Using marginaleffects, I was trying to
And failed in all! Any help is appreciated.
Df in the end
library(lme4)
library(lmerTest)
library(marginaleffects)
library(dplyr)
import dat_long
dat_long$group <- as.factor(dat_long$group)
dat_long$period <- as.factor(dat_long$period)
dat_long <- dat_long %>%
mutate(group2 = group)
m222 <- lmer(money ~ session + period + group2 + (1 | id2) + (1 | session / date / period), data = dat_long )
summary(m222)
contrasts_periods <- comparisons(
m222,
variables = "period",
include_random = FALSE,
newdata = datagrid(
period = c("p1", "p2", "p3", "p4")
)
)
#2
pred_period <- predictions( m222,
newdata = datagrid(id2 = NA,
period = c("p1", "p2", "p3", "p4"),
include_random = FALSE))
ggplot(pred, aes(x = period, y = predicted,
ymin = conf.low, ymax = conf.high))
#3
pred_session <- predictions( m222,
newdata = datagrid(id2 = NA,
session = seq(from = 16, to = 38, by = 1),
include_random = FALSE))
error codes:
Error: Unable to compute predicted values with this model. You can
try to supply a different dataset to thenewdata
argument. If this does not work, you can file a report on the Github Issue Tracker:
https://github.com/vincentarelbundock/marginaleffects/issues
Error: Unable to compute predicted values with this model. You can try to supply a different dataset to the
newdata
argument. If this does not work, you can file a report on the Github Issue Tracker:
https://github.com/vincentarelbundock/marginaleffects/issuesThis error was also raised: Invalid grouping factor specification, id2 In addition: Warning message: Some of the variable names are missing from the model data: include_random
df below:
dat_long <- structure(list(money = c(22625, 23349, 18189, 16302, 12874, 17343,
15912, 15300, 18762, 23506, 18290, 10296, 13172, 15288, 12462,
16380, 14352, 15052, 14497, 16241, 14832, 14304, 15120, 3745,
15012, 13916, 13056, 12432, 12441, 15762, 10660, 18150, 15496,
16905, 14872, 16166, 15892, 18755, 16241, 16874, 15836, 15225,
32190, 30450, 25200, 19840, 31800, 29892, 10416, 26520, 29029,
28623, 26544, 16988, 22801, 19317, 30694, 20447, 26030, 22378,
27267, 21760, 26334, 26896, 32085, 28914, 26892, 18683, 19468,
16920, 17640, 20829, 17920, 17424, 20538, 21760, 14985, 13407,
13624, 15470, 21252, 15129, 21336, 17760, 22908, 16940, 15860,
17732, 18048, 16002, 18480, 20328, 22848, 19630, 17030, 24220,
16074, 20234, 20413, 20448, 23715, 22010, 24000, 25245, 23088,
16445, 22200, 24786, 20100, 17766, 20022, 22194, 16284, 23560,
16638, 23345, 26788, 21462, 16786, 16362, 22176, 21600, 21744,
21432, 19026, 22330, 20049, 19968, 18876, 20850, 19126, 18788,
19650, 24320, 17100, 22785, 18875, 23520, 21252, 17766, 20304,
19170, 17780, 19296, 15855, 16244, 19875, 18476, 16284, 17780,
