

`logchange` |
either a logical specifying whether log2 of fold change should be visualized. |

`pos` |
a value indicating the position of range to be visualized. 1 for column, 2 for row. |

`method` |
a character string indicating which test method is to be computed. "non-parametric" (default), or "parametric". |

`...` |
further arguments to be passed to or from methods. |

The function returns a list containg a table with the summarized information and the relative p-value. For non-parametric method, if the number of group is equal to two, the p-value is computed using the Wilcoxon rank-sum test, Kruskal-Wallis test otherwise. For parametric method, if the number of group is equal to two, the p-value is computed using the Student's t-Test, ANOVA one-way otherwise.

Stefano Cacciatore

Cacciatore S, Luchinat C, Tenori L

Knowledge discovery by accuracy maximization.

*Proc Natl Acad Sci U S A* 2014;111(14):5117-22. doi: 10.1073/pnas.1220873111. Link

Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA

KODAMA: an updated R package for knowledge discovery and data mining.

*Bioinformatics* 2017;33(4):621-623. doi: 10.1093/bioinformatics/btw705. Link

`correlation.test`

, `categorical.test`

, `txtsummary`

data(clinical) hosp=clinical[,"Hospital"] gender=clinical[,"Gender"] GS=clinical[,"Gleason score"] BMI=clinical[,"BMI"] age=clinical[,"Age"] A=categorical.test("Gender",gender,hosp)$text B=categorical.test("Gleason score",GS,hosp)$text C=continuous.test("BMI",BMI,hosp,digits=2,pos=2,logchange = FALSE)$text D=continuous.test("Age",age,hosp,digits=1,pos=2,logchange = FALSE)$text rbind(A,B,C,D)

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