Package 'repmod' reference manual

Title:	Create Report Table from Different Objects
Description:	Tools for generating descriptives and report tables for different models, data.frames and tables and exporting them to different formats.
Authors:	David Hervas Marin
Maintainer:	David Hervas Marin <[email protected]>
License:	GPL (>=2)
Version:	0.4.02
Built:	2024-11-16 16:47:14 UTC
Source:	https://github.com/david-hervas/repmod

ROC area under curve

Description

Estimates AUC from predicted and observed values

Usage

AUC(pred, obs)
AUC(pred, obs)

Arguments

`pred`	Numeric vector of predicted values
`obs`	Numeric vector of observed values or factor with two levels

Value

Returns the AUC

Examples

glm1 <- glm(case ~ spontaneous + age, data=infert, family="binomial")
pred1 <- fitted(glm1)
AUC(pred1, infert$case)
glm1 <- glm(case ~ spontaneous + age, data=infert, family="binomial")
pred1 <- fitted(glm1)
AUC(pred1, infert$case)

Bootstrap optimism correction for models

Description

Returns optimism correction for absolute fit values

Usage

boot_model(
  formula,
  data,
  B = 200,
  fit_function = "lm",
  metric = if (length(unique(data[, as.character(formula)[2]])) == 2) "AUC" else "RMSE",
  predict.control = list(NULL),
  ...
)
boot_model(
  formula,
  data,
  B = 200,
  fit_function = "lm",
  metric = if (length(unique(data[, as.character(formula)[2]])) == 2) "AUC" else "RMSE",
  predict.control = list(NULL),
  ...
)

Arguments

`formula`	An object of class "formula" describing the model to be validated
`data`	A data frame containing the variables specified in formula argument
`B`	Number of bootstrap samples
`fit_function`	Name of the model fitting function
`metric`	Performance metric to estimate: RMSE, MSE, MAE or AUC
`predict.control`	Named list of arguments to pass to the predict function of the model
`...`	Further arguments passed to the model fitting function

Value

Optimism correction values for the selected performance metric

Examples

boot_model(Petal.Length ~ Sepal.Width + Species, data=iris)
boot_model(Petal.Length ~ Sepal.Width + Species, data=iris)

Auxiliary functions for report.data.frame

Description

Internal function for categorical summary

Usage

cat_summary(x, digits)
cat_summary(x, digits)

Arguments

`x`	A vector of class character
`digits`	Number of digits for rounding

Value

Returns a summary of a categorical variable

Plot of the coefficients of a model

Description

Creates a plot of the coefficients of a model.

Usage

coefplot(
  coefs,
  lwr.int = coefs,
  upper.int = coefs,
  offset = 0,
  coefnames = names(coefs),
  abline.pos = 0,
  sorted = FALSE,
  reverse = FALSE,
  pch = 16,
  xlim = c(min(lwr.int, na.rm = TRUE), max(upper.int, na.rm = TRUE)),
  ylim = c(1, length(coefs)),
  color = "black",
  ...
)
coefplot(
  coefs,
  lwr.int = coefs,
  upper.int = coefs,
  offset = 0,
  coefnames = names(coefs),
  abline.pos = 0,
  sorted = FALSE,
  reverse = FALSE,
  pch = 16,
  xlim = c(min(lwr.int, na.rm = TRUE), max(upper.int, na.rm = TRUE)),
  ylim = c(1, length(coefs)),
  color = "black",
  ...
)

Arguments

`coefs`	A vector with each coefficient
`lwr.int`	A vector with the lower end of the CI
`upper.int`	A vector with the upper end of the CI
`offset`	Y-axis offset for the coefficients
`coefnames`	Name for each variable
`abline.pos`	Position for the vertical reference line
`sorted`	Should the coefficients be sorted from highest to lowest?
`reverse`	Should the order be reversed?
`pch`	Type of point
`xlim`	Limits of the X-axis
`ylim`	Limits of the Y-axis
`color`	Color for the points
`...`	Further arguments passed to axis()

Value

A plot of the coefficients with their CI

Examples

lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
a<-report(lm1)
oldpar <- par()
par(mar=c(4, 10, 3, 2))
#Coefplot calling plot.reportmodel
plot(a)
par(mar=oldpar$mar)  #Restore old margin values
#Manual coefplot
coefplot(coefs=c(1, 2, 3), lwr.int=c(0, 1, 2), upper.int=c(5, 6, 7), coefnames=c("A", "B", "C"))
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
a<-report(lm1)
oldpar <- par()
par(mar=c(4, 10, 3, 2))
#Coefplot calling plot.reportmodel
plot(a)
par(mar=oldpar$mar)  #Restore old margin values
#Manual coefplot
coefplot(coefs=c(1, 2, 3), lwr.int=c(0, 1, 2), upper.int=c(5, 6, 7), coefnames=c("A", "B", "C"))

