Return at least one effect size measure for `htest` and `BFBayesFactor` objects

Given that most users will stick to the defaults most of the time, they might not even realize that we support this functionality, which would be a shame. It'd be nice if we return at least one effect size by default. The default can be whatever effectsize::effectsize() defaults to.

This is especially relevant for objects that don't have estimates in their tidied data frames:

suppressPackageStartupMessages({
  library(parameters)
  library(BayesFactor)
})
data("raceDolls")

m <- contingencyTableBF(
  raceDolls,
  sampleType = "indepMulti",
  fixedMargin = "cols"
)

parameters(m)
#> Warning: Could not estimate a good default ROPE range. Using 'c(-0.1, 0.1)'.
#> Bayesian contingency table analysis
#> 
#> Parameter |                            Prior |   BF
#> ---------------------------------------------------
#> Ratio     | Independent multinomial (0 +- 1) | 1.81
#> 
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#>   using a MCMC distribution approximation.

parameters(m, effectsize_type = "cramers_v")
#> Warning: Could not estimate a good default ROPE range. Using 'c(-0.1, 0.1)'.
#> Bayesian contingency table analysis
#> 
#> Parameter | Cramer's V (adj.) | Cramers 95% CI |                            Prior |   BF
#> ----------------------------------------------------------------------------------------
#> Ratio     |              0.15 |   [0.00, 0.29] | Independent multinomial (0 +- 1) | 1.81
#> 
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#>   using a MCMC distribution approximation.

^{Created on 2022-10-15 with reprex v2.0.2}

Start at the parameters() entry points for htest and BFBayesFactor objects and compare their default behavior with effectsize::effectsize(). Verify that the default call returns at least one effect-size measure for each object, including cases without estimates in tidied data frames, and use the existing examples as the completion check.