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add tests
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strengejacke committed Jan 19, 2025
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15 changes: 13 additions & 2 deletions R/format.R
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Original file line number Diff line number Diff line change
Expand Up @@ -248,7 +248,13 @@ format.marginaleffects_contrasts <- function(x, model, p_adjust, comparison, ...
# dash / minus as separator char. The column name is the name of the
# contrast term.
if (length(contrast) == 1) {
colnames(params) <- c("Level1", "Level2")
# rename columns
params <- datawizard::data_rename(
params,
select = paste0(contrast, 1:2),
replacement = c("Level1", "Level2"),
verbose = FALSE
)
} else {
# if we have more than one contrast term, we unite the levels from
# all contrast terms that belong to one "contrast group", separated
Expand Down Expand Up @@ -301,7 +307,12 @@ format.marginaleffects_contrasts <- function(x, model, p_adjust, comparison, ...
# column name back, so we can properly merge all variables in
# "contrast" and "by" to the original data
by_columns <- paste0(by, 1)
params <- datawizard::data_rename(params, select = by_columns, replacement = by, verbose = FALSE)
params <- datawizard::data_rename(
params,
select = by_columns,
replacement = by,
verbose = FALSE
)

# filter original data and new params by "by"
x <- x[keep_rows, ]
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255 changes: 255 additions & 0 deletions tests/testthat/_snaps/estimate_contrasts.md
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Original file line number Diff line number Diff line change
Expand Up @@ -326,6 +326,107 @@
Predictors averaged: e16sex
p-values are uncorrected.

---

Code
print(estimate_contrasts(fit, "c161sex", "c172code", backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | c172code | Difference | SE | 95% CI | t(825) | p
-------------------------------------------------------------------------------
Male | Female | low | -1.05 | 0.69 | [-2.40, 0.31] | -1.51 | 0.131
Male | Female | mid | -0.56 | 0.42 | [-1.38, 0.26] | -1.35 | 0.178
Male | Female | high | -0.96 | 0.69 | [-2.30, 0.39] | -1.40 | 0.163
Variable predicted: neg_c_7
Predictors contrasted: c161sex
Predictors averaged: e16sex
p-values are uncorrected.

---

Code
print(estimate_slopes(fit, "barthtot", backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Estimated Marginal Effects
Slope | SE | 95% CI | t | p
-----------------------------------------------
-0.05 | 0.00 | [-0.06, -0.05] | -12.77 | < .001
Marginal effects estimated for barthtot
Type of slope was dY/dX

---

Code
print(estimate_slopes(fit, "barthtot", by = "c172code", backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Estimated Marginal Effects
c172code | Slope | SE | 95% CI | t | p
---------------------------------------------------------
low | -0.06 | 0.01 | [-0.08, -0.05] | -7.08 | < .001
mid | -0.05 | 0.01 | [-0.06, -0.04] | -9.82 | < .001
high | -0.05 | 0.01 | [-0.07, -0.03] | -4.51 | < .001
Marginal effects estimated for barthtot
Type of slope was dY/dX

---

Code
print(estimate_contrasts(fit, "barthtot", "c172code", backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t | p
-------------------------------------------------------------------
low | mid | -0.01 | 0.01 | [-0.03, 0.01] | -1.17 | 0.243
low | high | -0.02 | 0.01 | [-0.04, 0.01] | -1.10 | 0.271
mid | high | 0.00 | 0.01 | [-0.03, 0.02] | -0.27 | 0.786
Variable predicted: neg_c_7
Predictors contrasted: barthtot
Predictors averaged: e16sex, barthtot
p-values are uncorrected.

---

Code
print(estimate_contrasts(fit, "barthtot", c("c172code", "e16sex"), backend = "marginaleffects"),
table_width = Inf, zap_small = TRUE)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t | p
-------------------------------------------------------------------------------
low, male | low, female | 0.01 | 0.02 | [-0.03, 0.04] | 0.35 | 0.729
low, male | mid, male | 0.01 | 0.02 | [-0.02, 0.04] | 0.46 | 0.648
low, male | mid, female | -0.02 | 0.01 | [-0.05, 0.01] | -1.24 | 0.216
low, male | high, male | 0.00 | 0.02 | [-0.04, 0.05] | 0.16 | 0.876
low, male | high, female | -0.02 | 0.02 | [-0.06, 0.01] | -1.19 | 0.236
low, female | mid, male | 0.00 | 0.02 | [-0.03, 0.03] | 0.08 | 0.940
low, female | mid, female | -0.02 | 0.01 | [-0.05, 0.00] | -1.76 | 0.079
low, female | high, male | 0.00 | 0.02 | [-0.05, 0.04] | -0.12 | 0.908
low, female | high, female | -0.03 | 0.02 | [-0.06, 0.01] | -1.58 | 0.115
mid, male | mid, female | -0.03 | 0.01 | [-0.05, 0.00] | -2.24 | 0.025
mid, male | high, male | 0.00 | 0.02 | [-0.05, 0.04] | -0.18 | 0.859
mid, male | high, female | -0.03 | 0.02 | [-0.06, 0.00] | -1.83 | 0.067
mid, female | high, male | 0.02 | 0.02 | [-0.02, 0.06] | 1.08 | 0.280
mid, female | high, female | 0.00 | 0.01 | [-0.03, 0.02] | -0.26 | 0.792
high, male | high, female | -0.03 | 0.02 | [-0.07, 0.02] | -1.11 | 0.268
Variable predicted: neg_c_7
Predictors contrasted: barthtot
Predictors averaged: barthtot
p-values are uncorrected.

