bruceR: model_summary – R documentation

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model_summary

Tidy report of regression models (into R console, Word, or HTML).

Description

This function is an extension (and combination) of texreg::screenreg(), texreg::htmlreg(), MuMIn::std.coef(), and MuMIn::r.squaredGLMM().

Usage

model_summary(
  model_list,
  std_coef = FALSE,
  digits = nsmall,
  nsmall = 3,
  zero = ifelse(std_coef, FALSE, TRUE),
  modify_se = NULL,
  bold = 0,
  file = NULL,
  ...
)

Arguments

`model_list`	A single model or a list of models. The models should be of the same type.
`std_coef`	Standardized coefficients? Default is `FALSE`. Only applicable to linear models and linear mixed models. Not applicable to generalized linear (mixed) models.
`digits`	Number of decimal places of output. Default is `3`.
`nsmall`	The same as `digits`.
`zero`	Display "0" before "."? Default is `TRUE`.
`modify_se`	Set custom values for standard errors. Useful if you need to replace raw SEs with robust SEs. New SEs should be provided as a list of numeric vectors. See usage in `texreg::screenreg()`.
`bold`	The p-value threshold below which the coefficient shall be formatted in a bold font. For example, `bold = 0.05` will cause all coefficients that are significant at the 95% level to be formatted in bold.
`file`	File name of the Word or HTML document. The extension should be `.doc` or `.html`.
`...`	Other parameters passed to the `texreg::screenreg()` or `texreg::htmlreg()` function.

Value

Invisibly return the plain text of output.

Examples

## Example 1: Linear Model
lm1=lm(Temp ~ Month + Day, data=airquality)
lm2=lm(Temp ~ Month + Day + Wind + Solar.R, data=airquality)
model_summary(lm1)
model_summary(lm2)
model_summary(list(lm1, lm2))
model_summary(list(lm1, lm2), std=TRUE, digits=2)
model_summary(list(lm1, lm2), file="OLS Models.doc")
model_summary(list(lm1, lm2), file="OLS Models.html")
unlink("OLS Models.doc")  # delete file for test
unlink("OLS Models.html")  # delete file for test

## Example 2: Generalized Linear Model
glm1=glm(case ~ age + parity,
         data=infert, family=binomial)
glm2=glm(case ~ age + parity + education + spontaneous + induced,
         data=infert, family=binomial)
model_summary(list(glm1, glm2))  # "std_coef" is not applicable to glm
model_summary(list(glm1, glm2), file="GLM Models.doc")
unlink("GLM Models.doc")  # delete file for test

## Example 3: Linear Mixed Model
library(lmerTest)
hlm1=lmer(Reaction ~ (1 | Subject), data=sleepstudy)
hlm2=lmer(Reaction ~ Days + (1 | Subject), data=sleepstudy)
hlm3=lmer(Reaction ~ Days + (Days | Subject), data=sleepstudy)
model_summary(list(hlm1, hlm2, hlm3))
model_summary(list(hlm1, hlm2, hlm3), std=TRUE)
model_summary(list(hlm1, hlm2, hlm3), file="HLM Models.doc")
unlink("HLM Models.doc")  # delete file for test

## Example 4: Generalized Linear Mixed Model
library(lmerTest)
data.glmm=MASS::bacteria
glmm1=glmer(y ~ trt + week + (1 | ID), data=data.glmm, family=binomial)
glmm2=glmer(y ~ trt + week + hilo + (1 | ID), data=data.glmm, family=binomial)
model_summary(list(glmm1, glmm2))  # "std_coef" is not applicable to glmm
model_summary(list(glmm1, glmm2), file="GLMM Models.doc")
unlink("GLMM Models.doc")  # delete file for test

## Example 5: Multinomial Logistic Model
library(nnet)
d=airquality
d$Month=as.factor(d$Month)  # Factor levels: 5, 6, 7, 8, 9
mn1=multinom(Month ~ Temp, data=d, Hess=TRUE)
mn2=multinom(Month ~ Temp + Wind + Ozone, data=d, Hess=TRUE)
model_summary(mn1)
model_summary(mn2)
model_summary(mn2, file="Multinomial Logistic Model.doc")
unlink("Multinomial Logistic Model.doc")  # delete file for test

bruceR

Broadly Useful Convenient and Efficient R Functions

v0.6.2

GPL-3

Authors

Han-Wu-Shuang Bao [aut, cre]

Initial release

2021-04-08