K-fold cross-validation for models

Description

Returns cross-validated absolute fit values

Usage

cv_model(
  formula,
  data,
  k = 5,
  fit_function = "lm",
  metric = if (length(unique(data[, as.character(formula)[2]])) == 2) "AUC" else "RMSE",
  predict.control = list(NULL),
  ...
)
cv_model(
  formula,
  data,
  k = 5,
  fit_function = "lm",
  metric = if (length(unique(data[, as.character(formula)[2]])) == 2) "AUC" else "RMSE",
  predict.control = list(NULL),
  ...
)

Arguments

`formula`	An object of class "formula" describing the model to be validated
`data`	A data frame containing the variables specified in formula argument
`k`	Number of folds
`fit_function`	Name of the model fitting function
`metric`	Performance metric to estimate: RMSE, MSE, MAE or AUC
`predict.control`	Named list of arguments to pass to the predict function of the model
`...`	Further arguments passed to the model fitting function

Value

Cross-validated values for the selected performance metric

Examples

cv_model(Petal.Length ~ Sepal.Width + Species, data=iris)
cv_model(Petal.Length ~ Sepal.Width + Species, data=iris)

Mean absolute error

Description

Estimates mean absolute error from predicted and observed values

Usage

MAE(pred, obs)
MAE(pred, obs)

Arguments

`pred`	Numeric vector of predicted values
`obs`	Numeric vector of observed values

Value

Returns the MAE

Examples

lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
pred1 <- fitted(lm1)
MAE(pred1, iris$Petal.Length)
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
pred1 <- fitted(lm1)
MAE(pred1, iris$Petal.Length)

Export a table to excel

Description

Exports a table to Excel.

Usage

make_csv_table(x, file, info)
make_csv_table(x, file, info)

Arguments

`x`	A data.frame object
`file`	Name of the file
`info`	Footer for the table

Value

Creates a .csv file with the table

Export a table to latex

Description

Exports a table to latex.

Usage

make_latex_table(x, file)
make_latex_table(x, file)

Arguments

`x`	A data.frame object
`file`	Name of the file

Value

Creates a .txt file with latex code for the table

Make a table from report

Description

Auxiliary function to create tables.

Usage

make_table(x, file, type, info = NULL, ...)
make_table(x, file, type, info = NULL, ...)

Arguments

`x`	A data.frame object
`file`	Name of the file
`type`	Type of file
`info`	Footer for the table
`...`	Additional parameters passed to make_word_table

Value

Creates a file with the table

Export a table to word

Description

Exports a table to Word.

Usage

make_word_table(x, file, info = NULL, use.rownames = TRUE)
make_word_table(x, file, info = NULL, use.rownames = TRUE)

Arguments

`x`	A data.frame object
`file`	Name of the file
`info`	Footer for the table
`use.rownames`	Should row names be added to the output?

Value

Creates a word file with the table

Auxiliary matrix paste function

Description

Internal function for report.table

Usage

matrixPaste(..., sep = rep(" ", length(list(...)) - 1))
matrixPaste(..., sep = rep(" ", length(list(...)) - 1))

Arguments

`...`	Matrices to paste
`sep`	Separator for the paste function

Value

Returns a matrix with the different matrices used as input pasted together

Mean squared error

Description

Estimates mean squared error from predicted and observed values

Usage

MSE(pred, obs)
MSE(pred, obs)

Arguments

`pred`	Numeric vector of predicted values
`obs`	Numeric vector of observed values

Value

Returns the MSE

Examples

lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
pred1 <- fitted(lm1)
MSE(pred1, iris$Petal.Length)
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
pred1 <- fitted(lm1)
MSE(pred1, iris$Petal.Length)

Auxiliary functions for report.data.frame

Description

Internal function for numerical summary

Usage

numeric_summary(x, digits)
numeric_summary(x, digits)

Arguments

`x`	A vector of class numeric
`digits`	Number of digits for rounding

Value

Returns a summary of a numerical variable

Coefplot for reportmodel objects

Description

Creates a coefplot from the reportmodel object.

