Comments (2)
closing this, as I think it's fixed!
Also, I don't think for now we should add a second p column for adjusted, as it would break the easy pattern, and moreover conceptually it would be weird to have both; it's like pizza and pineapple, it's one or the other, but you shouldn't have both 😁
from correlation.
It works at my place, it's just that iris is too small to have differences between holm and none (but try with p_adjust = "bonf"
. Or with the attitude
dataset:
> correlation(attitude, p_adjust="none")
Parameter1 | Parameter2 | r | 95% CI | t | df | p | Method | n_Obs
-------------------------------------------------------------------------------------
rating | complaints | 0.83 | [ 0.66, 0.91] | 7.74 | 28 | < .001 | Pearson | 30
rating | privileges | 0.43 | [ 0.08, 0.68] | 2.49 | 28 | 0.019 | Pearson | 30
rating | learning | 0.62 | [ 0.34, 0.80] | 4.22 | 28 | < .001 | Pearson | 30
rating | raises | 0.59 | [ 0.29, 0.78] | 3.87 | 28 | < .001 | Pearson | 30
rating | critical | 0.16 | [-0.22, 0.49] | 0.84 | 28 | 0.409 | Pearson | 30
rating | advance | 0.16 | [-0.22, 0.49] | 0.83 | 28 | 0.413 | Pearson | 30
complaints | privileges | 0.56 | [ 0.25, 0.76] | 3.56 | 28 | 0.001 | Pearson | 30
complaints | learning | 0.60 | [ 0.30, 0.79] | 3.94 | 28 | < .001 | Pearson | 30
complaints | raises | 0.67 | [ 0.41, 0.83] | 4.77 | 28 | < .001 | Pearson | 30
complaints | critical | 0.19 | [-0.19, 0.51] | 1.01 | 28 | 0.321 | Pearson | 30
complaints | advance | 0.22 | [-0.15, 0.54] | 1.22 | 28 | 0.233 | Pearson | 30
privileges | learning | 0.49 | [ 0.16, 0.72] | 3.00 | 28 | 0.006 | Pearson | 30
privileges | raises | 0.45 | [ 0.10, 0.69] | 2.63 | 28 | 0.014 | Pearson | 30
privileges | critical | 0.15 | [-0.22, 0.48] | 0.79 | 28 | 0.438 | Pearson | 30
privileges | advance | 0.34 | [-0.02, 0.63] | 1.93 | 28 | 0.063 | Pearson | 30
learning | raises | 0.64 | [ 0.36, 0.81] | 4.41 | 28 | < .001 | Pearson | 30
learning | critical | 0.12 | [-0.25, 0.46] | 0.62 | 28 | 0.542 | Pearson | 30
learning | advance | 0.53 | [ 0.21, 0.75] | 3.32 | 28 | 0.003 | Pearson | 30
raises | critical | 0.38 | [ 0.02, 0.65] | 2.15 | 28 | 0.040 | Pearson | 30
raises | advance | 0.57 | [ 0.27, 0.77] | 3.71 | 28 | < .001 | Pearson | 30
critical | advance | 0.28 | [-0.09, 0.58] | 1.56 | 28 | 0.129 | Pearson | 30
> correlation(attitude, p_adjust="BH")
Parameter1 | Parameter2 | r | 95% CI | t | df | p | Method | n_Obs
-------------------------------------------------------------------------------------
rating | complaints | 0.83 | [ 0.66, 0.91] | 7.74 | 28 | < .001 | Pearson | 30
rating | privileges | 0.43 | [ 0.08, 0.68] | 2.49 | 28 | 0.033 | Pearson | 30
rating | learning | 0.62 | [ 0.34, 0.80] | 4.22 | 28 | 0.001 | Pearson | 30
rating | raises | 0.59 | [ 0.29, 0.78] | 3.87 | 28 | 0.002 | Pearson | 30
rating | critical | 0.16 | [-0.22, 0.49] | 0.84 | 28 | 0.457 | Pearson | 30
rating | advance | 0.16 | [-0.22, 0.49] | 0.83 | 28 | 0.457 | Pearson | 30
complaints | privileges | 0.56 | [ 0.25, 0.76] | 3.56 | 28 | 0.004 | Pearson | 30
complaints | learning | 0.60 | [ 0.30, 0.79] | 3.94 | 28 | 0.002 | Pearson | 30
complaints | raises | 0.67 | [ 0.41, 0.83] | 4.77 | 28 | < .001 | Pearson | 30
complaints | critical | 0.19 | [-0.19, 0.51] | 1.01 | 28 | 0.396 | Pearson | 30
complaints | advance | 0.22 | [-0.15, 0.54] | 1.22 | 28 | 0.306 | Pearson | 30
privileges | learning | 0.49 | [ 0.16, 0.72] | 3.00 | 28 | 0.012 | Pearson | 30
privileges | raises | 0.45 | [ 0.10, 0.69] | 2.63 | 28 | 0.026 | Pearson | 30
privileges | critical | 0.15 | [-0.22, 0.48] | 0.79 | 28 | 0.459 | Pearson | 30
privileges | advance | 0.34 | [-0.02, 0.63] | 1.93 | 28 | 0.095 | Pearson | 30
learning | raises | 0.64 | [ 0.36, 0.81] | 4.41 | 28 | < .001 | Pearson | 30
learning | critical | 0.12 | [-0.25, 0.46] | 0.62 | 28 | 0.542 | Pearson | 30
learning | advance | 0.53 | [ 0.21, 0.75] | 3.32 | 28 | 0.006 | Pearson | 30
raises | critical | 0.38 | [ 0.02, 0.65] | 2.15 | 28 | 0.065 | Pearson | 30
raises | advance | 0.57 | [ 0.27, 0.77] | 3.71 | 28 | 0.003 | Pearson | 30
critical | advance | 0.28 | [-0.09, 0.58] | 1.56 | 28 | 0.181 | Pearson | 30
from correlation.
Related Issues (20)
- CRAN check failures HOT 3
- Create GitHub release corresponding to CRAN release
- Changing aesthetics of the correlation plot HOT 2
- Costumizing priors HOT 1
- Multilevel correlation changes when more correlations are computed HOT 6
- Suggestion of new function: `cormatrix_to_excel()` HOT 4
- Factors don't always work as intended
- Multilevel rank correlation HOT 1
- refactoring the `correlation` package HOT 6
- Package version doesn't follow easystats' versioning conventions HOT 1
- Bayesian partial correlations
- bayestestR HOT 2
- X
- Update documentation to discuss handling of missing values HOT 1
- specify adjustment variable HOT 1
- Time series auto- and cross-correlations HOT 1
- A new correlation coefficient (Chatterjee) HOT 8
- Expanding Kendall's Tau to include Tau a and Stuart's c
- Update `{correlation}` on CRAN to prevents user from seeing deprecation warnings HOT 5
- Fix CRAN note HOT 2
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from correlation.