Logistic models: Be less verbose by default + be less scary for users with less red

[DominiqueMakowski]

1. messages that are not warnings/errors and are information should be in yellow. Red really makes it look like something is wrong, and can frighten new users & students 👹
2. I would remove the message about the exponentiate. While the one above is information, that one is a _(debatable) suggestion and should be in docs

[bwiernik]

The red is just coming from your RStudio no? RStudio uses the same color for all messages, warnings, and errors.

[DominiqueMakowski]

I don't think these are messages per se, they are just part of the output, so we can specify colors as we often do elsewhere where we print info in yellow

[strengejacke]

Second is a message and only shown once per session:

parameters/R/format.R

Line 909 in 034f5df

if (!is.null(msg) && isTRUE(getOption("parameters_warning_exponentiate", TRUE))) {

[strengejacke]

First one is also a message and not shown in red:

parameters/R/format.R

Line 857 in 034f5df

}

[DominiqueMakowski]

I'd vote for:

1. Set the exponentiate warning to false by default (I don't think this info warrants an intrusive message, even once per sesh)
2. Transform the information about how CIs/ps are computed as part of the pretty printing and display them in yellow

In general, we should probably take a look at homogenizing outputs / colour schemes, we have sometimes some green, yellow, reds, etc. that we might be using inconsistently.
Arguably the problem with colours is that they must work on dark and white backgrounds, but I think if we stick to default for text, yellow for information, green/red for "passed/failed checks", and then warnings when actual warnings, we should be alright

[strengejacke]

What about model info? Yellow, too?

[DominiqueMakowski]

it's a bit much, white is fine I'd say

Maybe we could add a "Note: " before "Uncertainty intervals..." just to suggest to participants that it's not an issue per se that it's just for their information

[strengejacke]

Set the exponentiate warning to false by default (I don't think this info warrants an intrusive message, even once per sesh)

But then it's never shown.

You can always suppress all information with verbose = FALSE. And you can in general customize the amount of default information using global options:

https://easystats.github.io/parameters/reference/print.parameters_model.html#global-options-to-customize-messages-and-tables-when-printing

[DominiqueMakowski]

[strengejacke]

Note that this note is useful for people less familiar with log(it) transformations! See also:

library(parameters)
model <- lm(log(mpg) ~ hp, data = mtcars)
model_parameters(model)
#> Parameter   | Coefficient |       SE |         95% CI | t(30) |      p
#> ----------------------------------------------------------------------
#> (Intercept) |        3.46 |     0.08 | [ 3.30,  3.62] | 44.04 | < .001
#> hp          |   -3.43e-03 | 4.87e-04 | [ 0.00,  0.00] | -7.05 | < .001
#> 
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#>   using a Wald t-distribution approximation.
#> 
#> The model has a log-transformed response variable. Consider using
#>   `exponentiate = TRUE` to interpret coefficients as ratios.

library(parameters)
model <- lm(log(mpg) ~ hp, data = mtcars)
model_parameters(model, exponentiate = TRUE)
#> Parameter   | Coefficient |       SE |         95% CI | t(30) |      p
#> ----------------------------------------------------------------------
#> (Intercept) |       31.83 |     2.50 | [27.11, 37.37] | 44.04 | < .001
#> hp          |        1.00 | 4.85e-04 | [ 1.00,  1.00] | -7.05 | < .001
#> 
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#>   using a Wald t-distribution approximation.
#> 
#> The model has a log-transformed response variable, and exponentiated
#>   parameters are reported. A one-unit increase in the predictor is
#>   associated with multiplying the outcome by that predictor's coefficient.

[strengejacke]

And yes, your alerting red color is just because you have an RStudio setting that prints messages in red?!?

[DominiqueMakowski]

Note that this note is useful for people less familiar with log(it) transformations! See also:

Yes but printing this in the output is IMO not the right place for this kind of information 🙃

you have an RStudio setting that prints messages in red?!?