Plotting conditional effects from a fitted brms ordinal probit model: two categorical predictors

tidyverse
,
21

Yes, close enough. Again, thank you for your help. Much appreciated.

22

Hi, made a slight adjustment to my dataset (renamed S to C) and fitted the data in a new model. But the dots always land at the same level and I can't figure out what's wrong.

dput(conditional_merged) yields the below code.

structure(list(T = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L), levels = c("TA", "TB", "TC"), class = "factor"), Y = c(4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111
), C = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), levels = c("CI", 
"CJ", "CK", "CL", "CM"), class = "factor"), id = c(NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA), Item = c(NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA), cond__ = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L), levels = c("CI", "CJ", "CK", "CL", "CM"), class = "factor"), 
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    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), levels = c("TA", 
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    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L), levels = c("TA", "TB", "TC"), class = "factor"), 
    resp__ = c(7L, 3L, 4L, 7L, 7L, 7L, 6L, 7L, 2L, 7L, 7L, 6L, 
    6L, 4L, 3L, 7L, 3L, 4L, 7L, 5L, 5L, 7L, 3L, 5L, 3L, 6L, 3L, 
    2L, 3L, 3L, 6L, 3L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 7L, 
    7L, 7L, 7L, 6L, 6L, 6L, 7L, 7L, 6L, 7L, 1L, 7L, 4L, 7L, 7L, 
    7L, 3L, 4L, 7L, 6L, 7L, 6L, 7L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 
    7L, 7L, 5L, 3L, 6L, 7L, 7L, 4L, 3L, 6L, 6L, 7L, 7L, 6L, 6L, 
    6L, 4L, 7L, 6L, 6L, 5L, 6L, 7L, 6L, 7L, 7L, 6L, 6L, 6L, 6L, 
    7L, 2L, 7L, 7L, 4L, 7L, 7L, 6L, 7L, 7L, 5L, 7L, 7L, 1L, 6L, 
    6L, 7L, 7L, 5L, 6L, 4L, 5L, 6L, 6L, 7L, 6L, 7L, 6L, 6L, 7L, 
    6L, 6L, 6L, 5L, 7L, 6L, 7L, 6L, 7L, 4L, 7L, 6L, 3L, 6L, 6L, 
    7L, 6L, 5L, 3L, 4L, 5L, 6L, 6L, 6L, 4L, 3L, 4L, 6L, 7L, 6L, 
    4L, 7L, 6L, 6L, 6L, 6L, 6L, 7L, 5L, 6L, 5L, 6L, 7L, 5L, 7L, 
    6L, 6L, 5L, 6L, 6L, 4L, 5L, 7L, 5L, 7L, 6L, 6L, 5L, 7L, 5L, 
    7L, 5L, 6L, 3L, 7L, 5L, 7L, 5L, 6L, 6L, 5L, 7L, 4L, 6L, 5L, 
    7L, 5L, 7L, 5L, 6L, 5L, 6L, 5L, 6L, 7L, 6L, 6L, 3L, 5L, 6L, 
    3L, 5L, 6L, 6L, 6L, 5L, 7L, 6L, 6L, 3L, 6L, 7L, 7L, 6L, 6L, 
    6L, 6L, 6L, 7L, 7L, 7L, 7L, 6L, 5L, 5L, 4L, 6L, 2L, 5L, 4L, 
    3L, 4L, 5L, 6L, 5L, 7L, 7L, 6L, 3L, 6L, 7L, 7L, 7L, 5L, 7L, 
    6L, 7L, 7L, 6L, 6L, 7L, 7L, 7L, 6L, 6L, 7L, 7L, 6L, 7L, 2L, 
    7L, 7L, 7L, 6L, 6L, 5L, 5L, 3L, 7L, 6L, 6L, 6L, 7L, 7L, 3L, 
    7L, 7L, 6L, 5L, 7L, 7L, 7L, 5L, 6L, 7L, 1L, 6L, 5L, 7L, 7L, 
    6L, 6L, 6L, 7L, 3L, 6L, 6L, 6L, 7L, 5L, 7L, 7L, 7L, 6L, 4L, 
    7L, 7L, 7L, 4L, 7L, 5L, 7L, 6L, 7L, 2L, 1L, 7L, 6L, 5L, 4L, 
    1L, 7L, 3L, 6L, 5L, 7L, 7L, 4L, 7L, 6L, 7L, 6L, 3L, 4L, 6L, 
    7L, 1L, 7L), cond__ = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    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 = "CI", class = "factor"), 
    effect1__ = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L), levels = c("TA", "TB", "TC"), class = "factor")), row.names = c(NA, 
360L), class = "data.frame"), class = "data.frame")

Would there be anything else that I would need to change in the code you provided?

