findMissingPattern {bipd} | R Documentation |

Find missing data pattern in a given data i.e. whether variables are systematically missing or sporadically missing. Also calculates missing count and percentage for exploratory purposes.

```
findMissingPattern(
dataset = NULL,
covariates = NULL,
typeofvar = NULL,
studyname = NULL,
treatmentname = NULL,
outcomename = NULL
)
```

`dataset` |
data which contains variables of interests |

`covariates` |
vector of variable names that the user is interested in finding a missing data pattern |

`typeofvar` |
type of covariate variables; should be a vector of these values: "continuous", "binary", or "count". Order should follow that of covariates parameter. |

`studyname` |
study name in the data specified |

`treatmentname` |
treatment name in the data specified |

`outcomename` |
outcome name in the data specified |

`missingcount` |
missing number of patients for each study and covariate |

`missingpercent` |
missing percentage of patients for each study and covariate |

`sys_missing` |
a vector indicating whether each covariate is systematically missing |

`spor_missing` |
a vector indicating whether each covariate is sporadically missing |

`sys_covariates` |
a vector of systematically missing covariates |

`spor_covariates` |
a vector of sporadically missing covariates |

`without_sys_covariates` |
a vector of covariates that are not systematically missing |

`covariates` |
vector of variable names that the user is interested in finding a missing data pattern |

`studyname` |
study name in the data specified |

`treatmentname` |
treatment name in the data specified |

`outcomename` |
outcome name in the data specified |

```
simulated_dataset <- generate_sysmiss_ipdma_example(Nstudies = 10, Ncov = 5, sys_missing_prob = 0.3,
magnitude = 0.2, heterogeneity = 0.1)
missP <- findMissingPattern(simulated_dataset, covariates = c("x1", "x2", "x3", "x4", "x5"),
typeofvar = c("continuous", "binary", "binary", "continuous", "continuous"), studyname = "study",
treatmentname = "treat", outcomename = "y")
missP
```

[Package *bipd* version 0.3 Index]