14279, 20562, 17556, 17568, 20700, 19750, 22401, 19625, 20264,
18176, 19272, 24180, 21855, 22490, 22560, 19599, 20550, 17856,
20670, 18768, 20385, 17856, 16891, 18081, 18755, 18796, 21450,
18576, 16263, 18460, 16616, 16992, 17250, 18995, 21021, 20368,
17536, 18626, 11742, 15872, 19684, 17250, 15616, 17176, 17653,
17690, 19890, 18054, 17760, 17346, 17316, 17316, 16610, 15428,
19950, 17424, 18720, 18029, 20724, 21574, 21632, 23584, 22059,
17741, 19328, 21120, 18029, 20295, 21679, 19803, 16157, 20250,
21870, 15052, 19782, 21528, 22275, 21285, 17787, 19635, 20768,
19965, 19203, 21666, 23472, 22270, 21528, 14900, 14070, 15120,
18306, 15707, 17810, 18630, 13552, 20691, 18375, 21376, 17732,
16512, 16896, 22410, 22022, 27512, 18796, 26274, 19877, 24462,
29722, 21823, 18834, 23856, 22491, 23055, 26568, 19096, 20944,
21320, 21140, 20124, 17415, 15776, 20034, 20698, 19723, 19845,
22139, 17272, 18720, 23616, 18144, 21312, 20150, 13560, 13560,
15470, 19458, 18944, 19044, 16129, 18354, 23400, 20155, 18161,
19881, 20002, 21060, 20436, 16637, 16968, 15656, 12870, 17767,
17160, 17549, 15696, 18860, 22116, 14602, 20648, 20680, 17549,
19184, 21756, 23718, 24742, 22848, 18511, 23230, 22987, 25480,
26064, 18300, 18161, 18300, 17628, 18720, 24072, 23760, 21672,
20060, 20280, 20482, 18620, 20160, 16764, 15990, 19328, 18125,
18864, 12870, 13899, 16254, 16891, 14742, 16482, 16520, 14278,
16074, 16610, 14848, 16002, 16675, 18850, 14964, 15738, 13254,
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16128, 16124, 16065, 14756, 12432, 15029, 21352, 17810, 19932,
18495, 14720, 22914, 17063, 15645, 20735, 22960, 22925, 19845,
15708, 21942, 27531, 20850, 22475, 22484, 22140, 15260, 21106,
19817, 15360, 18480, 14586, 20433, 20838, 23881, 21679, 17612,
19952, 17856, 23560, 19311, 19728, 18850, 18560, 20139, 15840,
14824, 11210, 19728, 14784, 15065, 22638, 18216, 26219, 22797,
37047, 20687, 22176, 19519, 18492, 13516, 18327, 15616, 16616,
24928, 19840, 20838, 18460, 19176, 17825, 16950, 16786, 23254,
20655, 19352, 22632, 19684, 15312, 16770, 17010, 16464, 17135,
16568, 15494, 18327, 17136, 19221, 16166, 18944, 16541, 15622,
13746, 19720, 16640, 16303, 17690, 15132, 14400, 14060, 14835,
13320, 14322, 13860, 14796, 14946, 14790, 12600, 19460, 16940,
15708, 18176, 16080, 18161, 14260, 18358, 14632, 16482, 19964,
22218, 20139, 19040, 15368, 19880, 17286, 17388, 20424, 17400,
16445, 18760, 16958, 13334, 10608, 5940, 23068, 20300, 20944,
22046, 23256, 19418, 19456, 20328, 20536, 17343, 18161, 18070,
22632, 21624, 22620, 23850, 21840, 20174, 18250, 20172, 15260,
18120, 15038, 18445, 15048, 19456, 20328, 20536, 17343, 15594,
14124, 12862, 16899, 17160, 15080, 12971, 16430, 13356, 12947,
14430, 16764, 17136, 21965, 15729, 18000, 14304, 14214, 19470,
