lm_model_table {psycModel}

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)