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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