17380, 14688, 17666, 16470, 17334, 14976, 14688, 26196, 25993,
22704, 24639, 19352, 22188, 21924, 18271, 20240, 14874, 16320,
13923, 26989, 24464, 24830, 20320, 21195, 20212, 17168, 18612,
19454, 15510, 25277, 19872, 21033, 20808, 20824, 23250, 16002,
18492, 18900, 20413, 17446, 20124, 24257, 19557, 23919, 25610,
17490, 16157, 17545, 18370, 21357, 23058, 21888, 18796, 22388,
18200, 19140, 21808, 19844, 19530, 21879, 22880, 19239, 22230,
23166, 18871, 17480, 17199, 16874, 24206, 13224, 16905, 11322,
17880, 19536, 13910, 15972, 17145, 16750, 16226, 15972, 14875,
15128, 14756, 15972, 14875, 15128, 14756, 17112, 21312, 19126,
17556, 20276, 17100, 18972, 15429, 17820, 17024, 16641, 17135,
16714, 17324, 14125, 13080, 13189, 16000, 15006, 16740, 16092,
17908, 14626, 14859, 15744, 15113, 17292, 13804, 14541, 15113,
17292, 13804, 14541, 22308, 20736, 17958, 14976, 15410, 14762,
14803, 18900, 17792, 19448, 16872, 17013, 14040, 14840, 16520,
14224, 17908, 13462, 16874, 16675, 14715, 16263, 16440, 14317,
17082, 13764, 17052, 18120, 17442, 12838, 2322, 14637, 14934,
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14803, 14874, 16320, 13923, 19328, 20592, 17152, 21573, 19716,
19800, 17792, 16896, 15128, 16899, 16510, 16375, 15488, 16974,
15151, 17980, 15946, 20856, 21158, 17493, 19539, 19488, 21060,
19840, 18352, 16974, 20034, 18997, 16758, 16046, 20034, 18997,
16758, 16046, 18600, 19939, 18603, 15184, 20829, 19096, 19630,
15012, 21384, 16750, 18029, 15410, 18724, 14580, 13420, 17664,
16206, 1595, 16675, 17822, 16348, 19304, 17136, 17136, 15812,
12648, 20961, 18544, 11748, 14763, 16758, 16046, 11748, 14763,
11660, 17589, 19200, 19588, 20727, 10725, 13870, 17374, 12354,
16214, 22101, 21080, 21525, 20125, 19434, 19800, 20125, 19434,
19800, 21054, 19800, 24250, 20196, 21175, 24790, 18318, 24024,
25004, 20083, 18144, 23976, 26660, 18688, 23520, 20304, 19832,
19360, 18228, 18921, 20800, 21038, 19873, 22468, 17666, 13635
), session = c(34, 34, 34, 17, 17, 19, 19, 19, 21, 21, 21, 24,
24, 24, 24, 25, 25, 25, 25, 26, 26, 26, 26, 27, 27, 27, 27, 33,
33, 33, 33, 35, 35, 35, 35, 36, 36, 36, 36, 37, 37, 37, 18, 19,
19, 19, 21, 21, 21, 23, 24, 24, 24, 24, 26, 26, 27, 27, 27, 34,
34, 34, 36, 36, 38, 38, 38, 17, 17, 17, 18, 18, 18, 21, 21, 21,
22, 22, 22, 23, 23, 23, 25, 25, 25, 25, 26, 26, 26, 27, 27, 27,
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21, 21, 21, 23, 23, 23, 23, 25, 25, 26, 26, 26, 26, 32, 32, 32,
32, 33, 33, 33, 34, 34, 34, 35, 35, 35, 35, 36, 36, 36, 36, 16,
16, 16, 17, 17, 17, 21, 21, 21, 21, 23, 23, 25, 25, 25, 26, 26,
32, 32, 32, 32, 33, 33, 33, 34, 34, 34, 34, 35, 35, 38, 38, 38,
17, 17, 17, 18, 18, 21, 21, 23, 23, 23, 23, 25, 25, 25, 26, 26,