Thanks again for your help.

Best,
Dan

23

The data in the new C column doesn't match what's in the old S column of the rdatLong table you shared above, so the join won't work for folks here. Did you change that table, too?

24

I changed the name of the factor levels, CI, CJ, CK, CL, CM. And for T to TA, TB and TC.

The model was changed to include unequal variance. Other than that it should be the same output.

Best,
D

Den 26 aug. 2024 kl 20:01, David Romano via Posit Community <[noreply@forum.posit.co](mailto:Den 26 aug. 2024 kl 20:01, David Romano via Posit Community < skrev:

25

Could you say how the new factor levels relate to the old one?

26

CI = Sw, CJ = UK, CK = Ge, CL = Br, CM = Th
TA = Parental, TB = Married, TC = Citizen

Thanks!

27

This is what I get:

original `rdatLong` and new `conditional_merged` tables 
rdatLong <- 
structure(list(T = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L), levels = c("Citizen", "Married", "Parental"), class = "factor"), 
    Item = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
    8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
    8L, 8L, 8L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L), G = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 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, 2L, 2L, 2L, 2L, 2L, 2L, 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, 2L, 2L, 2L, 2L, 2L, 2L, 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, 2L, 2L, 2L, 2L, 2L, 2L, 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, 2L, 2L, 2L, 2L, 2L, 2L, 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), levels = c("F", "M"), class = "factor"), 
    Ind = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
    13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 
    25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
    8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
    20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L, 
    2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
    15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 
    27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
    11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
    23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 
    6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
    19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
    1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
    15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 
    27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
    11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
    23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 
    6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
    19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
    1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 
    15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 
    27L, 28L, 29L, 30L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
    11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
    23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L), S = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), levels = c("Sw", 
    "UK", "Ge", "Br", "Th"), class = "factor"), Y = c(6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 6L, 6L, 
    6L, 5L, 6L, 6L, 6L, 6L, 5L, 6L, 6L, 5L, 6L, 6L, 5L, 6L, 6L, 
    6L, 6L, 6L, 7L, 6L, 7L, 6L, 6L, 5L, 6L, 6L, 6L, 7L, 6L, 6L, 
    6L, 7L, 6L, 6L, 6L, 7L, 6L, 5L, 6L, 7L, 6L, 6L, 7L, 5L, 3L, 
    5L, 5L, 6L, 7L, 7L, 6L, 7L, 7L, 6L, 6L, 7L, 6L, 6L, 7L, 6L, 
    6L, 6L, 6L, 4L, 5L, 6L, 6L, 7L, 6L, 6L, 5L, 7L, 7L, 6L, 6L, 
    4L, 6L, 6L, 4L, 7L, 4L, 7L, 6L, 6L, 7L, 7L, 7L, 5L, 7L, 6L, 
    7L, 7L, 7L, 7L, 4L, 6L, 4L, 7L, 6L, 6L, 7L, 6L, 6L, 5L, 6L, 
    6L, 7L, 2L, 5L, 7L, 5L, 6L, 3L, 6L, 7L, 7L, 7L, 6L, 7L, 6L, 
    6L, 7L, 6L, 7L, 7L, 3L, 6L, 7L, 7L, 7L, 7L, 7L, 4L, 7L, 7L, 
    7L, 7L, 6L, 5L, 7L, 6L, 7L, 6L, 5L, 1L, 4L, 7L, 7L, 7L, 7L, 
    7L, 1L, 7L, 7L, 7L, 5L, 6L, 7L, 7L, 7L, 5L, 5L, 7L, 4L, 1L, 
    4L, 6L, 4L, 3L, 2L, 4L, 6L, 1L, 7L, 1L, 1L, 7L, 3L, 4L, 1L, 
    1L, 2L, 6L, 4L, 6L, 6L, 2L, 6L, 4L, 2L, 2L, 2L, 1L, 7L, 6L, 
    5L, 7L, 1L, 7L, 5L, 5L, 4L, 6L, 1L, 7L, 6L, 2L, 3L, 5L, 4L, 
    2L, 4L, 5L, 5L, 6L, 7L, 3L, 4L, 6L, 2L, 4L, 5L, 3L, 6L, 1L, 
    2L, 1L, 4L, 2L, 3L, 1L, 2L, 5L, 2L, 2L, 7L, 1L, 1L, 6L, 1L, 
    1L, 5L, 2L, 7L, 2L, 4L, 1L, 3L, 3L, 6L, 7L, 1L, 5L, 3L, 6L, 
    4L, 1L, 1L, 1L, 2L, 2L, 2L, 7L, 3L, 1L, 4L, 1L, 6L, 1L, 2L, 
    2L, 5L, 4L, 3L, 1L, 1L, 1L, 4L, 3L, 1L, 7L, 3L, 4L)), row.names = c(NA, 
-300L), class = "data.frame")

