lm_model_table: Linear Regression Model Table Generate tables with multiple...

In psycModel: Integrated Toolkit for Psychological Analysis and Modeling in R

Linear Regression Model Table Generate tables with multiple response and predictor variable (only lm models are supported)

Description

Linear Regression Model Table Generate tables with multiple response and predictor variable (only lm models are supported)

Usage

lm_model_table(
  data,
  response_variable,
  predictor_variable,
  control_variable = NULL,
  marginal_alpha = 0.1,
  return_result = FALSE,
  verbose = TRUE,
  show_p = FALSE
)

Arguments

data	data.frame
response_variable	response variable. Support dplyr::select() syntax.
predictor_variable	predictor variable. Support dplyr::select() syntax. It will automatically remove the response variable from predictor variable, so you can use contains() or start_with() safely.
control_variable	control variables. Support dplyr::select() syntax.
marginal_alpha	the set marginal_alpha level for marginally significant (denoted by .). Set to 0.05 if do not want marginally significant denotation.
return_result	It set to TRUE, it return the model estimates data frame.
verbose	default is TRUE. Set to FALSE to suppress outputs
show_p	show the p-value in parenthesis

Value

data.frame

Examples

lm_model_table(data = iris, 
            response_variable = c(Sepal.Length,Sepal.Width),
            predictor_variable = Petal.Width)

psycModel documentation built on Nov. 2, 2023, 6:02 p.m.