Description Usage Arguments Value Examples

Analysis Function for Replications.

1 2 3 4 5 6 | ```
analyses(DV, treat, data, model = "lm", covs = NULL,
heterogenous = NULL, subset = NULL, FE = NULL, cluster = NULL,
IV_list = NULL, robust = is.null(cluster), ri = NULL, IPW = NULL,
treat_only = FALSE, margin_at = NULL, status = NULL,
stars = FALSE, round_digits = 3, return_df = FALSE, seed = 12345,
cores = 4)
``` |

`DV` |
Dependent variable specified as character. |

`treat` |
Treatment vector of variables specified as character vector. |

`data` |
Data frame which contains all the relevant variables. |

`model` |
Character string specifying the model to estimate. Currently only "lm" (OLS), "logit" (Binary Logit), "probit" (Binary Probit), "ologit" (Ordered Logit) and "oprobit" (Ordered Probit) models are supported. Default is "lm". |

`covs` |
Character vector of covariates specified as character vector. |

`heterogenous` |
Character vector of covariates to interact with treatments specified as character vector. |

`subset` |
character string specifing logical expression for subsetting. |

`FE` |
Character vector of fixed effects covariates specified as character vector. |

`cluster` |
Covariate for clustered robust standard errors as defined by |

`IV_list` |
Character string. Should be a character string which presents valid IV formula as specified in |

`robust` |
Logical. Whether to report heteroskedastic robust standard errors. Implemented only for linear models for now. |

`ri` |
Numeric. If not NULL, gives number of iterations to use for calculation of non-parametric Studentized randomization inference p-values from two-sided test. Only implemented for model = "lm" at the moment. |

`IPW` |
Inverse probability weights specified as character vector. |

`treat_only` |
Logical vector of length 1, specifying whether only |

`margin_at` |
Character string which should be in the format of |

`status` |
Logical vector of length 3, specifying whether the model was pre-(R)egistered, run in (S)cript and reported in (P)aper respectively. |

`stars` |
Logical. If |

`round_digits` |
Integer. How many decimal points to round to in the output. |

`return_df` |
If |

`seed` |
Numeric. RNG seed. |

`cores` |
Numeric from 1 to 4. Number of cores used for parallel processing. |

List of three objects. `estimates`

is estimates from the model and corresponding standard errors. `stat`

is vector of adjusted R squared and number of observations. `model_spec`

is logical vector of characteristics of the model.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |

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