Formats output of lm() model object for a
publication-ready format.
Usage
nice_lm(
model,
b.label = "b",
standardize = FALSE,
mod.id = TRUE,
ci.alternative = "two.sided",
...
)Arguments
- model
The model to be formatted.
- b.label
What to rename the default "b" column (e.g., to capital B if using standardized data for it to be converted to the Greek beta symbol in the nice_table function). Now attempts to automatically detect whether the variables were standardized, and if so, sets
b.label = "B"automatically. Factor variables or dummy variables (only two numeric values) are ignored when checking for standardization. This argument is now deprecated, please use argumentstandardizedirectly instead.- standardize
Logical, whether to standardize the data before refitting the model. If
TRUE, automatically setsb.label = "B". Defaults toFALSE. Note that if you have factor variables, these will be pseudo-betas, so these coefficients could be interpreted more like Cohen's d.- mod.id
Logical. Whether to display the model number, when there is more than one model.
- ci.alternative
Alternative for the confidence interval of the sr2. It can be either "two.sided (the default in this package), "greater", or "less".
- ...
Further arguments to be passed to the effectsize::r2_semipartial function for the effect size.
Value
A formatted dataframe of the specified lm model, with DV, IV, degrees of freedom, regression coefficient, t-value, p-value, and the effect size, the semi-partial correlation squared, and its confidence interval.
Details
The effect size, sr2 (semi-partial correlation squared, also
known as delta R2), is computed through effectsize::r2_semipartial.
Please read the documentation for that function, especially regarding
the interpretation of the confidence interval. In rempsyc, instead
of using the default one-sided alternative ("greater"), we use the
two-sided alternative.
To interpret the sr2, use effectsize::interpret_r2_semipartial().
For the easystats equivalent, use report::report() on the lm()
model object.
See also
Checking simple slopes after testing for moderation:
nice_lm_slopes, nice_mod,
nice_slopes. Tutorial:
https://rempsyc.remi-theriault.com/articles/moderation
Examples
# Make and format model
model <- lm(mpg ~ cyl + wt * hp, mtcars)
nice_lm(model)
#> Dependent Variable Predictor df b t p
#> 1 mpg cyl 27 -0.36523909 -0.7180977 4.788652e-01
#> 2 mpg wt 27 -7.62748929 -5.0146028 2.928375e-05
#> 3 mpg hp 27 -0.10839427 -3.6404181 1.136403e-03
#> 4 mpg wt:hp 27 0.02583659 3.2329593 3.221753e-03
#> sr2 CI_lower CI_upper
#> 1 0.002159615 0.0000000000 0.01306786
#> 2 0.105313085 0.0089876445 0.20163853
#> 3 0.055502405 0.0005550240 0.11934768
#> 4 0.043773344 0.0004377334 0.09898662
# Make and format multiple models
model2 <- lm(qsec ~ disp + drat * carb, mtcars)
my.models <- list(model, model2)
x <- nice_lm(my.models)
x
#> Model Number Dependent Variable Predictor df b t
#> 1 1 mpg cyl 27 -0.365239089 -0.7180977
#> 2 1 mpg wt 27 -7.627489287 -5.0146028
#> 3 1 mpg hp 27 -0.108394273 -3.6404181
#> 4 1 mpg wt:hp 27 0.025836594 3.2329593
#> 5 2 qsec disp 27 -0.006222635 -1.9746464
#> 6 2 qsec drat 27 0.227692395 0.1968842
#> 7 2 qsec carb 27 1.154106215 0.7179431
#> 8 2 qsec drat:carb 27 -0.477539959 -1.0825727
#> p sr2 CI_lower CI_upper
#> 1 4.788652e-01 0.0021596150 0.0000000000 0.01306786
#> 2 2.928375e-05 0.1053130854 0.0089876445 0.20163853
#> 3 1.136403e-03 0.0555024045 0.0005550240 0.11934768
#> 4 3.221753e-03 0.0437733438 0.0004377334 0.09898662
#> 5 5.861684e-02 0.0702566891 0.0000000000 0.19796621
#> 6 8.453927e-01 0.0006984424 0.0000000000 0.01347203
#> 7 4.789590e-01 0.0092872897 0.0000000000 0.05587351
#> 8 2.885720e-01 0.0211165564 0.0000000000 0.09136014
# Get interpretations
cbind(x, Interpretation = effectsize::interpret_r2_semipartial(x$sr2))
#> Model Number Dependent Variable Predictor df b t
#> 1 1 mpg cyl 27 -0.365239089 -0.7180977
#> 2 1 mpg wt 27 -7.627489287 -5.0146028
#> 3 1 mpg hp 27 -0.108394273 -3.6404181
#> 4 1 mpg wt:hp 27 0.025836594 3.2329593
#> 5 2 qsec disp 27 -0.006222635 -1.9746464
#> 6 2 qsec drat 27 0.227692395 0.1968842
#> 7 2 qsec carb 27 1.154106215 0.7179431
#> 8 2 qsec drat:carb 27 -0.477539959 -1.0825727
#> p sr2 CI_lower CI_upper Interpretation
#> 1 4.788652e-01 0.0021596150 0.0000000000 0.01306786 very small
#> 2 2.928375e-05 0.1053130854 0.0089876445 0.20163853 medium
#> 3 1.136403e-03 0.0555024045 0.0005550240 0.11934768 small
#> 4 3.221753e-03 0.0437733438 0.0004377334 0.09898662 small
#> 5 5.861684e-02 0.0702566891 0.0000000000 0.19796621 medium
#> 6 8.453927e-01 0.0006984424 0.0000000000 0.01347203 very small
#> 7 4.789590e-01 0.0092872897 0.0000000000 0.05587351 very small
#> 8 2.885720e-01 0.0211165564 0.0000000000 0.09136014 small