26, 26, 32, 32, 32, 34, 34, 34, 35, 35, 35, 35, 16, 19, 19, 16,
16, 16, 17, 17, 19, 19, 21, 21, 21, 21, 22, 22, 22, 27, 27, 27,
27, 32, 32, 32, 32, 33, 33, 33, 33, 35, 35, 35, 35, 36, 36, 36,
36, 16, 16, 16, 19, 19, 19, 20, 20, 21, 21, 21, 22, 22, 22, 23,
23, 23, 24, 24, 24, 25, 25, 25, 26, 26, 26, 27, 27, 27, 27, 32,
32, 33, 33, 33, 34, 34, 35, 35, 35, 19, 19, 19, 23, 23, 23, 24,
24, 24, 24, 25, 25, 25, 27, 27, 27, 27, 33, 33, 33, 37, 37, 23,
23, 23, 38, 38, 16, 16, 16, 17, 17, 17, 18, 18, 18, 21, 21, 21,
22, 22, 23, 23, 23, 24, 16, 18, 19, 19, 19, 20, 20, 20, 22, 23,
24, 16, 16, 16, 18, 18, 18, 19, 19, 19, 22, 22, 22, 23, 23, 23,
23, 24, 24, 24, 24, 25, 25, 25, 26, 26, 26, 26, 27, 27, 27, 27,
32, 32, 32, 32, 33, 33, 33, 33, 34, 34, 35, 35, 36, 36, 36, 36,
38, 38, 38, 17, 17, 17, 18, 18, 18, 20, 20, 20, 21, 21, 21, 22,
22, 22, 23, 23, 23, 23, 24, 24, 24, 24, 35, 35, 35, 36, 36, 36,
36, 37, 37, 16, 17, 17, 17, 18, 18, 18, 19, 19, 21, 23, 23, 23,
25, 25, 25, 25, 32, 32, 32, 33, 33, 33, 33, 34, 34, 34, 35, 35,
35, 35, 36, 36, 36, 36, 38, 38, 38, 38, 16, 16, 16, 19, 19, 19,
20, 20, 20, 21, 21, 21, 22, 22, 22, 23, 23, 23, 23, 25, 25, 35,
35, 36, 36, 36, 36, 37, 37, 37, 23, 16, 16, 16, 19, 19, 19, 21,
21, 21, 21, 31, 31, 31, 32, 32, 32, 32, 34, 34, 36, 36, 36, 16,
16, 22, 22, 22, 22, 24, 24, 24, 24, 28, 28, 28, 34, 34, 34, 37,
37, 37, 16, 16, 16, 21, 21, 21, 25, 25, 25, 25, 30, 30, 30, 30,
31, 31, 31, 32, 32, 32, 36, 36, 36, 16, 16, 16, 20, 20, 34, 34,
34, 35, 35, 17, 17, 17, 18, 21, 21, 21, 23, 23, 23, 23, 26, 26,
26, 26, 27, 27, 29, 29, 29, 30, 30, 30, 30, 32, 32, 32, 33, 34,
34, 34, 35, 35, 36, 36, 36, 17, 17, 17, 19, 19, 23, 23, 23, 26,
26, 27, 27, 27, 29, 30, 30, 31, 31, 31, 32, 32, 32, 32, 34, 34,
34, 35, 37, 37, 17, 17, 17, 21, 21, 21, 21, 23, 23, 23, 24, 24,
24, 24, 25, 25, 25, 25, 28, 28, 28, 28, 29, 29, 29, 29, 30, 30,
30, 30, 31, 31, 31, 31, 33, 33, 33, 35, 35, 17, 17, 17, 18, 24,
24, 24, 24, 25, 25, 25, 25, 26, 26, 26, 26, 33, 33, 33, 36, 18,
18, 18, 20, 20, 20, 26, 26, 27, 27, 27, 28, 28, 28, 28, 31, 31,
31, 33, 33, 33, 37, 37, 37, 18, 18, 18, 21, 21, 21, 21, 22, 22,
22, 26, 26, 26, 26, 27, 27, 27, 29, 29, 29, 29, 30, 30, 30, 30,
31, 31, 31, 31, 33, 33, 18, 18, 18, 19, 19, 19, 22, 22, 22, 24,
24, 24, 24, 25, 25, 25, 25, 27, 27, 27, 27, 29, 29, 29, 29, 30,
30, 30, 30, 32, 32, 32, 32, 34, 34, 34, 35, 35, 37, 37, 37, 22,
22, 22, 22, 24, 24, 24, 24, 25, 25, 25, 25, 28, 28, 28, 28, 35,
37, 37, 37, 19, 22, 22, 24, 24, 24, 25, 25, 25, 26, 26, 28, 28,
28, 32, 32, 32, 33, 35, 36, 20, 20, 20, 23, 23, 23, 27, 27, 29,
29, 29, 36, 36, 20, 28), period = structure(c(1L, 2L, 4L, 1L,
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2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), levels = c("con", "int"), class = "factor"), id2 = c(1,