conditional_merged <- 
structure(list(T = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L), levels = c("TA", "TB", "TC"), class = "factor"), Y = c(4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111, 
4.39111111111111, 4.39111111111111, 4.39111111111111, 4.39111111111111
), C = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), levels = c("CI", 
"CJ", "CK", "CL", "CM"), class = "factor"), id = c(NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA), Item = c(NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA), cond__ = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L), levels = c("CI", "CJ", "CK", "CL", "CM"), class = "factor"), 
    cats__ = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 
    4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 
    2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 
    7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 
    5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 
    3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 
    1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 
    6L, 6L, 6L, 7L, 7L, 7L), levels = c("1", "2", "3", "4", "5", 
    "6", "7"), class = "factor"), effect1__ = structure(c(1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), levels = c("TA", 
    "TB", "TC"), class = "factor"), effect2__ = structure(c(1L, 
    1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 
    6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 
    4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 
    2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 
    7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 
    5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 
    3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L), levels = c("1", 
    "2", "3", "4", "5", "6", "7"), class = "factor"), estimate__ = c(0.0300008268819071, 
    0.00170807140416257, 0.0125678588873665, 0.0371695414439314, 
    0.012119471358395, 0.0282020433470131, 0.0538546633379412, 
    0.0425689545348869, 0.0530491120976749, 0.0658775964304108, 
    0.0882563128704992, 0.0761589847929193, 0.0986130094126399, 
    0.180771897415021, 0.126126694339745, 0.23881935853806, 0.439185893195075, 
    0.312629512121465, 0.471759679078726, 0.229424934177548, 
    0.386371712219473, 0.0215646239815038, 0.000546952685843985, 
    0.0205942035802998, 0.0502130180065366, 0.0108069765149421, 
    0.0522485194051517, 0.0907720718966637, 0.0637827426619218, 
    0.0964711912408152, 0.119961784361526, 0.160041421750908, 
    0.128192546448136, 0.174963042743208, 0.304268646961126, 
    0.185804021804899, 0.330680231561976, 0.411020943848545, 
    0.333180437911378, 0.205979859500311, 0.042634737058423, 
    0.176609225454535, 0.0215329313231839, 0.000883081583992305, 
    2.34158961390798e-13, 0.0699776817876162, 0.0207605155279803, 
    2.22442197097232e-06, 0.137749963897597, 0.118468196237038, 
    0.00979060872762466, 0.17650500511898, 0.250608812268428, 
    0.323537075499795, 0.226664708281569, 0.347899647049756, 
    0.620984038862575, 0.292348342489242, 0.247307061557615, 
    0.037449052320798, 0.0687276015591253, 0.00677021277843431, 
    5.68342928275456e-10, 0.0776144159829051, 0.0118758379516284, 
    8.92932541877572e-09, 0.167188305411382, 0.12736189913919, 
    0.00228352002621285, 0.227615057856713, 0.327442899651959, 
    0.314370577358229, 0.205443329494754, 0.31004790941512, 0.611834153268482, 
    0.178725382249026, 0.177437210593003, 0.0611446577666386, 
    0.12656459486168, 0.0376240014124437, 5.28109596841242e-05, 
