modelsum: Fit models over each of a set of independent variables with a...
In arsenal: An Arsenal of 'R' Functions for Large-Scale Statistical Summaries

Description Usage Arguments Value Author(s) See Also Examples

Fit and summarize models for each independent (x) variable with a response variable (y), with options to adjust by variables for each model.

modelsum(
  formula,
  family = "gaussian",
  data,
  adjust = NULL,
  na.action = NULL,
  subset = NULL,
  weights = NULL,
  id,
  strata,
  control = NULL,
  ...
)

`formula`	an object of class `formula`; a symbolic description of the variables to be modeled. See "Details" for more information.
`family`	similar mechanism to `glm`, where the model to be fit is driven by the family. Options include: binomial, gaussian, survival, poisson, negbin, clog, and ordinal. These can be passed as a string, as a function, or as a list resulting from a call to one of the functions. See `modelsum.family` for details on survival, ordinal, negbin, and clog families.
`data`	an optional data.frame, list or environment (or object coercible by `as.data.frame` to a data frame) containing the variables in the model. If not found in `data`, the variables are taken from `environment(formula)`, typically the environment from which `modelsum` is called.
`adjust`	an object of class `formula` or a list of formulas, listing variables to adjust by in all models. Specify as a one-sided formula, like: `~Age+ Sex`. If a list, the names are used for the summary function. Unadjusted models can be specified as `~ 1` or as a list: `list(Unadjusted = NULL)`.
`na.action`	a function which indicates what should happen when the data contain `NA`s. The default (`NULL`) is to use the defaults of `lm`, `glm`, or `coxph`, depending on the `family` specifications.
`subset`	an optional vector specifying a subset of observations (rows of `data`) to be used in the results. If `strata` is missing, this works as vector of logicals or an index; otherwise, it should be a logical vector.
`weights`	an optional vector specifying the weights to apply to each data observation (rows of `data`)
`id`	A vector to identify clusters. Only used for `relrisk` at this time.
`strata`	a vector of strata to separate model summaries by an additional group. Note that for families like "clog", the "usual" strata term to indicate subject groupings should be given in the `adjust` argument.
`control`	control parameters to handle optional settings within `modelsum`. Arguments for `modelsum.control` can be passed to `modelsum` via the `...` argument, but if a control object and `...` arguments are both supplied, the latter are used. See `modelsum.control` for other details.
`...`	additional arguments to be passed to internal `modelsum` functions.

An object with class c("modelsum", "arsenal_table")

Jason Sinnwell, Patrick Votruba, Beth Atkinson, Gregory Dougherty, and Ethan Heinzen, adapted from SAS Macro of the same name

arsenal_table, modelsum.control, summary.modelsum, modelsum.internal, formulize

data(mockstudy)

tab1 <- modelsum(bmi ~ sex + age, data = mockstudy)
summary(tab1, text = TRUE)

tab2 <- modelsum(alk.phos ~ arm + ps + hgb, adjust = ~ age + sex,
                 family = "gaussian", data = mockstudy)
summary(tab2, text = TRUE)

summary(tab2, show.intercept = FALSE, text = TRUE)

tab2.df <- as.data.frame(tab2)

tab2.df[1:5,]