tests/testthat/_snaps/print.md
In easystats/estimate: Estimation of Model-Based Predictions, Contrasts and Means
estimate_contrasts - by with special character
Code
print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects",
p_adjust = "holm"), table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p
--------------------------------------------------------------------------------
mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999
high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999
high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999
mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999
high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.565
high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.691
mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999
high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.368
high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999
Variable predicted: neg_c_7
Predictors contrasted: c172code
p-value adjustment method: Holm (1979)
Code
print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects",
p_adjust = "holm"), table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(810) | p
----------------------------------------------------------------------------------
low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001
mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999
mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001
mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001
high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999
high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.099
high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001
low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001
mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999
mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | 0.001
high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001
high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.636
high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | > .999
mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001
mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001
mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999
high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001
high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001
high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.450
mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001
high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999
high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.099
high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001
mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001
high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.789
high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.545
high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001
high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001
high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999
high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001
high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
Variable predicted: neg_c_7
Predictors contrasted: c172code, barthtot = [sd]
p-value adjustment method: Holm (1979)
Code
print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p
-------------------------------------------------------------------------------
mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596
high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691
high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360
mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589
high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071
high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099
mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221
high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041
high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181
Variable predicted: neg_c_7
Predictors contrasted: c172code
p-values are uncorrected.
Code
print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(810) | p
----------------------------------------------------------------------------------
low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001
mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596
mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001
mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001
high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691
high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.008
high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001
low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001
mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589
mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | < .001
high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001
high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071
high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | 0.160
mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001
mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001
mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221
high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001
high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001
high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041
mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001
high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360
high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.008
high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001
mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001
high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099
high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.055
high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001
high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001
high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181
high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001
high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
Variable predicted: neg_c_7
Predictors contrasted: c172code, barthtot = [sd]
p-values are uncorrected.
estimate_means - by is list
Code
print(estimate_means(fit, list(c172code = c("low", "high"), c161sex = c(
"Female", "Male")), backend = "marginaleffects"), table_width = Inf,
zap_small = TRUE)
Output
Estimated Marginal Means
c172code | c161sex | Mean | SE | 95% CI | t(825)
-----------------------------------------------------------
low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44
high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31
low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25
high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45
Variable predicted: neg_c_7
Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male')
Predictors averaged: e16sex
Code
print(estimate_means(fit, c("c172code = c('low', 'high')",
"c161sex = c('Female', 'Male')"), backend = "marginaleffects"), table_width = Inf,
zap_small = TRUE)
Output
Estimated Marginal Means
c172code | c161sex | Mean | SE | 95% CI | t(825)
-----------------------------------------------------------
low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44
high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31
low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25
high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45
Variable predicted: neg_c_7
Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male')
Predictors averaged: e16sex
estimate_epectation - don't print empty RE columns
Code
print(estimate_expectation(m, by = "spp", predict = "conditional"), zap_small = TRUE)
Output
Model-based Predictions
spp | Predicted | SE | CI
---------------------------------------
GP | 0.73 | 0.21 | [0.32, 1.14]
PR | 0.42 | 0.16 | [0.11, 0.72]
DM | 0.94 | 0.25 | [0.45, 1.43]
EC-A | 0.60 | 0.19 | [0.24, 0.96]
EC-L | 1.42 | 0.37 | [0.69, 2.14]
DES-L | 1.34 | 0.36 | [0.63, 2.04]
DF | 0.78 | 0.21 | [0.37, 1.19]
Variable predicted: count
Predictors modulated: spp
Predictors controlled: mined (yes)
Predictions are on the conditional-scale.
print - layouts and include data grid
Code
print(out)
Output
Estimated Marginal Means
Species | Mean | SE | 95% CI | t(147)
------------------------------------------------
setosa | 1.46 | 0.06 | [1.34, 1.58] | 24.02
versicolor | 4.26 | 0.06 | [4.14, 4.38] | 70.00
virginica | 5.55 | 0.06 | [5.43, 5.67] | 91.23
Variable predicted: Petal.Length
Predictors modulated: Species
Code
print(out, select = "minimal")
Output
Estimated Marginal Means
Species | Mean (CI)
------------------------------
setosa | 1.46 (1.34, 1.58)
versicolor | 4.26 (4.14, 4.38)
virginica | 5.55 (5.43, 5.67)
Variable predicted: Petal.Length
Predictors modulated: Species
Code
print(out, select = "minimal")
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference (CI) | p
----------------------------------------------------
versicolor | setosa | 2.80 (2.63, 2.97) | <0.001
virginica | setosa | 4.09 (3.92, 4.26) | <0.001
virginica | versicolor | 1.29 (1.12, 1.46) | <0.001
Variable predicted: Petal.Length
Predictors contrasted: Species
p-values are uncorrected.
