Deprecation of sjstats::anova_stats() about cgpfunctions

[strengejacke]

If model_parameters() turns out to not be a full replacement of anova_stats() and there might be some information missing, let me know.

[ibecav]

Thanks Daniel, understand. Thank you for being proactive! I can work with this. Just to make sure I understand you plan on deprecating in a few weeks? How how until removal? I can manage the work it's just all about timing.

[strengejacke]

Well, I'm submitting an update of sjstats to CRAN today (without any changes that affect your package). The next update with deprecation would probably be in about 2-3 month, there is no pressure. However, anova_stats() does not work properly for repeated measurements anova, while the implementation in effectsize / parameters does. I don't want to recode everything from scratch to make anova_stats() work correctly for those "edge cases", so I want to "navigate" users to use effectsize and deprecate anova_stats().

[strengejacke]

If you plan to address this issue later, deprecation and removal in sjstats can also wait longer.

[ibecav]

No problem at all I just needed to know if I had days or weeks to make the adjustments. Your plan is more than reasonable and really not a lot of work for me so just timing.

[strengejacke]

Btw, the next version of parameters (to be release by the end of January / beginning of February) will also be able to add a Power column to the output, just in case you need that information as well.

library(sjstats)
library(parameters)
data(efc)

# fit linear model
fit <- aov(
  c12hour ~ as.factor(e42dep) + as.factor(c172code) + c160age,
  data = efc
)

anova_stats(car::Anova(fit, type = 2))
#> term                |     sumsq |    meansq |  df | statistic | p.value | etasq | partial.etasq | omegasq | partial.omegasq | epsilonsq | cohens.f | power
#> ----------------------------------------------------------------------------------------------------------------------------------------------------------
#> as.factor(e42dep)   | 4.265e+05 | 1.422e+05 |   3 |    80.299 |  < .001 | 0.212 |         0.224 |   0.209 |           0.221 |     0.209 |    0.537 | 1.000
#> as.factor(c172code) |  7352.049 |  3676.025 |   2 |     2.076 |   0.126 | 0.004 |         0.005 |   0.002 |           0.003 |     0.002 |    0.071 | 0.429
#> c160age             | 1.052e+05 | 1.052e+05 |   1 |    59.408 |  < .001 | 0.052 |         0.066 |   0.051 |           0.065 |     0.051 |    0.267 | 1.000
#> Residuals           | 1.476e+06 |  1770.307 | 834 |           |         |       |               |         |                 |           |          |

model_parameters(fit, type = 2, power = TRUE)
#> Parameter           | Sum_Squares |  df | Mean_Square |     F |      p |  Power
#> -------------------------------------------------------------------------------
#> as.factor(e42dep)   |    4.26e+05 |   3 |    1.42e+05 | 80.30 | < .001 | 100.0%
#> as.factor(c172code) |     7352.05 |   2 |     3676.02 |  2.08 | 0.126  |  42.9%
#> c160age             |    1.05e+05 |   1 |    1.05e+05 | 59.41 | < .001 | 100.0%
#> Residuals           |    1.48e+06 | 834 |     1770.31 |       |        |

^{Created on 2021-01-08 by the reprex package (v0.3.0)}