# estimate_contrasts - simple contrasts and with - in levels works

Code
Expand Down Expand Up @@ -376,3 +477,157 @@
Predictors averaged: sex
p-values are uncorrected.

---

Code
print(estimate_contrasts(m, contrast = "time", by = "coffee", backend = "marginaleffects"),
zap_small = TRUE, table_width = Inf)
Output
Marginal Contrasts Analysis
Level1 | Level2 | coffee | Difference | SE | 95% CI | t(113) | p
------------------------------------------------------------------------------------
morning | noon | coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336
morning | afternoon | coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336
morning | noon | control | -5.78 | 1.99 | [-9.73, -1.83] | -2.90 | 0.004
morning | afternoon | control | -5.78 | 1.99 | [-9.73, -1.83] | -2.90 | 0.004
noon | afternoon | coffee | -3.86 | 1.99 | [-7.81, 0.09] | -1.93 | 0.056
noon | afternoon | control | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999
Variable predicted: alertness
Predictors contrasted: time
Predictors averaged: sex
p-values are uncorrected.

---

Code
print(estimate_contrasts(model, contrast = c("mined", "spp"), backend = "marginaleffects"),
zap_small = TRUE, table_width = Inf)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | z | p
-----------------------------------------------------------------------------
yes, GP | yes, PR | -0.06 | 0.05 | [-0.16, 0.04] | -1.10 | 0.271
yes, GP | yes, DM | -0.32 | 0.11 | [-0.54, -0.10] | -2.89 | 0.004
yes, GP | yes, EC-A | -0.04 | 0.05 | [-0.13, 0.05] | -0.80 | 0.421
yes, GP | yes, EC-L | -0.17 | 0.08 | [-0.32, -0.02] | -2.19 | 0.028
yes, GP | yes, DES-L | -0.43 | 0.14 | [-0.70, -0.17] | -3.19 | 0.001
yes, GP | yes, DF | -0.43 | 0.14 | [-0.70, -0.17] | -3.19 | 0.001
yes, GP | no, GP | -2.59 | 0.55 | [-3.67, -1.50] | -4.67 | < .001
yes, GP | no, PR | -0.51 | 0.16 | [-0.82, -0.20] | -3.21 | 0.001
yes, GP | no, DM | -2.86 | 0.61 | [-4.05, -1.68] | -4.73 | < .001
yes, GP | no, EC-A | -1.10 | 0.27 | [-1.64, -0.57] | -4.03 | < .001
yes, GP | no, EC-L | -4.67 | 0.94 | [-6.52, -2.82] | -4.95 | < .001
yes, GP | no, DES-L | -4.62 | 0.93 | [-6.45, -2.79] | -4.95 | < .001
yes, GP | no, DF | -2.24 | 0.49 | [-3.20, -1.28] | -4.58 | < .001
yes, PR | yes, DM | -0.26 | 0.11 | [-0.48, -0.05] | -2.43 | 0.015
yes, PR | yes, EC-A | 0.02 | 0.06 | [-0.09, 0.13] | 0.33 | 0.740
yes, PR | yes, EC-L | -0.11 | 0.08 | [-0.27, 0.04] | -1.43 | 0.154
yes, PR | yes, DES-L | -0.38 | 0.13 | [-0.64, -0.12] | -2.86 | 0.004
yes, PR | yes, DF | -0.38 | 0.13 | [-0.64, -0.12] | -2.86 | 0.004
yes, PR | no, GP | -2.53 | 0.56 | [-3.62, -1.44] | -4.54 | < .001
yes, PR | no, PR | -0.45 | 0.16 | [-0.77, -0.13] | -2.75 | 0.006
yes, PR | no, DM | -2.80 | 0.61 | [-4.00, -1.61] | -4.61 | < .001
yes, PR | no, EC-A | -1.05 | 0.28 | [-1.59, -0.50] | -3.76 | < .001
yes, PR | no, EC-L | -4.61 | 0.95 | [-6.47, -2.76] | -4.87 | < .001
