tests/testthat/_snaps/windows/estimate_contrasts_effectsize.md
In easystats/estimate: Estimation of Model-Based Predictions, Contrasts and Means
estimate_contrasts - emmeans backend
Code
estimate_contrasts(model, backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "none", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "emmeans", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | partial_d | es 95% CI
---------------------------------------
setosa | 1.94 | [ 1.48, 2.39]
setosa | 1.34 | [ 0.91, 1.76]
versicolor | -0.60 | [-1.00, -0.20]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "marginal", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p | marginal_d
-------------------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001 | 1.16
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001 | 0.80
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003 | -0.36
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "boot", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | Cohen's d | Cohen's d 95% CI
-----------------------------------------
setosa | 1.94 | [ 1.52, 2.39]
setosa | 1.34 | [ 0.82, 1.72]
versicolor | -0.60 | [-0.92, -0.22]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "boot", es_type = "akp.robust.d",
backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | Robust Cohen's d | Robust Cohen's d 95% CI
-------------------------------------------------------
setosa | 1.88 | [ 1.42, 2.49]
setosa | 1.37 | [ 0.92, 1.78]
versicolor | -0.51 | [-0.90, -0.17]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "boot", es_type = "hedges.g", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | Hedges' g | Hedges' g 95% CI
-----------------------------------------
setosa | 1.93 | [ 1.51, 2.38]
setosa | 1.33 | [ 0.82, 1.71]
versicolor | -0.60 | [-0.91, -0.22]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
estimate_contrasts - marginaleffects backend
Code
estimate_contrasts(model, backend = "marginaleffects")
Message
We selected `contrast=c("Species")`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(147) | p
------------------------------------------------------------------------------
versicolor | setosa | -0.66 | 0.07 | [-0.79, -0.52] | -9.69 | < .001
virginica | setosa | -0.45 | 0.07 | [-0.59, -0.32] | -6.68 | < .001
virginica | versicolor | 0.20 | 0.07 | [ 0.07, 0.34] | 3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "none", backend = "marginaleffects")
Message
We selected `contrast=c("Species")`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(147) | p
------------------------------------------------------------------------------
versicolor | setosa | -0.66 | 0.07 | [-0.79, -0.52] | -9.69 | < .001
virginica | setosa | -0.45 | 0.07 | [-0.59, -0.32] | -6.68 | < .001
virginica | versicolor | 0.20 | 0.07 | [ 0.07, 0.34] | 3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "marginal", backend = "marginaleffects")
Message
We selected `contrast=c("Species")`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(147) | p | marginal_d
-------------------------------------------------------------------------------------------
versicolor | setosa | -0.66 | 0.07 | [-0.79, -0.52] | -9.69 | < .001 | -1.16
virginica | setosa | -0.45 | 0.07 | [-0.59, -0.32] | -6.68 | < .001 | -0.80
virginica | versicolor | 0.20 | 0.07 | [ 0.07, 0.34] | 3.00 | 0.003 | 0.36
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
easystats/estimate documentation built on April 5, 2025, 1:36 p.m.
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estimate_contrasts - emmeans backend
Code
estimate_contrasts(model, backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "none", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "emmeans", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | partial_d | es 95% CI
---------------------------------------
setosa | 1.94 | [ 1.48, 2.39]
setosa | 1.34 | [ 0.91, 1.76]
versicolor | -0.60 | [-1.00, -0.20]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "marginal", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p | marginal_d
-------------------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001 | 1.16
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001 | 0.80
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003 | -0.36
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "boot", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | Cohen's d | Cohen's d 95% CI
-----------------------------------------
setosa | 1.94 | [ 1.52, 2.39]
setosa | 1.34 | [ 0.82, 1.72]
versicolor | -0.60 | [-0.92, -0.22]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "boot", es_type = "akp.robust.d",
backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | Robust Cohen's d | Robust Cohen's d 95% CI
-------------------------------------------------------
setosa | 1.88 | [ 1.42, 2.49]
setosa | 1.37 | [ 0.92, 1.78]
versicolor | -0.51 | [-0.90, -0.17]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "boot", es_type = "hedges.g", backend = "emmeans")
Message
No variable was specified for contrast estimation. Selecting `contrast =
"Species"`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | 95% CI | SE | t(147) | p
------------------------------------------------------------------------------
setosa | versicolor | 0.66 | [ 0.52, 0.79] | 0.07 | 9.69 | < .001
setosa | virginica | 0.45 | [ 0.32, 0.59] | 0.07 | 6.68 | < .001
versicolor | virginica | -0.20 | [-0.34, -0.07] | 0.07 | -3.00 | 0.003
Level1 | Hedges' g | Hedges' g 95% CI
-----------------------------------------
setosa | 1.93 | [ 1.51, 2.38]
setosa | 1.33 | [ 0.82, 1.71]
versicolor | -0.60 | [-0.91, -0.22]
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
estimate_contrasts - marginaleffects backend
Code
estimate_contrasts(model, backend = "marginaleffects")
Message
We selected `contrast=c("Species")`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(147) | p
------------------------------------------------------------------------------
versicolor | setosa | -0.66 | 0.07 | [-0.79, -0.52] | -9.69 | < .001
virginica | setosa | -0.45 | 0.07 | [-0.59, -0.32] | -6.68 | < .001
virginica | versicolor | 0.20 | 0.07 | [ 0.07, 0.34] | 3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "none", backend = "marginaleffects")
Message
We selected `contrast=c("Species")`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(147) | p
------------------------------------------------------------------------------
versicolor | setosa | -0.66 | 0.07 | [-0.79, -0.52] | -9.69 | < .001
virginica | setosa | -0.45 | 0.07 | [-0.59, -0.32] | -6.68 | < .001
virginica | versicolor | 0.20 | 0.07 | [ 0.07, 0.34] | 3.00 | 0.003
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
Code
estimate_contrasts(model, effectsize = "marginal", backend = "marginaleffects")
Message
We selected `contrast=c("Species")`.
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(147) | p | marginal_d
-------------------------------------------------------------------------------------------
versicolor | setosa | -0.66 | 0.07 | [-0.79, -0.52] | -9.69 | < .001 | -1.16
virginica | setosa | -0.45 | 0.07 | [-0.59, -0.32] | -6.68 | < .001 | -0.80
virginica | versicolor | 0.20 | 0.07 | [ 0.07, 0.34] | 3.00 | 0.003 | 0.36
Variable predicted: Sepal.Width
Predictors contrasted: Species
p-values are uncorrected.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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