1 2 3 4 5 |

`df` |
Dataframe [REQUIRED]. |

`fit` |
GLM model object [fit or family/covs/out are REQUIRED]. |

`family` |
Model family name in quotes ("guassian", "binomial", "poisson") [fit or family/covs/out are REQUIRED]. |

`covs` |
Vector of covariates to include in model [fit or family/covs/out are REQUIRED]. |

`out` |
Outcome for regression model [fit or family/covs/out are REQUIRED]. |

`regtype` |
Should the covariates be run separately ("uni") or together in a multiple regression model ("multi") [REQUIRED if no fit]. |

`exp` |
Option to exponentiate coefficients and CI's. Default is NA (estimates are only exponentiated for binomial and poisson family models by default). |

`estname` |
Option to override default estimate column name. Default is NA. |

`intercept` |
If TRUE the intercept will be included in the table. Default is FALSE. |

`overallp` |
If TRUE, a likelihood ratio test pvalue (using drop1 Chisq tests) will be calculated for each variable. Default is TRUE. |

`est.dec` |
Number of decimal places for estimates. Default is 2. |

`ci.dec` |
Number of decimal places for 95 \itempval.decNumber of decimal places for pvalues. Default is 3. \itemcolorHex color to use for htmlTable output. Default is "#EEEEEE" (grey). \itemprintRMDWhether to print resulting table to Rmd via xtable. Default is FALSE \itemprintR2Whether to include R squared value in label (rsq package, type 'v'). \itemhtmlTableWhether to use htmlTable package to display table (instead of xtable). Default is TRUE |

This function creates a nice looking regression table for a glm model. Input either a glm object or outcome variable, vector of covariates, model family, and type of analysis (bivariate or multiple regression). The function returns a dataframe with regression coefficients. By default a table is also printed via htmlTable - handy for R markdown html reports. coefficients glm linear logistic poisson regression table

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