Description Usage Arguments Details Value See Also Examples

Logistic regression

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`dataset` |
Dataset |

`rvar` |
The response variable in the model |

`evar` |
Explanatory variables in the model |

`lev` |
The level in the response variable defined as _success_ |

`int` |
Interaction term to include in the model |

`wts` |
Weights to use in estimation |

`check` |
Use "standardize" to see standardized coefficient estimates. Use "stepwise-backward" (or "stepwise-forward", or "stepwise-both") to apply step-wise selection of variables in estimation. Add "robust" for robust estimation of standard errors (HC1) |

`ci_type` |
To use the profile-likelihood (rather than Wald) for confidence intervals use "profile". For datasets with more than 5,000 rows the Wald method will be used, unless "profile" is explicitly set |

`data_filter` |
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000") |

See https://radiant-rstats.github.io/docs/model/logistic.html for an example in Radiant

A list with all variables defined in logistic as an object of class logistic

`summary.logistic`

to summarize the results

`plot.logistic`

to plot the results

`predict.logistic`

to generate predictions

`plot.model.predict`

to plot prediction output

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