    0.0110609909216826, 0.000104399401824273, 0, 0.264484999913786, 
    0.102304230847438, 0.00550613746200636, 0.253569720020148, 
    0.352221710367078, 0.374235010575604, 0.214262193581045, 
    0.349681045340641, 0.558314856173018, 0.133246841630802, 
    0.145633586629427, 0.0544470659976089, 0.0847773973321119, 
    0.0382578848347728, 0.000643042681645889, 0.0421545215987503, 
    0.00336402634096827, 1.73061349362236e-07, 0.00246573731239585, 
    1.98132293272035e-06, 0), se__ = c(0.0109581961780363, 0.00135246460353729, 
    0.00584001483656834, 0.00766244114280564, 0.00586246867586202, 
    0.00781245161065959, 0.00834206679902841, 0.0121243025610004, 
    0.009846248992885, 0.00843464770261154, 0.0155190781171241, 
    0.010709734550086, 0.0114336956882855, 0.0208842710067859, 
    0.0143021394565877, 0.0220674393197195, 0.0310256199238322, 
    0.0260444043072376, 0.0450691016468207, 0.0429428020838231, 
    0.0475582267683523, 0.00973164826897761, 0.000502991643768085, 
    0.00942469795354643, 0.0122490799452495, 0.00561556985386257, 
    0.0127167608042644, 0.013872847912608, 0.0184153155072177, 
    0.0142375732310978, 0.0133944956036142, 0.0246686670539234, 
    0.0139862757979948, 0.0166453756760368, 0.0262365111373308, 
    0.017658008281725, 0.026151793230096, 0.0462294287615096, 
    0.0266904348132576, 0.0380535724654495, 0.0185187551187277, 
    0.036992451462338, 0.00945482251521887, 0.000797610670240591, 
    3.47163385253748e-13, 0.0163770143590675, 0.00991255313798958, 
    3.22480224961055e-06, 0.0187419513674298, 0.0276517300479326, 
    0.00884282971979177, 0.0168465817699377, 0.0294987004765749, 
    0.0955224523359158, 0.0182312261141241, 0.0278095444958595, 
    0.0827195082182694, 0.0322493045784407, 0.0491785430241369, 
    0.026531025466952, 0.02170673508893, 0.00472176110639137, 
    8.42478565377114e-10, 0.0232288802447621, 0.00724993889261854, 
    1.32299397191594e-08, 0.0225649774875159, 0.0325772882124464, 
    0.00269919813753681, 0.0198936616691798, 0.0348115158359877, 
    0.105075500807634, 0.0171143944837877, 0.0277519638034909, 
    0.0775387354036028, 0.0195975766891566, 0.034745498672043, 
    0.039927241462467, 0.0264292741703992, 0.0168930828587183, 
    7.38782924090657e-05, 0.00599981889574162, 0.000117127632720276, 
    0, 0.0443943321915507, 0.0332854806858299, 0.00524733001141858, 
    0.0234762440187718, 0.0408337125466672, 0.0896307756508654, 
    0.0200076500807566, 0.0329065583157791, 0.0699801902359, 
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    0.0140880453724271, 0.00254430674959, 2.54365094529208e-07, 
    0.0018052579055687, 2.67702775898196e-06, 0), lower__ = c(0.0132308206642849, 
    0.000267881287083297, 0.00447112403640101, 0.0232449192163, 
    0.00406161627178914, 0.0153538435061708, 0.0384062199170399, 
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    0.00737645250278172, 0.0291435232141837, 0.00303346006892112, 
    0.0302185619909281, 0.0654822986025623, 0.0319213918211253, 
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    0.112425544309916, 0.0082113932016613, 9.32704213376801e-05, 
    6.82190375467763e-20, 0.0416645904364448, 0.00670596413973237, 
    2.23648389048956e-09, 0.102084803887236, 0.0677414428202744, 
    0.000657962798805887, 0.145454945812128, 0.190532056079914, 
    0.137381778611668, 0.192871150111729, 0.292741215103492, 
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    0.00436612542911273, 0.0346102760890623, 0.00131082777869522, 
    5.99520433297585e-15, 0.0397616718734944, 0.0026864466567117, 
