View source: R/print.CatTable.R

print.CatTable | R Documentation |

`CatTable`

class objects`print`

method for the `CatTable`

class objects created by `CreateCatTable`

function.

## S3 method for class 'CatTable' print( x, digits = 1, pDigits = 3, quote = FALSE, missing = FALSE, explain = TRUE, printToggle = TRUE, noSpaces = FALSE, format = c("fp", "f", "p", "pf")[1], showAllLevels = FALSE, cramVars = NULL, dropEqual = FALSE, test = TRUE, exact = NULL, smd = FALSE, CrossTable = FALSE, formatOptions = list(scientific = FALSE), ... )

`x` |
Object returned by |

`digits` |
Number of digits to print in the table. |

`pDigits` |
Number of digits to print for p-values (also used for standardized mean differences). |

`quote` |
Whether to show everything in quotes. The default is FALSE. If TRUE, everything including the row and column names are quoted so that you can copy it to Excel easily. |

`missing` |
Whether to show missing data information. |

`explain` |
Whether to add explanation to the variable names, i.e., (%) is added to the variable names when percentage is shown. |

`printToggle` |
Whether to print the output. If FALSE, no output is created, and a matrix is invisibly returned. |

`noSpaces` |
Whether to remove spaces added for alignment. Use this option if you prefer to align numbers yourself in other software. |

`format` |
The default is "fp" frequency (percentage). You can also choose from "f" frequency only, "p" percentage only, and "pf" percentage (frequency). |

`showAllLevels` |
Whether to show all levels. FALSE by default, i.e., for 2-level categorical variables, only the higher level is shown to avoid redundant information. |

`cramVars` |
A character vector to specify the two-level categorical variables, for which both levels should be shown in one row. |

`dropEqual` |
Whether to drop " = second level name" description indicating which level is shown for two-level categorical variables. |

`test` |
Whether to show p-values. TRUE by default. If FALSE, only the numerical summaries are shown. |

`exact` |
A character vector to specify the variables for which the p-values should be those of exact tests. By default all p-values are from large sample approximation tests (chisq.test). |

`smd` |
Whether to show standardized mean differences. FALSE by default. If there are more than one contrasts, the average of all possible standardized mean differences is shown. For individual contrasts, use |

`CrossTable` |
Whether to show the cross table objects held internally using gmodels::CrossTable function. This will give an output similar to the PROC FREQ in SAS. |

`formatOptions` |
A list of options, which will be passed to |

`...` |
For compatibility with generic. Ignored. |

A matrix object containing what you see is also invisibly returned. This can be assinged a name and exported via `write.csv`

.

Kazuki Yoshida, Alexander Bartel

`CreateTableOne`

, `CreateCatTable`

, `summary.CatTable`

## Load library(tableone) ## Load Mayo Clinic Primary Biliary Cirrhosis Data library(survival) data(pbc) ## Check variables head(pbc) ## Create an overall table for categorical variables catVars <- c("status","ascites","hepato","spiders","edema","stage") catTableOverall <- CreateCatTable(vars = catVars, data = pbc) ## Simply typing the object name will invoke the print.CatTable method, ## which will show the sample size, frequencies and percentages. ## For 2-level variables, only the higher level is shown for simplicity. catTableOverall ## If you need to show both levels for some 2-level factors, use cramVars print(catTableOverall, cramVars = "hepato") ## Use the showAllLevels argument to see all levels for all variables. print(catTableOverall, showAllLevels = TRUE) ## You can choose form frequencies ("f") and/or percentages ("p") or both. ## "fp" frequency (percentage) is the default. Row names change accordingly. print(catTableOverall, format = "f") print(catTableOverall, format = "p") ## To further examine the variables, use the summary.CatTable method, ## which will show more details. summary(catTableOverall) ## The table can be stratified by one or more variables catTableBySexTrt <- CreateCatTable(vars = catVars, strata = c("sex","trt"), data = pbc) ## print now includes p-values which are by default calculated by chisq.test. ## It is formatted at the decimal place specified by the pDigits argument ## (3 by default). It does <0.001 for you. catTableBySexTrt ## The exact argument toggles the p-values to the exact test result from ## fisher.test. It will show which ones are from exact tests. print(catTableBySexTrt, exact = "ascites") ## summary now includes both types of p-values summary(catTableBySexTrt) ## If your work flow includes copying to Excel and Word when writing manuscripts, ## you may benefit from the quote argument. This will quote everything so that ## Excel does not mess up the cells. print(catTableBySexTrt, exact = "ascites", quote = TRUE) ## If you want to center-align values in Word, use noSpaces option. print(catTableBySexTrt, exact = "ascites", quote = TRUE, noSpaces = TRUE)

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