glm_model_explore: Exploratory Linear Regression Model Table

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

Exploratory Linear Regression Model Table

Description

Exploratory analyses for linear regression models with multiple response, predictor, and two-way interaction variables. (lm models). At the moment, multi-categorical variables are not supported as predictors or interactions (but control is fine). Binary variable should be numeric instead of factor

Usage

glm_model_explore(
  data,
  response_variable,
  predictor_variable,
  family,
  two_way_interaction_variable = NULL,
  three_way_interaction_variable = NULL,
  control_variable = NULL,
  marginal_alpha = 0.1,
  verbose = TRUE,
  show_p = TRUE,
  return_result = FALSE,
  print_control = FALSE,
  plot_interaction = FALSE,
  file_dir = NULL,
  device = "jpeg",
  width = 8.5,
  height = 5,
  units = "in",
  y_lim = c(0, 1)
)

Arguments

data	data.frame
response_variable	Response variable. Support dplyr::select() syntax.
predictor_variable	Pred variable. Support dplyr::select() syntax.
family	a GLM family. It will passed to the family argument in glm See ?glm for possible options.
two_way_interaction_variable	Two-way interaction variable. Each two-way interaction variable will interact with each pred variable. Support dplyr::select() syntax.
three_way_interaction_variable	Three-way interaction variable. Each three-way interaction variable will interact with each pred and two-way interaction variables. Support dplyr::select() syntax.
control_variable	Control variables. Support dplyr::select() syntax.
marginal_alpha	Set marginal_alpha level for marginally significant (denoted by .). Set to 0.05 if do not want marginally significant denotation.
verbose	Default is TRUE. Set to FALSE to suppress outputs
show_p	Default is TRUE. When TRUE, show the p-value in parenthesis.
return_result	Default is FALSE. If TRUE, it returns the model estimates as a data frame.
print_control	Default is FALSE. If TRUE, print coefficients of control variables.
plot_interaction	Default is FALSE. If TRUE, interactions will be plotted and saved on your laptop.
file_dir	Path of the directory to save plot to
device	Default is "jpeg". See ggplot2::ggsave() for all options.
width	Default is 8.5 (i.e., letter size width).
height	Default is 5.
units	Default is inches. Options are "in", "cm", "mm" or "px".
y_lim	the plot's upper and lower limit for the y-axis. Length of 2. Example: c(lower_limit, upper_limit)

Value

data.frame

Examples

test = data.frame(y1 = sample(c(0, 1), size = 1000, replace = TRUE),
y2 = sample(c(0, 1), size = 1000, replace = TRUE),
y3 = sample(c(0, 1), size = 1000, replace = TRUE),
x1 = rnorm(1000,100,10),
x2 = rnorm(1000,10,1),
x3 = rnorm(1000,6,2),
m1 = rnorm(1000,3,1),
m2 = rnorm(1000,2,0.5),
m3 = rnorm(1000,9,0.1),
c1 = rnorm(1000,5,0.4),
c2 = rnorm(1000,2,0.2),
c3 = rnorm(1000,7,0.9)
)

glm_model_explore(data = test, 
                 response_variable = c(y1,y2,y3),
                 predictor_variable = c(x1,x2,x3),
                 two_way_interaction_variable = c(m1,m2,m3),
                 family = binomial(link = 'logit'),
                 control_variable = c(c1,c2,c3))

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