    1.6401755004269e-13, 0.122341425735659, 0.0676944489910864, 
    4.66065456311946e-05, 0.189969221207212, 0.254120493023344, 
    0.112204215718648, 0.173545982814769, 0.255162874245699, 
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    0.000570793519440205, 8.45735897980762e-11, 0.000403998381446805, 
    2.23016929062903e-08, 0), upper__ = c(0.0575501895014338, 
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    6.42020722091408e-07, 0.132836970638068, 0.0356440752494878, 
    6.39290072059738e-06, 0.217253975480101, 0.202554152526666, 
    0.0221219589321008, 0.269296929575383, 0.393672313478166, 
    0.5656552669243, 0.241058740223302, 0.367271250343831, 0.739144681129605, 
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    0.182576537467774, 0.084258265820575, 0.00148323352619449, 
    0.0287007945114536, 0.00110314200090858, 8.0183693018654e-12, 
    0.359207100226798, 0.186040433313165, 0.0361591555310803, 
    0.302735001210392, 0.433917524044242, 0.578864414276696, 
    0.255135129721873, 0.415353538170228, 0.684289553679762, 
    0.16839015707036, 0.213136050621892, 0.152620069134574, 0.1176588327904, 
    0.0810736623213326, 0.00666357798901797, 0.075454054247938, 
    0.0143130489049961, 2.53564166485198e-05, 0.00938334652505292, 
    6.56689024886637e-05, 8.43206060530123e-13)), row.names = c(NA, 
-105L), effects = c("T", "cats__"), response = "Y", surface = FALSE, categorical = TRUE, catscale = "Probability", ordinal = FALSE, points = structure(list(
    T = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L), levels = c("TA", "TB", "TC"), class = "factor"), 
    resp__ = c(7L, 3L, 4L, 7L, 7L, 7L, 6L, 7L, 2L, 7L, 7L, 6L, 
    6L, 4L, 3L, 7L, 3L, 4L, 7L, 5L, 5L, 7L, 3L, 5L, 3L, 6L, 3L, 
    2L, 3L, 3L, 6L, 3L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 7L, 
    7L, 7L, 7L, 6L, 6L, 6L, 7L, 7L, 6L, 7L, 1L, 7L, 4L, 7L, 7L, 
    7L, 3L, 4L, 7L, 6L, 7L, 6L, 7L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 
    7L, 7L, 5L, 3L, 6L, 7L, 7L, 4L, 3L, 6L, 6L, 7L, 7L, 6L, 6L, 
    6L, 4L, 7L, 6L, 6L, 5L, 6L, 7L, 6L, 7L, 7L, 6L, 6L, 6L, 6L, 
    7L, 2L, 7L, 7L, 4L, 7L, 7L, 6L, 7L, 7L, 5L, 7L, 7L, 1L, 6L, 
    6L, 7L, 7L, 5L, 6L, 4L, 5L, 6L, 6L, 7L, 6L, 7L, 6L, 6L, 7L, 
    6L, 6L, 6L, 5L, 7L, 6L, 7L, 6L, 7L, 4L, 7L, 6L, 3L, 6L, 6L, 
    7L, 6L, 5L, 3L, 4L, 5L, 6L, 6L, 6L, 4L, 3L, 4L, 6L, 7L, 6L, 
    4L, 7L, 6L, 6L, 6L, 6L, 6L, 7L, 5L, 6L, 5L, 6L, 7L, 5L, 7L, 
    6L, 6L, 5L, 6L, 6L, 4L, 5L, 7L, 5L, 7L, 6L, 6L, 5L, 7L, 5L, 
    7L, 5L, 6L, 3L, 7L, 5L, 7L, 5L, 6L, 6L, 5L, 7L, 4L, 6L, 5L, 
    7L, 5L, 7L, 5L, 6L, 5L, 6L, 5L, 6L, 7L, 6L, 6L, 3L, 5L, 6L, 
    3L, 5L, 6L, 6L, 6L, 5L, 7L, 6L, 6L, 3L, 6L, 7L, 7L, 6L, 6L, 
    6L, 6L, 6L, 7L, 7L, 7L, 7L, 6L, 5L, 5L, 4L, 6L, 2L, 5L, 4L, 
    3L, 4L, 5L, 6L, 5L, 7L, 7L, 6L, 3L, 6L, 7L, 7L, 7L, 5L, 7L, 
    6L, 7L, 7L, 6L, 6L, 7L, 7L, 7L, 6L, 6L, 7L, 7L, 6L, 7L, 2L, 
    7L, 7L, 7L, 6L, 6L, 5L, 5L, 3L, 7L, 6L, 6L, 6L, 7L, 7L, 3L, 
    7L, 7L, 6L, 5L, 7L, 7L, 7L, 5L, 6L, 7L, 1L, 6L, 5L, 7L, 7L, 
    6L, 6L, 6L, 7L, 3L, 6L, 6L, 6L, 7L, 5L, 7L, 7L, 7L, 6L, 4L, 
    7L, 7L, 7L, 4L, 7L, 5L, 7L, 6L, 7L, 2L, 1L, 7L, 6L, 5L, 4L, 
    1L, 7L, 3L, 6L, 5L, 7L, 7L, 4L, 7L, 6L, 7L, 6L, 3L, 4L, 6L, 
    7L, 1L, 7L), cond__ = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    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 = "CI", class = "factor"), 
    effect1__ = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L), levels = c("TA", "TB", "TC"), class = "factor")), row.names = c(NA, 
360L), class = "data.frame"), class = "data.frame")

