uvsum {reportRmd}

Get univariate summary dataframe

Description

Returns a dataframe corresponding to a univariate regression table

Usage

uvsum(
  response,
  covs,
  data,
  digits = getOption("reportRmd.digits", 2),
  id = NULL,
  corstr = NULL,
  family = NULL,
  type = NULL,
  offset = NULL,
  gee = FALSE,
  strata = 1,
  markup = TRUE,
  sanitize = TRUE,
  nicenames = TRUE,
  showN = TRUE,
  showEvent = TRUE,
  CIwidth = 0.95,
  reflevel = NULL,
  returnModels = FALSE,
  forceWald
)

Arguments

response

string vector with name of response

covs

character vector with the names of columns to fit univariate models to

data

dataframe containing data

digits

number of digits to round to

id

character vector which identifies clusters. Used for GEE and coxph models.

corstr

character string specifying the correlation structure. Only used for geeglm. The following are permitted: '"independence"', '"exchangeable"', '"ar1"', '"unstructured"' and '"userdefined"'

family

specify details of the model used. This argument does not need to be specified and should be used with caution. By default, gaussian errors are used for linear models, the binomial family with logit link is used for logistic regression and poisson with log link is used for poisson regression. This can be specified with the type argument, or will be inferred from the data type. See family. Ignored for ordinal and survival regression and if the type argument is not explicitly specified.

type

string indicating he type of univariate model to fit. The function will try and guess what type you want based on your response. If you want to override this you can manually specify the type. Options include "linear", "logistic", "poisson", coxph", "crr", "boxcox", "ordinal" and "negbin"

offset

string specifying the offset term to be used for Poisson or negative binomial regression. Example: offset="log(follow_up)"

gee

boolean indicating if gee models should be fit to account for correlated observations. If TRUE then the id argument must specify the column in the data which indicates the correlated clusters.

strata

character vector of covariates to stratify by. Only used for coxph and crr

markup

boolean indicating if you want latex markup

sanitize

boolean indicating if you want to sanitize all strings to not break LaTeX

nicenames

boolean indicating if you want to replace . and _ in strings with a space

showN

boolean indicating if you want to show sample sizes

showEvent

boolean indicating if you want to show number of events. Only available for logistic.

CIwidth

width of confidence interval, default is 0.95

reflevel

manual specification of the reference level. Only used for ordinal. This may allow you to debug if the function throws an error.

returnModels

boolean indicating if a list of fitted models should be returned.

forceWald

boolean indicating if Wald confidence intervals should be used instead of profile likelihood. This is not recommended, but can speed up computations. To use throughout a document use options(reportRmd.forceWald=TRUE)

Details

Univariate summaries for a number of covariates, the type of model can be specified. If unspecified the function will guess the appropriate model based on the response variable.

Confidence intervals are extracted using confint where possible. Otherwise Student t distribution is used for linear models and the Normal distribution is used for proportions.

returnModels can be used to return a list of the univariate models, which will be the same length as covs. The data used to run each model will include all cases with observations on the response and covariate. For gee models the data are re-ordered so that the ids appear sequentially and proper estimates are given.

See Also

lm,glm,crr,coxph, lme,geeglm,polr,glm.nb