tabgee: Create Summary Table for Fitted Generalized Estimating...

In tab: Create Summary Tables for Statistical Reports

Description

Creates a table summarizing a GEE fit using the gee function.

Usage

tabgee(
  fit,
  data = NULL,
  columns = NULL,
  robust = TRUE,
  var.labels = NULL,
  factor.compression = 1,
  sep.char = ", ",
  decimals = 2,
  formatp.list = NULL
)

Arguments

fit	Fitted gee object.
data	Data frame that served as 'data' in function call to gee. Only needs to be specified if one or more of the predictors is a factor and factor.compression is 1, 2, 3, or 4.
columns	Character vector specifying what columns to include. Choices for each element are "beta", "se", "betaci" for 95% CI for Beta, "beta.se" for Beta (SE), "beta.ci" for Beta (95% CI), "or", "orci" for 95% CI for OR, "or.ci" for OR (95% CI), "hr", "hrci" for 95% CI for HR, "hr.ci" for HR (95% CI), "z" for z statistic, and "p". If OR's or HR's are requested, the function will trust that exponentiated betas correspond to these quantities.
robust	Logical value for whether to use robust standard errors.
var.labels	Named list specifying labels to use for certain predictors. For example, if fit includes a predictor named "race" that you want to label "Race/ethnicity" and a predictor named "age_yrs" that you want to label "Age (years)", use var.labels = list(race = "Race/ethnicity", age_yrs = "Age (years)".
factor.compression	Integer value from 1 to 5 controlling how much compression is applied to factor predictors (higher value = more compression). If 1, rows are Variable, Level 1 (ref), Level 2, ...; if 2, rows are Variable (ref = Level 1), Level 2, ...; if 3, rows are Level 1 (ref), Level 2, ...; if 4, rows are Level 2 (ref = Level 1), ...; if 5, rows are Level 2, ...
sep.char	Character string with separator to place between lower and upper bound of confidence intervals. Typically "-" or ", ".
decimals	Numeric value specifying number of decimal places for numbers other than p-values.
formatp.list	List of arguments to pass to formatp.

Value

kable.

Examples

# Load in sample dataset and convert to long format
tabdata2 <- reshape(data = tabdata,
                    varying = c("bp.1", "bp.2", "bp.3", "highbp.1",
                                "highbp.2", "highbp.3"),
                    timevar = "bp.visit", direction = "long")
tabdata2 <- tabdata2[order(tabdata2$id), ]

# Blood pressure at 1, 2, and 3 months vs. age, sex, race, and treatment
library("gee")
fit <- gee(bp ~ Age + Sex + Race + Group, id = id, data = tabdata2,
           corstr = "unstructured")
tabgee(fit)

# Can also use piping
fit %>% tabgee(data = tabdata2)

# Same as previous, but with custom labels for Age and Race and factors
# displayed in slightly more compressed format
fit %>%
  tabgee(
    data = tabdata2,
    var.labels = list(Age = "Age (years)", Race = "Race/ethnicity"),
    factor.compression = 2
  )

# GEE with some higher-order terms
# higher-order terms
fit <- gee(
  highbp ~ poly(Age, 2, raw = TRUE) + Sex + Race + Group + Race*Group,
  id = id,
  data = tabdata2,
  family = "binomial",
  corstr = "unstructured"
)
fit %>% tabgee(data = tabdata2)

tab documentation built on Aug. 2, 2021, 9:06 a.m.