Usage

## S3 method for class 'reportmodel'
plot(x, ...)
## S3 method for class 'reportmodel'
plot(x, ...)

Arguments

`x`	A reportmodel object
`...`	Further arguments passed to coefplot

Value

Returns a plot of each coefficient in the model with its 95

Examples

lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
a<-report(lm1)
oldpar <- par()
par(mar=c(4, 10, 3, 2))
plot(a)   #Coefplot calling plot.reportmodel
par(mar=oldpar$mar)
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
a<-report(lm1)
oldpar <- par()
par(mar=c(4, 10, 3, 2))
plot(a)   #Coefplot calling plot.reportmodel
par(mar=oldpar$mar)

Generic function for creating reporting tables

Description

Generic function for creating reporting tables.

Usage

report(x, ...)
report(x, ...)

Arguments

`x`	An compatibleobject that can be summarized
`...`	further arguments passed to make_table

Value

A data frame with the report table

Examples

report(iris)  #Report of descriptive statistics
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
report(lm1)   #Report of model
report(iris)  #Report of descriptive statistics
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
report(lm1)   #Report of model

Report from beta regression model

Description

Creates a report table from a beta regression model.

Usage

## S3 method for class 'betareg'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'betareg'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A betareg model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report models from brms package

Description

Creates a report table from model fitted by brms.

Usage

## S3 method for class 'brmsfit'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'brmsfit'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A brms model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from ordinal model

Description

Creates a report table from an ordinal model.

Usage

## S3 method for class 'clm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'clm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	An ordinal model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from ordinal mixed model

Description

Creates a report table from an ordinal mixed model.

Usage

## S3 method for class 'clmm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'clmm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	An ordinal model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from cox regression model

Description

Creates a report table from a cox model.

Usage

## S3 method for class 'coxph'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'coxph'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A cox model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report tables of summary data

Description

Creates a report table ready for publication.

Usage

## S3 method for class 'data.frame'
report(
  x,
  by = NULL,
  remove.by = FALSE,
  file = NULL,
  type = "word",
  digits = 2,
  digitscat = digits,
  print = TRUE,
  ...
)
## S3 method for class 'data.frame'
report(
  x,
  by = NULL,
  remove.by = FALSE,
  file = NULL,
  type = "word",
  digits = 2,
  digitscat = digits,
  print = TRUE,
  ...
)

Arguments

`x`	A data.frame object
`by`	Grouping variable for the report
`remove.by`	Remove grouping variable from the report table?
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimal places
`digitscat`	Number of decimal places for categorical variables (if different to digits)
`print`	Should the report table be printed on screen?
`...`	further arguments passed to make_table()

Value

Returns a summary table of the data in publication-friendly format

Examples

report(iris)
(reporTable<-report(iris, by="Species"))
class(reporTable)
report(iris)
(reporTable<-report(iris, by="Species"))
class(reporTable)

Default function for report

Description

This is a default function for calling summary(x) on non-implemented classes.

Usage

## Default S3 method:
report(x, ...)
## Default S3 method:
report(x, ...)

Arguments

`x`	Any object without specific report function
`...`	further arguments passed to summary

Value

A summary of the object

Report from categorical variable

Description

Creates a report table.

Usage

## S3 method for class 'factor'
report(x, ...)
## S3 method for class 'factor'
report(x, ...)

Arguments

`x`	A categorical variable
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from generalized linear model

Description

Creates a report table from a generalized linear model.

Usage

## S3 method for class 'glm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'glm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A generalized linear model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from generalized linear mixed model

Description

Creates a report table from a generalized linear mixed model.

Usage

## S3 method for class 'glmerMod'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'glmerMod'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A generalized linear mixed model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from generalized linear mixed model from ADMB

Description

Creates a report table from a glmmadmb model.

Usage

## S3 method for class 'glmmadmb'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'glmmadmb'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A generalized linear mixed model object (glmmabmb)
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report models from glmnet package

Description

Creates a report table from models fitted by glmnet.

Usage

## S3 method for class 'glmnet'
report(
  x,
  s,
  gamma = 1,
  drop.zero = TRUE,
  file = NULL,
  type = "word",
  digits = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'glmnet'
report(
  x,
  s,
  gamma = 1,
  drop.zero = TRUE,
  file = NULL,
  type = "word",
  digits = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A glmnet model object
`s`	Value of lambda for estimating the coefficients
`gamma`	Value of gamma for estimating the coefficients (only used in relaxed fits)
`drop.zero`	Should zero coefficients be dropped?
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from generalized least squares model

Description

Creates a report table from a generalized least squares model.

Usage

## S3 method for class 'gls'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'gls'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A gls object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from linear model

Description

Creates a report table from a linear model.