1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6,
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7,
7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,
7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8,
8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 14,
14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14,
14, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 16, 16, 16, 16,
16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19,
19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19,
19, 19, 19, 20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21,
21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22,
22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23,
23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26,
26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
27, 27, 27, 27, 27, 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28,
28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29, 29, 29, 29, 29, 29,
29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29,
29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30,
30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30,
30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31,
31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31,
31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 33, 33,
33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33,
33, 33, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 35,
35), date = c(34, 34, 34, 17, 17, 19, 19, 19, 21, 21, 21, 24,
24, 24, 24, 25, 25, 25, 25, 26, 26, 26, 26, 27, 27, 27, 27, 33,
33, 33, 33, 35, 35, 35, 35, 36, 36, 36, 36, 37, 37, 37, 18, 19,
19, 19, 21, 21, 21, 23, 24, 24, 24, 24, 26, 26, 27, 27, 27, 34,
34, 34, 36, 36, 38, 38, 38, 17, 17, 17, 18, 18, 18, 21, 21, 21,
22, 22, 22, 23, 23, 23, 25, 25, 25, 25, 26, 26, 26, 27, 27, 27,
37, 37, 37, 38, 38, 38, 38, 16, 16, 16, 18, 18, 18, 19, 19, 19,
21, 21, 21, 23, 23, 23, 23, 25, 25, 26, 26, 26, 26, 32, 32, 32,
32, 33, 33, 33, 34, 34, 34, 35, 35, 35, 35, 36, 36, 36, 36, 16,
16, 16, 17, 17, 17, 21, 21, 21, 21, 23, 23, 25, 25, 25, 26, 26,
32, 32, 32, 32, 33, 33, 33, 34, 34, 34, 34, 35, 35, 38, 38, 38,
17, 17, 17, 18, 18, 21, 21, 23, 23, 23, 23, 25, 25, 25, 26, 26,
26, 26, 32, 32, 32, 34, 34, 34, 35, 35, 35, 35, 16, 19, 19, 16,
16, 16, 17, 17, 19, 19, 21, 21, 21, 21, 22, 22, 22, 27, 27, 27,
27, 32, 32, 32, 32, 33, 33, 33, 33, 35, 35, 35, 35, 36, 36, 36,
36, 16, 16, 16, 19, 19, 19, 20, 20, 21, 21, 21, 22, 22, 22, 23,
23, 23, 24, 24, 24, 25, 25, 25, 26, 26, 26, 27, 27, 27, 27, 32,
32, 33, 33, 33, 34, 34, 35, 35, 35, 19, 19, 19, 23, 23, 23, 24,
24, 24, 24, 25, 25, 25, 27, 27, 27, 27, 33, 33, 33, 37, 37, 23,
