JointAI: summary.JointAI – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

summary.JointAI

Summarize the results from an object of class JointAI

Description

Obtain and print the summary, (fixed effects) coefficients (coef) and credible interval (confint) for an object of class 'JointAI'.

Usage

## S3 method for class 'JointAI'
summary(object, start = NULL, end = NULL, thin = NULL,
  quantiles = c(0.025, 0.975), subset = NULL, exclude_chains = NULL,
  outcome = NULL, missinfo = FALSE, warn = TRUE, mess = TRUE, ...)

## S3 method for class 'summary.JointAI'
print(x, digits = max(3, .Options$digits - 4), ...)

## S3 method for class 'JointAI'
coef(object, start = NULL, end = NULL, thin = NULL,
  subset = NULL, exclude_chains = NULL, warn = TRUE, mess = TRUE, ...)

## S3 method for class 'JointAI'
confint(object, parm = NULL, level = 0.95,
  quantiles = NULL, start = NULL, end = NULL, thin = NULL,
  subset = NULL, exclude_chains = NULL, warn = TRUE, mess = TRUE, ...)

## S3 method for class 'JointAI'
print(x, digits = max(4, getOption("digits") - 4), ...)

Arguments

`object`	object inheriting from class 'JointAI'
`start`	the first iteration of interest (see `window.mcmc`)
`end`	the last iteration of interest (see `window.mcmc`)
`thin`	thinning interval (integer; see `window.mcmc`). For example, `thin = 1` (default) will keep the MCMC samples from all iterations; `thin = 5` would only keep every 5th iteration.
`quantiles`	posterior quantiles
`subset`	subset of parameters/variables/nodes (columns in the MCMC sample). Follows the same principle as the argument `monitor_params` in `*_imp`.
`exclude_chains`	optional vector of the index numbers of chains that should be excluded
`outcome`	optional; vector identifying for which outcomes the summary should be given, either by specifying their indices, or their names (LHS of the respective model formulas as character string).
`missinfo`	logical; should information on the number and proportion of missing values be included in the summary?
`warn`	logical; should warnings be given? Default is `TRUE`.
`mess`	logical; should messages be given? Default is `TRUE`.
`...`	currently not used
`x`	an object of class `summary.JointAI` or `JointAI`
`digits`	the minimum number of significant digits to be printed in values.
`parm`	same as `subset` (for consistency with `confint` method for other types of objects)
`level`	confidence level (default is 0.95)

Examples

mod1 <- lm_imp(y ~ C1 + C2 + M2, data = wideDF, n.iter = 100)

summary(mod1, missinfo = TRUE)
coef(mod1)
confint(mod1)

JointAI

Joint Analysis and Imputation of Incomplete Data

v1.0.2

GPL (>= 2)

Authors

Nicole S. Erler [aut, cre] (<https://orcid.org/0000-0002-9370-6832>)

Initial release