yes, PR | no, DES-L | -4.56 | 0.94 | [-6.40, -2.73] | -4.87 | < .001
yes, PR | no, DF | -2.18 | 0.49 | [-3.15, -1.22] | -4.44 | < .001
yes, DM | yes, EC-A | 0.28 | 0.11 | [ 0.07, 0.50] | 2.59 | 0.010
yes, DM | yes, EC-L | 0.15 | 0.11 | [-0.06, 0.36] | 1.39 | 0.164
yes, DM | yes, DES-L | -0.11 | 0.13 | [-0.36, 0.14] | -0.89 | 0.375
yes, DM | yes, DF | -0.11 | 0.13 | [-0.36, 0.14] | -0.89 | 0.375
yes, DM | no, GP | -2.27 | 0.58 | [-3.40, -1.14] | -3.93 | < .001
yes, DM | no, PR | -0.19 | 0.20 | [-0.58, 0.21] | -0.93 | 0.352
yes, DM | no, DM | -2.54 | 0.63 | [-3.77, -1.31] | -4.04 | < .001
yes, DM | no, EC-A | -0.78 | 0.31 | [-1.38, -0.18] | -2.56 | 0.011
yes, DM | no, EC-L | -4.35 | 0.96 | [-6.24, -2.46] | -4.51 | < .001
yes, DM | no, DES-L | -4.30 | 0.95 | [-6.17, -2.43] | -4.51 | < .001
yes, DM | no, DF | -1.92 | 0.51 | [-2.93, -0.91] | -3.74 | < .001
yes, EC-A | yes, EC-L | -0.13 | 0.08 | [-0.29, 0.02] | -1.68 | 0.093
yes, EC-A | yes, DES-L | -0.40 | 0.13 | [-0.66, -0.14] | -2.97 | 0.003
yes, EC-A | yes, DF | -0.40 | 0.13 | [-0.66, -0.14] | -2.97 | 0.003
yes, EC-A | no, GP | -2.55 | 0.56 | [-3.64, -1.46] | -4.58 | < .001
yes, EC-A | no, PR | -0.47 | 0.16 | [-0.79, -0.15] | -2.90 | 0.004
yes, EC-A | no, DM | -2.82 | 0.61 | [-4.01, -1.63] | -4.65 | < .001
yes, EC-A | no, EC-A | -1.06 | 0.28 | [-1.61, -0.52] | -3.85 | < .001
yes, EC-A | no, EC-L | -4.63 | 0.95 | [-6.48, -2.78] | -4.90 | < .001
yes, EC-A | no, DES-L | -4.58 | 0.94 | [-6.42, -2.75] | -4.90 | < .001
yes, EC-A | no, DF | -2.20 | 0.49 | [-3.17, -1.24] | -4.49 | < .001
yes, EC-L | yes, DES-L | -0.26 | 0.13 | [-0.51, -0.02] | -2.08 | 0.037
yes, EC-L | yes, DF | -0.26 | 0.13 | [-0.51, -0.02] | -2.08 | 0.037
yes, EC-L | no, GP | -2.42 | 0.57 | [-3.53, -1.31] | -4.28 | < .001
yes, EC-L | no, PR | -0.34 | 0.18 | [-0.69, 0.01] | -1.89 | 0.058
yes, EC-L | no, DM | -2.69 | 0.62 | [-3.90, -1.48] | -4.37 | < .001
yes, EC-L | no, EC-A | -0.93 | 0.29 | [-1.50, -0.37] | -3.23 | 0.001
yes, EC-L | no, EC-L | -4.50 | 0.95 | [-6.37, -2.63] | -4.72 | < .001
yes, EC-L | no, DES-L | -4.45 | 0.94 | [-6.30, -2.60] | -4.71 | < .001
yes, EC-L | no, DF | -2.07 | 0.50 | [-3.05, -1.09] | -4.14 | < .001
yes, DES-L | yes, DF | 0.00 | 0.13 | [-0.26, 0.26] | 0.00 | > .999
yes, DES-L | no, GP | -2.15 | 0.59 | [-3.31, -1.00] | -3.67 | < .001
yes, DES-L | no, PR | -0.07 | 0.22 | [-0.50, 0.36] | -0.33 | 0.738
yes, DES-L | no, DM | -2.43 | 0.64 | [-3.68, -1.18] | -3.81 | < .001
yes, DES-L | no, EC-A | -0.67 | 0.32 | [-1.29, -0.04] | -2.09 | 0.037
yes, DES-L | no, EC-L | -4.24 | 0.97 | [-6.14, -2.33] | -4.36 | < .001
yes, DES-L | no, DES-L | -4.19 | 0.96 | [-6.07, -2.30] | -4.35 | < .001
yes, DES-L | no, DF | -1.81 | 0.52 | [-2.83, -0.78] | -3.45 | < .001
yes, DF | no, GP | -2.15 | 0.59 | [-3.31, -1.00] | -3.67 | < .001
yes, DF | no, PR | -0.07 | 0.22 | [-0.50, 0.36] | -0.33 | 0.738