23, 23, 38, 38, 16, 16, 16, 17, 17, 17, 18, 18, 18, 21, 21, 21,
22, 22, 23, 23, 23, 24, 16, 18, 19, 19, 19, 20, 20, 20, 22, 23,
24, 16, 16, 16, 18, 18, 18, 19, 19, 19, 22, 22, 22, 23, 23, 23,
23, 24, 24, 24, 24, 25, 25, 25, 26, 26, 26, 26, 27, 27, 27, 27,
32, 32, 32, 32, 33, 33, 33, 33, 34, 34, 35, 35, 36, 36, 36, 36,
38, 38, 38, 17, 17, 17, 18, 18, 18, 20, 20, 20, 21, 21, 21, 22,
22, 22, 23, 23, 23, 23, 24, 24, 24, 24, 35, 35, 35, 36, 36, 36,
36, 37, 37, 16, 17, 17, 17, 18, 18, 18, 19, 19, 21, 23, 23, 23,
25, 25, 25, 25, 32, 32, 32, 33, 33, 33, 33, 34, 34, 34, 35, 35,
35, 35, 36, 36, 36, 36, 38, 38, 38, 38, 16, 16, 16, 19, 19, 19,
20, 20, 20, 21, 21, 21, 22, 22, 22, 23, 23, 23, 23, 25, 25, 35,
35, 36, 36, 36, 36, 37, 37, 37, 23, 32, 32, 32, 38, 38, 38, 42,
42, 42, 42, 62, 62, 62, 64, 64, 64, 64, 68, 68, 72, 72, 72, 32,
32, 44, 44, 44, 44, 48, 48, 48, 48, 56, 56, 56, 68, 68, 68, 74,
74, 74, 32, 32, 32, 42, 42, 42, 50, 50, 50, 50, 60, 60, 60, 60,
62, 62, 62, 64, 64, 64, 72, 72, 72, 32, 32, 32, 40, 40, 68, 68,
68, 70, 70, 34, 34, 34, 36, 42, 42, 42, 46, 46, 46, 46, 52, 52,
52, 52, 54, 54, 58, 58, 58, 60, 60, 60, 60, 64, 64, 64, 66, 68,
68, 68, 70, 70, 72, 72, 72, 34, 34, 34, 38, 38, 46, 46, 46, 52,
52, 54, 54, 54, 58, 60, 60, 62, 62, 62, 64, 64, 64, 64, 68, 68,
68, 70, 74, 74, 34, 34, 34, 42, 42, 42, 42, 46, 46, 46, 48, 48,
48, 48, 50, 50, 50, 50, 56, 56, 56, 56, 58, 58, 58, 58, 60, 60,
60, 60, 62, 62, 62, 62, 66, 66, 66, 70, 70, 34, 34, 34, 36, 48,
48, 48, 48, 50, 50, 50, 50, 52, 52, 52, 52, 66, 66, 66, 72, 36,
36, 36, 40, 40, 40, 52, 52, 54, 54, 54, 56, 56, 56, 56, 62, 62,
62, 66, 66, 66, 74, 74, 74, 36, 36, 36, 42, 42, 42, 42, 44, 44,
44, 52, 52, 52, 52, 54, 54, 54, 58, 58, 58, 58, 60, 60, 60, 60,
62, 62, 62, 62, 66, 66, 36, 36, 36, 38, 38, 38, 44, 44, 44, 48,
48, 48, 48, 50, 50, 50, 50, 54, 54, 54, 54, 58, 58, 58, 58, 60,
60, 60, 60, 64, 64, 64, 64, 68, 68, 68, 70, 70, 74, 74, 74, 44,
44, 44, 44, 48, 48, 48, 48, 50, 50, 50, 50, 56, 56, 56, 56, 70,
74, 74, 74, 38, 44, 44, 48, 48, 48, 50, 50, 50, 52, 52, 56, 56,
56, 64, 64, 64, 66, 70, 72, 40, 40, 40, 46, 46, 46, 54, 54, 58,
58, 58, 72, 72, 40, 56)), row.names = c(NA, -834L), class = c("tbl_df",
"tbl", "data.frame"))
This answer uses the development version (0.9.0.9043) of marginaleffects
, which you can install by following the instructions here: https://vincentarelbundock.github.io/marginaleffects/
Please note that the extra lme4
-related arguments must be supplied to the predictions()
function, and not to the datagrid()
function as you do in your second example.
Also, I strongly suggest you avoid include_random
and use the default arguments supplied by the lme4
modelling package itself (via predict.merMod
). In this case: re.form
and allow.new.levels
.
