lm_model_summary: Model Summary for Linear Regression

In jasonmoy28/psycModel: Integrated Toolkit for Psychological Analysis and Modeling in R

Model Summary for Linear Regression

Description

An integrated function for fitting a linear regression model. This function will no longer be updated. Please use the these functions separately instead: model_summary, interaction_plot,and simple_slope.

Usage

lm_model_summary(
  data,
  response_variable = NULL,
  predictor_variable = NULL,
  two_way_interaction_factor = NULL,
  three_way_interaction_factor = NULL,
  family = NULL,
  cateogrical_var = NULL,
  graph_label_name = NULL,
  model_summary = TRUE,
  interaction_plot = TRUE,
  y_lim = NULL,
  plot_color = FALSE,
  digits = 3,
  simple_slope = FALSE,
  assumption_plot = FALSE,
  quite = FALSE,
  streamline = FALSE,
  return_result = FALSE
)

Arguments

data	data.frame
response_variable	DV (i.e., outcome variable / response variable). Length of 1. Support dplyr::select() syntax.
predictor_variable	IV. Support dplyr::select() syntax.
two_way_interaction_factor	two-way interaction factors. You need to pass 2+ factor. Support dplyr::select() syntax.
three_way_interaction_factor	three-way interaction factor. You need to pass exactly 3 factors. Specifying three-way interaction factors automatically included all two-way interactions, so please do not specify the two_way_interaction_factor argument. Support dplyr::select() syntax.
family	a GLM family. It will passed to the family argument in glm. See ?glm for possible options.
cateogrical_var	list. Specify the upper bound and lower bound directly instead of using ± 1 SD from the mean. Passed in the form of list(var_name1 = c(upper_bound1, lower_bound1),var_name2 = c(upper_bound2, lower_bound2))
graph_label_name	optional vector or function. vector of length 2 for two-way interaction graph. vector of length 3 for three-way interaction graph. Vector should be passed in the form of c(response_var, predict_var1, predict_var2, ...). Function should be passed as a switch function (see ?two_way_interaction_plot for an example)
model_summary	print model summary. Required to be TRUE if you want assumption_plot.
interaction_plot	generate the interaction plot. Default is TRUE
y_lim	the plot's upper and lower limit for the y-axis. Length of 2. Example: c(lower_limit, upper_limit)
plot_color	If it is set to TRUE (default is FALSE), the interaction plot will plot with color.
digits	number of digits to round to
simple_slope	Slope estimate at +1/-1 SD and the mean of the moderator. Uses interactions::sim_slope() in the background.
assumption_plot	Generate an panel of plots that check major assumptions. It is usually recommended to inspect model assumption violation visually. In the background, it calls performance::check_model()
quite	suppress printing output
streamline	print streamlined output
return_result	If it is set to TRUE (default is FALSE), it will return the model, model_summary, and plot (if the interaction term is included)

Value

a list of all requested items in the order of model, model_summary, interaction_plot, simple_slope

Examples

fit <- lm_model_summary(
  data = iris,
  response_variable = "Sepal.Length",
  predictor_variable = dplyr::everything(),
  two_way_interaction_factor = c(Sepal.Width, Species),
  interaction_plot = FALSE, # you can also request the interaction plot
  simple_slope = FALSE, # you can also request simple slope estimate 
  assumption_plot = FALSE, # you can also request assumption plot
  streamline = FALSE #you can change this to get the least amount of info
)

jasonmoy28/psycModel documentation built on Sept. 6, 2024, 11:45 a.m.