Usage

## S3 method for class 'lm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'lm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A linear model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from linear mixed model

Description

Creates a report table from a linear mixed model.

Usage

## S3 method for class 'lmerMod'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'lmerMod'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A linear mixed model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from quantile mixed model

Description

Creates a report table from a quantile mixed model.

Usage

## S3 method for class 'lqmm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'lqmm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A quantile model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from linear mixed model with pvalues

Description

Creates a report table from a linear mixed model.

Usage

## S3 method for class 'merModLmerTest'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'merModLmerTest'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A linear mixed model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from numeric variable

Description

Creates a report table.

Usage

## S3 method for class 'numeric'
report(x, ...)
## S3 method for class 'numeric'
report(x, ...)

Arguments

`x`	A numeric variable
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from robust linear model (rlm)

Description

Creates a report table from a robust linear model.

Usage

## S3 method for class 'rlm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'rlm'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A rlm object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Report from quantile regression model

Description

Creates a report table from a quantile regression model.

Usage

## S3 method for class 'rq'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)
## S3 method for class 'rq'
report(
  x,
  file = NULL,
  type = "word",
  digits = 3,
  digitspvals = 3,
  info = TRUE,
  print = TRUE,
  exclude = NULL,
  ...
)

Arguments

`x`	A quantreg model object
`file`	Name of the file to export the table
`type`	Format of the file
`digits`	Number of decimals
`digitspvals`	Number of decimals for p-values
`info`	If TRUE, include call in the exported table
`print`	Should the report table be printed on screen?
`exclude`	Vector with rownames to remove from output
`...`	Further arguments passed to make_table

Value

A data frame with the report table

Root mean squared error

Description

Estimates root mean squared error from predicted and observed values

Usage

RMSE(pred, obs)
RMSE(pred, obs)

Arguments

`pred`	Numeric vector of predicted values
`obs`	Numeric vector of observed values

Value

Returns the RMSE

Examples

lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
pred1 <- fitted(lm1)
RMSE(pred1, iris$Petal.Length)
lm1 <- lm(Petal.Length ~ Sepal.Width + Species, data=iris)
pred1 <- fitted(lm1)
RMSE(pred1, iris$Petal.Length)

Function to compute bootstrap confidence intervals for robust linear regression models

Description

Estimates confidence intervals for rlm models.

Usage

rob.ci(x, level = 0.95, maxit = 200, R = 2000)
rob.ci(x, level = 0.95, maxit = 200, R = 2000)

Arguments

`x`	A rlm object
`level`	Confidence level for the interval
`maxit`	Maximum number of iterations per fit
`R`	Number of boostrap samples

Value

A matrix with bootstrap confidence intervals for each variable in the model

Function to compute p-values for robust linear regression models

Description

Estimates p-values for rlm models.

Usage

rob.pvals(x)
rob.pvals(x)

Arguments

`x`	A rlm object

Value

A vector of p-values

Set header names for word tables

Description

Internal function for make_word_table.

Usage

set_noms(x, args)
set_noms(x, args)

Arguments

`x`	A flextable object
`args`	A names list with the header names

Value

A flextable object with assigned header names

Generic VarCorr function

Description

Extract Variance-Covariance Matrix.

Usage

VarCorr(x, sigma = 1, ...)
VarCorr(x, sigma = 1, ...)

Arguments

`x`	A model object
`sigma`	Optional value used as a multiplier for the standard deviations
`...`	Further arguments passed to VarrCorr methods

Value

A Variance-Covariance Matrix

Package 'repmod'

Help Index

ROC area under curve

Description

Usage

Arguments

Value

Examples

Bootstrap optimism correction for models

Description

Usage

Arguments

Value

Examples

Auxiliary functions for report.data.frame

Description

Usage

Arguments

Value

Plot of the coefficients of a model

Description

Usage

Arguments

Value

Examples

K-fold cross-validation for models

Description

Usage

Arguments

Value

Examples

Mean absolute error

Description

Usage

Arguments

Value

Examples

Export a table to excel

Description

Usage

Arguments

Value

Export a table to latex

Description

Usage

Arguments

Value

Make a table from report

Description

Usage

Arguments

Value

Export a table to word

Description

Usage

Arguments

Value

Auxiliary matrix paste function

Description

Usage

Arguments

Value

Mean squared error

Description

Usage

Arguments

Value

Examples

Auxiliary functions for report.data.frame

Description

Usage

Arguments

Value

Coefplot for reportmodel objects

Description

Usage

Arguments

Value

Examples

Generic function for creating reporting tables