library(lme4)
library(lmerTest)
library(marginaleffects)
library(dplyr)
dat_long$group <- as.factor(dat_long$group)
dat_long$period <- as.factor(dat_long$period)
dat_long <- dat_long %>% mutate(group2 = group)
m222 <- lmer(money ~ session + period + group2 + (1 | id2) + (1 | session / date / period), data = dat_long )
comparisons(
m222,
variables = "period",
re.form = NA,
newdata = datagrid(period = c("p1", "p2", "p3", "p4")))
#
# Term Contrast Estimate Std. Error z Pr(>|z|) 2.5 % 97.5 % session group2 id2 date
# period p2 - p1 -361.6 260.0 -1.391 0.1643688 -871.3 148.1 23 int 16 37.90168
# period p2 - p1 -361.6 260.0 -1.391 0.1643688 -871.3 148.1 23 int 16 37.90168
# period p2 - p1 -361.6 260.0 -1.391 0.1643688 -871.3 148.1 23 int 16 37.90168
# period p2 - p1 -361.6 260.0 -1.391 0.1643688 -871.3 148.1 23 int 16 37.90168
# period p3 - p1 -745.6 260.0 -2.868 0.0041366 -1255.3 -236.0 23 int 16 37.90168
# period p3 - p1 -745.6 260.0 -2.868 0.0041366 -1255.3 -236.0 23 int 16 37.90168
# period p3 - p1 -745.6 260.0 -2.868 0.0041366 -1255.3 -236.0 23 int 16 37.90168
# period p3 - p1 -745.6 260.0 -2.868 0.0041366 -1255.3 -236.0 23 int 16 37.90168
# period p4 - p1 -1371.6 318.4 -4.308 1.6492e-05 -1995.6 -747.5 23 int 16 37.90168
# period p4 - p1 -1371.6 318.4 -4.308 1.6492e-05 -1995.6 -747.5 23 int 16 37.90168
# period p4 - p1 -1371.6 318.4 -4.308 1.6492e-05 -1995.6 -747.5 23 int 16 37.90168
# period p4 - p1 -1371.6 318.4 -4.308 1.6492e-05 -1995.6 -747.5 23 int 16 37.90168
#
# Prediction type: response
# Columns: rowid, type, term, contrast, estimate, std.error, statistic, p.value, conf.low, conf.high, predicted, predicted_hi, predicted_lo, money, session, group2, id2, date, period
predictions(
m222,
newdata = datagrid(
id2 = NA,
session = seq(from = 16, to = 38, by = 1)),
re.form = NA,
allow.new.levels = TRUE)
#
# Estimate Std. Error z Pr(>|z|) 2.5 % 97.5 % period group2 date id2 session
# 19654 656.1 29.96 < 2.22e-16 18368 20940 p1 int 37.90168 NA 16
# 19649 647.4 30.35 < 2.22e-16 18380 20917 p1 int 37.90168 NA 17
# 19643 639.5 30.72 < 2.22e-16 18390 20896 p1 int 37.90168 NA 18
# 19637 632.5 31.05 < 2.22e-16 18398 20877 p1 int 37.90168 NA 19
# 19632 626.2 31.35 < 2.22e-16 18404 20859 p1 int 37.90168 NA 20
# 19626 620.9 31.61 < 2.22e-16 18409 20843 p1 int 37.90168 NA 21
# 19621 616.5 31.83 < 2.22e-16 18412 20829 p1 int 37.90168 NA 22
# 19615 613.0 32.00 < 2.22e-16 18414 20817 p1 int 37.90168 NA 23
# 19610 610.5 32.12 < 2.22e-16 18413 20806 p1 int 37.90168 NA 24
# 19604 608.9 32.20 < 2.22e-16 18411 20798 p1 int 37.90168 NA 25
# 19599 608.2 32.22 < 2.22e-16 18406 20791 p1 int 37.90168 NA 26
# 19593 608.6 32.19 < 2.22e-16 18400 20786 p1 int 37.90168 NA 27
# 19587 609.9 32.12 < 2.22e-16 18392 20783 p1 int 37.90168 NA 28
# 19582 612.1 31.99 < 2.22e-16 18382 20782 p1 int 37.90168 NA 29
# 19576 615.3 31.82 < 2.22e-16 18370 20782 p1 int 37.90168 NA 30
# 19571 619.4 31.60 < 2.22e-16 18357 20785 p1 int 37.90168 NA 31
# 19565 624.4 31.33 < 2.22e-16 18341 20789 p1 int 37.90168 NA 32
# 19560 630.4 31.03 < 2.22e-16 18324 20795 p1 int 37.90168 NA 33
# 19554 637.1 30.69 < 2.22e-16 18305 20803 p1 int 37.90168 NA 34
# 19549 644.8 30.32 < 2.22e-16 18285 20812 p1 int 37.90168 NA 35
# 19543 653.2 29.92 < 2.22e-16 18263 20823 p1 int 37.90168 NA 36
# 19538 662.4 29.49 < 2.22e-16 18239 20836 p1 int 37.90168 NA 37
# 19532 672.4 29.05 < 2.22e-16 18214 20850 p1 int 37.90168 NA 38
#
# Prediction type: response
# Columns: rowid, type, estimate, std.error, statistic, p.value, conf.low, conf.high, money, period, group2, date, id2, session