Code
print(out, select = "{estimate}{stars}|{ci}")
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | CI
-------------------------------------------------
versicolor | setosa | 2.80*** | 2.63, 2.97
virginica | setosa | 4.09*** | 3.92, 4.26
virginica | versicolor | 1.29*** | 1.12, 1.46
Variable predicted: Petal.Length
Predictors contrasted: Species
p-values are uncorrected.
Code
print(estimate_relation(m, by = "qsec"))
Output
Model-based Predictions
qsec | Predicted | SE | 95% CI
---------------------------------------
14.50 | 2.80 | 0.19 | [2.41, 3.18]
15.43 | 2.91 | 0.15 | [2.62, 3.21]
16.37 | 3.03 | 0.11 | [2.81, 3.26]
17.30 | 3.15 | 0.09 | [2.97, 3.32]
18.23 | 3.27 | 0.08 | [3.10, 3.44]
19.17 | 3.38 | 0.10 | [3.17, 3.60]
20.10 | 3.50 | 0.14 | [3.21, 3.78]
21.03 | 3.62 | 0.18 | [3.25, 3.98]
21.97 | 3.73 | 0.22 | [3.28, 4.19]
22.90 | 3.85 | 0.27 | [3.30, 4.40]
Variable predicted: wt
Predictors modulated: qsec
Predictors controlled: mpg (20)
Code
print(estimate_relation(m, by = "qsec"), include_grid = TRUE)
Output
Model-based Predictions
qsec | mpg | Predicted | SE | 95% CI
-----------------------------------------------
14.50 | 20.09 | 2.80 | 0.19 | [2.41, 3.18]
15.43 | 20.09 | 2.91 | 0.15 | [2.62, 3.21]
16.37 | 20.09 | 3.03 | 0.11 | [2.81, 3.26]
17.30 | 20.09 | 3.15 | 0.09 | [2.97, 3.32]
18.23 | 20.09 | 3.27 | 0.08 | [3.10, 3.44]
19.17 | 20.09 | 3.38 | 0.10 | [3.17, 3.60]
20.10 | 20.09 | 3.50 | 0.14 | [3.21, 3.78]
21.03 | 20.09 | 3.62 | 0.18 | [3.25, 3.98]
21.97 | 20.09 | 3.73 | 0.22 | [3.28, 4.19]
22.90 | 20.09 | 3.85 | 0.27 | [3.30, 4.40]
Variable predicted: wt
Predictors modulated: qsec
Predictors controlled: mpg (20)
easystats/estimate documentation built on April 5, 2025, 1:36 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
estimate_contrasts - by with special character
Code
print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects",
p_adjust = "holm"), table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p
--------------------------------------------------------------------------------
mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999
high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999
high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999
mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999
high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.565
high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.691
mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999
high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.368
high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999
Variable predicted: neg_c_7
Predictors contrasted: c172code
p-value adjustment method: Holm (1979)
Code
print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects",
p_adjust = "holm"), table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(810) | p
----------------------------------------------------------------------------------
low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001
mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999
mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001
mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001
high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999
high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.099
high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001
low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001
mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999
mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | 0.001
high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001
high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.636
high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | > .999
mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001
mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001
mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999
high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001
high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001
high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.450
mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001
high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999
high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.099
high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001
mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001
high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.789
high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.545
high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001
high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001
high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999
high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001
high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
Variable predicted: neg_c_7
Predictors contrasted: c172code, barthtot = [sd]
p-value adjustment method: Holm (1979)
Code
print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p
-------------------------------------------------------------------------------
mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596
high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691
high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360
mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589
high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071
high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099
mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221
high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041
high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181
Variable predicted: neg_c_7
Predictors contrasted: c172code
p-values are uncorrected.
Code
print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(810) | p
----------------------------------------------------------------------------------
low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001
mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596
mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001
mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001
high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691
high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.008
high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001
low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001
mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001
mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589
mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | < .001
high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001
high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071
high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | 0.160
mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001
mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001
mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221
high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001
high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001
high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041
mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001
high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360
high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.008
high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001
mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001
high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001
high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099
high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.055
high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001
high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001
high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181
high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001
high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001
Variable predicted: neg_c_7
Predictors contrasted: c172code, barthtot = [sd]
p-values are uncorrected.
