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Format linear model statistics

Source: R/format_stats_lm.R
format_stats.lm.Rd

This method formats (generalized) linear model statistics from the class lm or glm. If no term is specified, overall model statistics are returned. For linear models (lm objects), this includes the R-squared, F statistic, and p-value. For generalized linear models (glm objects), this includes deviance and AIC. The default output is APA formatted, but this function allows control over numbers of digits, leading zeros, italics, degrees of freedom, and output format of Markdown or LaTeX.

Usage

# S3 method for class 'lm'
format_stats(
  x,
  term = NULL,
  digits = 3,
  pdigits = 3,
  pzero = FALSE,
  full = TRUE,
  italics = TRUE,
  dfs = "par",
  type = "md",
  ...
)

Arguments

x

An lm or glm object from stats::lm() or stats::glm().

term

Character string for row name of term to extract statistics for. This must be the exact string returned in the summary() output from the lm or glm object.

digits

Number of digits after the decimal for test statistics.

pdigits

Number of digits after the decimal for p-values, ranging between 1-5 (also controls cutoff for small p-values).

pzero

Logical value (default = FALSE) for whether to include leading zero for p-values.

full

Logical value (default = TRUE) for whether to include extra info (e.g., standard errors and t-values or z-values for terms) or just test statistic and p-value.

italics

Logical value (default = TRUE) for whether statistics labels should be italicized.

dfs

Formatting for degrees of freedom ("par" = parenthetical, "sub" = subscript, "none" = do not print degrees of freedom).

type

Type of formatting ("md" = markdown, "latex" = LaTeX).

...

Additional arguments passed to methods.

Value

A character string of statistical information formatted in Markdown or LaTeX.

See also

Other functions for printing statistical objects: format_bf(), format_corr(), format_stats(), format_stats.BFBayesFactor(), format_stats.aov(), format_stats.easycorrelation(), format_stats.htest(), format_stats.lmerModLmerTest(), format_stats.merMod(), format_ttest()

Examples

test_lm <- lm(mpg ~ cyl * hp, data = mtcars)
test_glm <- glm(am ~ cyl * hp, data = mtcars, family = binomial)

# Format linear model overall statistics
format_stats(test_lm)
#> [1] "_R_^2^ = 0.757, _F_(3, 28) = 33.113, _p_ < .001"

# Format linear model term statistics
format_stats(test_lm, term = "cyl")
#> [1] "_β_ = -4.119, SE = 0.988, _t_ = -4.168, _p_ < .001"

# Format generalized linear model overall statistics
format_stats(test_glm)
#> [1] "Deviance = 28.619, _χ_^2^ = 14.611, AIC = 36.619"

# Format generalized linear model term statistics
format_stats(test_glm, term = "cyl")
#> [1] "_β_ = -1.749, SE = 0.839, _z_ = -2.084, _p_ = .037"

# Remove italics and make degrees of freedom subscripts
format_stats(test_lm, term = "cyl", italics = FALSE, dfs = "sub")
#> [1] "β = -4.119, SE = 0.988, t = -4.168, p < .001"

# Change digits and add leading zero to p-value
format_stats(test_lm, term = "hp", digits = 3, pdigits = 4, pzero = TRUE)
#> [1] "_β_ = -0.171, SE = 0.069, _t_ = -2.470, _p_ = 0.0199"

# Format for LaTeX
format_stats(test_lm, term = "hp", type = "latex")
#> [1] "$\\beta$ = -0.171, SE = 0.069, $t$ = -2.470, $p$ = .020"