yes, DF | no, DM | -2.43 | 0.64 | [-3.68, -1.18] | -3.81 | < .001
yes, DF | no, EC-A | -0.67 | 0.32 | [-1.29, -0.04] | -2.09 | 0.037
yes, DF | no, EC-L | -4.24 | 0.97 | [-6.14, -2.33] | -4.36 | < .001
yes, DF | no, DES-L | -4.19 | 0.96 | [-6.07, -2.30] | -4.35 | < .001
yes, DF | no, DF | -1.81 | 0.52 | [-2.83, -0.78] | -3.45 | < .001
no, GP | no, PR | 2.08 | 0.48 | [ 1.14, 3.02] | 4.35 | < .001
no, GP | no, DM | -0.27 | 0.37 | [-1.00, 0.46] | -0.73 | 0.466
no, GP | no, EC-A | 1.49 | 0.41 | [ 0.68, 2.29] | 3.61 | < .001
no, GP | no, EC-L | -2.08 | 0.58 | [-3.21, -0.95] | -3.61 | < .001
no, GP | no, DES-L | -2.03 | 0.57 | [-3.15, -0.92] | -3.57 | < .001
no, GP | no, DF | 0.35 | 0.35 | [-0.35, 1.04] | 0.98 | 0.328
no, PR | no, DM | -2.35 | 0.53 | [-3.39, -1.32] | -4.47 | < .001
no, PR | no, EC-A | -0.59 | 0.23 | [-1.05, -0.14] | -2.56 | 0.011
no, PR | no, EC-L | -4.16 | 0.86 | [-5.84, -2.49] | -4.87 | < .001
no, PR | no, DES-L | -4.11 | 0.85 | [-5.77, -2.45] | -4.86 | < .001
no, PR | no, DF | -1.73 | 0.42 | [-2.55, -0.92] | -4.15 | < .001
no, DM | no, EC-A | 1.76 | 0.46 | [ 0.87, 2.65] | 3.86 | < .001
no, DM | no, EC-L | -1.81 | 0.55 | [-2.89, -0.73] | -3.29 | < .001
no, DM | no, DES-L | -1.76 | 0.54 | [-2.82, -0.70] | -3.24 | 0.001
no, DM | no, DF | 0.62 | 0.38 | [-0.12, 1.36] | 1.65 | 0.100
no, EC-A | no, EC-L | -3.57 | 0.77 | [-5.07, -2.07] | -4.66 | < .001
no, EC-A | no, DES-L | -3.52 | 0.76 | [-5.00, -2.03] | -4.65 | < .001
no, EC-A | no, DF | -1.14 | 0.36 | [-1.85, -0.43] | -3.16 | 0.002
no, EC-L | no, DES-L | 0.05 | 0.48 | [-0.89, 0.99] | 0.10 | 0.918
no, EC-L | no, DF | 2.43 | 0.61 | [ 1.22, 3.63] | 3.95 | < .001
no, DES-L | no, DF | 2.38 | 0.61 | [ 1.19, 3.57] | 3.92 | < .001
Variable predicted: count
Predictors contrasted: mined, spp
Predictors averaged: cover, site
p-values are uncorrected.
Contrasts are on the response-scale.

---

Code
print(estimate_contrasts(model, contrast = "mined", by = "spp", backend = "marginaleffects"),
zap_small = TRUE, table_width = Inf)
Output
Marginal Contrasts Analysis
Level1 | Level2 | spp | Difference | SE | 95% CI | z | p
-----------------------------------------------------------------------------
yes | no | GP | -2.59 | 0.55 | [-3.67, -1.50] | -4.67 | < .001
yes | no | PR | -0.45 | 0.16 | [-0.77, -0.13] | -2.75 | 0.006
yes | no | DM | -2.54 | 0.63 | [-3.77, -1.31] | -4.04 | < .001
yes | no | EC-A | -1.06 | 0.28 | [-1.61, -0.52] | -3.85 | < .001
yes | no | EC-L | -4.50 | 0.95 | [-6.37, -2.63] | -4.72 | < .001
yes | no | DES-L | -4.19 | 0.96 | [-6.07, -2.30] | -4.35 | < .001
yes | no | DF | -1.81 | 0.52 | [-2.83, -0.78] | -3.45 | < .001
Variable predicted: count
Predictors contrasted: mined
Predictors averaged: cover, site
p-values are uncorrected.
Contrasts are on the response-scale.

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