estimate_means - by is list
Code
print(estimate_means(fit, list(c172code = c("low", "high"), c161sex = c(
"Female", "Male")), backend = "marginaleffects"), table_width = Inf,
zap_small = TRUE)
Output
Estimated Marginal Means
c172code | c161sex | Mean | SE | 95% CI | t(825)
-----------------------------------------------------------
low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44
high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31
low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25
high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45
Variable predicted: neg_c_7
Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male')
Predictors averaged: e16sex
Code
print(estimate_means(fit, c("c172code = c('low', 'high')",
"c161sex = c('Female', 'Male')"), backend = "marginaleffects"), table_width = Inf,
zap_small = TRUE)
Output
Estimated Marginal Means
c172code | c161sex | Mean | SE | 95% CI | t(825)
-----------------------------------------------------------
low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44
high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31
low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25
high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45
Variable predicted: neg_c_7
Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male')
Predictors averaged: e16sex
estimate_epectation - don't print empty RE columns
Code
print(estimate_expectation(m, by = "spp", predict = "conditional"), zap_small = TRUE)
Output
Model-based Predictions
spp | Predicted | SE | CI
---------------------------------------
GP | 0.73 | 0.21 | [0.32, 1.14]
PR | 0.42 | 0.16 | [0.11, 0.72]
DM | 0.94 | 0.25 | [0.45, 1.43]
EC-A | 0.60 | 0.19 | [0.24, 0.96]
EC-L | 1.42 | 0.37 | [0.69, 2.14]
DES-L | 1.34 | 0.36 | [0.63, 2.04]
DF | 0.78 | 0.21 | [0.37, 1.19]
Variable predicted: count
Predictors modulated: spp
Predictors controlled: mined (yes)
Predictions are on the conditional-scale.
print - layouts and include data grid
Code
print(out)
Output
Estimated Marginal Means
Species | Mean | SE | 95% CI | t(147)
------------------------------------------------
setosa | 1.46 | 0.06 | [1.34, 1.58] | 24.02
versicolor | 4.26 | 0.06 | [4.14, 4.38] | 70.00
virginica | 5.55 | 0.06 | [5.43, 5.67] | 91.23
Variable predicted: Petal.Length
Predictors modulated: Species
Code
print(out, select = "minimal")
Output
Estimated Marginal Means
Species | Mean (CI)
------------------------------
setosa | 1.46 (1.34, 1.58)
versicolor | 4.26 (4.14, 4.38)
virginica | 5.55 (5.43, 5.67)
Variable predicted: Petal.Length
Predictors modulated: Species
Code
print(out, select = "minimal")
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference (CI) | p
----------------------------------------------------
versicolor | setosa | 2.80 (2.63, 2.97) | <0.001
virginica | setosa | 4.09 (3.92, 4.26) | <0.001
virginica | versicolor | 1.29 (1.12, 1.46) | <0.001
Variable predicted: Petal.Length
Predictors contrasted: Species
p-values are uncorrected.
Code
print(out, select = "{estimate}{stars}|{ci}")
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | CI
-------------------------------------------------
versicolor | setosa | 2.80*** | 2.63, 2.97
virginica | setosa | 4.09*** | 3.92, 4.26
virginica | versicolor | 1.29*** | 1.12, 1.46
Variable predicted: Petal.Length
Predictors contrasted: Species
p-values are uncorrected.
Code
print(estimate_relation(m, by = "qsec"))
Output
Model-based Predictions
qsec | Predicted | SE | 95% CI
---------------------------------------
14.50 | 2.80 | 0.19 | [2.41, 3.18]
15.43 | 2.91 | 0.15 | [2.62, 3.21]
16.37 | 3.03 | 0.11 | [2.81, 3.26]
17.30 | 3.15 | 0.09 | [2.97, 3.32]
18.23 | 3.27 | 0.08 | [3.10, 3.44]
19.17 | 3.38 | 0.10 | [3.17, 3.60]
20.10 | 3.50 | 0.14 | [3.21, 3.78]
21.03 | 3.62 | 0.18 | [3.25, 3.98]
21.97 | 3.73 | 0.22 | [3.28, 4.19]
22.90 | 3.85 | 0.27 | [3.30, 4.40]
Variable predicted: wt
Predictors modulated: qsec
Predictors controlled: mpg (20)
Code
print(estimate_relation(m, by = "qsec"), include_grid = TRUE)
Output
Model-based Predictions
qsec | mpg | Predicted | SE | 95% CI
-----------------------------------------------
14.50 | 20.09 | 2.80 | 0.19 | [2.41, 3.18]
15.43 | 20.09 | 2.91 | 0.15 | [2.62, 3.21]
16.37 | 20.09 | 3.03 | 0.11 | [2.81, 3.26]
17.30 | 20.09 | 3.15 | 0.09 | [2.97, 3.32]
18.23 | 20.09 | 3.27 | 0.08 | [3.10, 3.44]
19.17 | 20.09 | 3.38 | 0.10 | [3.17, 3.60]
20.10 | 20.09 | 3.50 | 0.14 | [3.21, 3.78]
21.03 | 20.09 | 3.62 | 0.18 | [3.25, 3.98]
21.97 | 20.09 | 3.73 | 0.22 | [3.28, 4.19]
22.90 | 20.09 | 3.85 | 0.27 | [3.30, 4.40]
Variable predicted: wt
Predictors modulated: qsec
Predictors controlled: mpg (20)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.