gam_plot {BioPred} | R Documentation |

## GAM Plot

### Description

Generates a generalized additive model (GAM) plot for exploring the relationship between a response variable and a biomarker.

### Usage

```
gam_plot(
yvar,
censorvar = NULL,
xvar,
xvars.adj = NULL,
sxvars.adj = NULL,
type,
data,
k,
pred.type = "iterms",
link.scale = TRUE,
title = "Trend Plot",
ybreaks = NULL,
xbreaks = NULL,
rugcol.var = NULL,
add.points = FALSE,
prt.sum = TRUE,
prt.chk = FALSE,
outlier.rm = FALSE,
newdat = NULL
)
```

### Arguments

`yvar` |
Response variable name. |

`censorvar` |
Censoring variable name for survival analysis (0-censored, 1-event). |

`xvar` |
Biomarker name. |

`xvars.adj` |
Potential confounding variables to adjust for using linear terms. |

`sxvars.adj` |
Potential confounding variables to adjust for using curve terms. |

`type` |
"c" for continuous, "s" for survival, and "b" for binary response. |

`data` |
The dataset containing the variables. |

`k` |
Upper limit on the degrees of freedom associated with an s smooth. |

`pred.type` |
"iterms" for trend of xvar, "response" for Y at the original scale. |

`link.scale` |
Whether to show the plot in the scale of the link function. |

`title` |
Title of the plot. |

`ybreaks` |
Breaks on the y-axis. |

`xbreaks` |
Breaks on the x-axis. |

`rugcol.var` |
Variable name defining the color of the rug and points. |

`add.points` |
Whether to add data points to the plot. |

`prt.sum` |
Whether to print summary or not. |

`prt.chk` |
Whether to print model diagnosis. |

`outlier.rm` |
Whether to remove outliers based on 1.5IQR. |

`newdat` |
User-supplied customized data for prediction and plotting. |

### Value

A list containing p-table, s-table, GAM summary, GAM check, and the plot.

*BioPred*version 1.0.1 Index]