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lm
Linear Regression Model Table Generate tables with multiple response and predictor variable (only lm models are supported)
lm_model_table( data, response_variable, predictor_variable, control_variable = NULL, marginal_alpha = 0.1, return_result = FALSE, verbose = TRUE, show_p = FALSE )
data.frame
response variable. Support dplyr::select() syntax.
dplyr::select()
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.
contains()
start_with()
control variables. Support dplyr::select() syntax.
the set marginal_alpha level for marginally significant (denoted by .). Set to 0.05 if do not want marginally significant denotation.
.
It set to TRUE, it return the model estimates data frame.
TRUE
default is TRUE. Set to FALSE to suppress outputs
FALSE
show the p-value in parenthesis
lm_model_table(data = iris, response_variable = c(Sepal.Length,Sepal.Width), predictor_variable = Petal.Width)
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