library(tidyverse)
rdatLong |> 
  mutate(
    # reverse order of response levels so 7 appears at top of plot
    Y = Y |> as.character(),
    Y = Y |> fct_relevel(7:1 |> as.character())
  ) |> 
  mutate(C = S |> fct_recode(CI = 'Sw', CJ = 'UK', CK = 'Ge', CL = 'Br', CM = 'Th')) |> 
  mutate(T = T |> fct_recode(TA = 'Parental', TB = 'Married', TC = 'Citizen')) |> 
  inner_join(
    conditional_merged %>% 
      # mutate(C = S |> fct_recode(CI = 'Sw', CJ = 'UK', CK = 'Ge', CL = 'Br', CM = 'Th')) |> 
      mutate(overall_resp = as.numeric(effect2__) * estimate__) |>
      aggregate(overall_resp ~ C * T, sum) 
  ) |> 
  ggplot() + 
  geom_bar(aes(C, fill = C)) +
  # add open dots at overall response value, replotted at each response value
  geom_point(aes(C, overall_resp, fill = C), shape = 21) +
  facet_grid(Y ~ T)

Created on 2024-08-26 with reprex v2.0.2

This seems to be in keeping with your data, so I'm not sure what you were seeing.

28

So, I tried it again. I get this

Rplot1
Rplot11260×754 78.6 KB

Perhaps there's a change in the data frame that I create,

data frame named result contains the observed data. dput(result) contains more characters than I'm allowed to post here. A glimpse shows this (if that helps)

glimpse(result)
Rows: 1,800
Columns: 6
$ G    <chr> "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M", "M",…
$ Item <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ id   <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20…
$ C    <fct> CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, CI, C…
$ T    <fct> TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, TA, T…
$ Y    <int> 7, 3, 4, 7, 7, 7, 6, 7, 2, 7, 7, 6, 6, 4, 3, 7, 3, 4, 7, 5, 5, 7, 3, …

I'm sorry for all the work I'm causing you...

Best,
D

29

I see the issue, but don't see a simple fix yet. I'll think some more, and maybe other folks may have some ideas, too.

1 Like
30

It looks like you’re encountering issues with the geom_segment function. The warning suggests that some aesthetics are not recognized. Ensure that position, lineend, and show.legend are correctly applied in the context of geom_segment. You might need to adjust the code or use alternative methods to set xend coordinates. Have you tried using scale_x_continuous or scale_y_continuous for better control over the axes?

31

Hi @abuislam,

thanks for commenting and trying to help. I'm not that familiar with ggplot2 coding. Would you be able to provide an example?