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Print a Model Comparison or ANOVA Table With DMAR p-value Formatting

Source: R/print_anova.R
print_anova.Rd

Pretty-print an ANOVA-like object (the output of stats::anova, car::Anova, lmerTest::anova, etc.) with p-values formatted at a fixed number of decimal places (default 4) and with a “< 10^(-digits_p)” floor for values too small to express. The default behavior of print.anova routes p-values through stats::format.pval, which applies its own digit rule (max(1L, getOption("digits") - 2L)) and switches to scientific notation for tiny values. print_anova() sidesteps that by converting the p-value columns to character strings up front and printing as a data frame.

Usage

print_anova(x, digits_p = 4L)

Arguments

x

An ANOVA-like data frame with one or more Pr(...) columns. Accepts anova objects from stats::anova, car::Anova, car::Manova, and lmerTest::anova.

digits_p

Integer number of decimal places for the p-value column(s). Default 4L.

Value

The input x, invisibly and unchanged.

Details

The returned object is the input x invisibly, unchanged: the underlying numeric p-values retain full precision and can still be indexed (for example as x[["Pr(>F)"]]).

Any column whose name starts with Pr( is formatted as a p-value column. Other columns print at whatever getOption("digits") dictates (so set options(digits = 4) for a uniformly compact display).

See also

format_p, print_summary.

Author

Ken Kelley

Examples

fit <- lm(weight ~ Time + Diet, data = ChickWeight)
print_anova(anova(fit))
#> Analysis of Variance Table
#> 
#> Response: weight
#> 
#>            Df    Sum Sq     Mean Sq    F value   Pr(>F)
#> Time        1 2042343.7 2042343.749 1576.45969 < 0.0001
#> Diet        3  129876.1   43292.019   33.41657 < 0.0001
#> Residuals 573  742336.1    1295.526         NA     <NA>

print_anova(car::Anova(fit, type = "III"))
#> Anova Table (Type III tests)
#> 
#> Response: weight
#> 
#>                 Sum Sq  Df    F value   Pr(>F)
#> (Intercept)   13689.64   1   10.56687   0.0012
#> Time        2016357.15   1 1556.40096 < 0.0001
#> Diet         129876.06   3   33.41657 < 0.0001
#> Residuals    742336.12 573         NA     <NA>

# Underlying numeric p-values are untouched:
a <- anova(fit)
print_anova(a)
#> Analysis of Variance Table
#> 
#> Response: weight
#> 
#>            Df    Sum Sq     Mean Sq    F value   Pr(>F)
#> Time        1 2042343.7 2042343.749 1576.45969 < 0.0001
#> Diet        3  129876.1   43292.019   33.41657 < 0.0001
#> Residuals 573  742336.1    1295.526         NA     <NA>
a[["Pr(>F)"]]   # full-precision doubles
#> [1] 1.226523e-166  6.473189e-20            NA