coord_flip in plot_model sjplot

ffscu2ro  于 2023-04-27  发布在  其他
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我将感谢任何帮助在翻转轴如图所示.我尝试使用plot_model在plot_model（sjplot）但没有任何成功.我尝试coord_flip()/ coord_flitp = TRUE但没有任何成功.

  1. library(sjmisc)
  2. library(sjPlot)
  4. data(efc)
  5. efc <- to_factor(efc, c161sex, e42dep, c172code)
  6. m <- lm(neg_c_7 ~ pos_v_4 + c12hour + e42dep + c172code, data = efc)
  8. # create plot-object
  9. p <- plot_model(m)
  11. # change theme
  12. p + theme_sjplot()

  1. library(lme4)       # linear mixed-effects models
  2. library(lmerTest)   # test for linear mixed-effects models
  3. library(gtsummary)
  4. library(sjPlot)
  5. library(ggplot2)
  7. m1 <- lmer(distance ~ as.factor(year) + (1 | id), data = trajectories)
  9. summary(m1)
  10. p <- plot_model(m1)
  11. p+coord_cartesian()
  13. m2 <- lmer(distance ~ as.factor(year)+sex + (1 | id), data = trajectories)
  15. summary(m2)
  16. p2 <- plot_model(m2, rm.terms = c("sex [M]"))
  17. p2+coord_cartesian()
  19. p3 <- plot_models(m1,m2, rm.terms = c("sex [M]"),
  20.                   axis.labels = c("2010","2009","2008","20007","2006", "2005","2004","2003","2002"))
  21. p3+coord_cartesian()
  23. p4 <- plot_models(m1,m2, rm.terms = c("sex [M]"),
  24.                   axis.labels = c("2002","2003","2004","2005","2006", "2007","2008","2009","2010"))
  25. p4+coord_cartesian()

下面是p3

输出
这是p4输出

这里是虚拟数据

  1. > dput(trajectories)
  2. structure(list(id = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  3. 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 
  4. 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 
  5. 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 
  6. 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 
  7. 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 
  8. 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
  9. 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
  10. 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 
  11. 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 
  12. 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 
  13. 17L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 
  14. 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 
  15. 20L, 20L, 20L, 20L, 20L), year = c(2001L, 2002L, 2003L, 2004L, 
  16. 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 
  17. 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 
  18. 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 
  19. 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 
  20. 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 
  21. 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2001L, 2002L, 
  22. 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2004L, 
  23. 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 
  24. 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 
  25. 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 
  26. 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 
  27. 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 
  28. 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 
  29. 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 
  30. 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 
  31. 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 
  32. 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 
  33. 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 
  34. 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 
  35. 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L), distance = c(15, 
  36. 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 
  37. 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 24, 
  38. 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 
  39. 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 
  40. 23, 21, 21.5, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 
  41. 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 
  42. 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 
  43. 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 
  44. 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 
  45. 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 
  46. 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 
  47. 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 
  48. 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 
  49. 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24), age = c(8L, 
  50. 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 11L, 12L, 13L, 14L, 
  51. 15L, 16L, 17L, 18L, 19L, 20L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 
  52. 22L, 23L, 24L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 
  53. 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 9L, 10L, 11L, 12L, 
  54. 13L, 14L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 18L, 
  55. 19L, 20L, 21L, 22L, 23L, 24L, 28L, 40L, 41L, 42L, 43L, 44L, 45L, 
  56. 46L, 47L, 48L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 
  57. 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 
  58. 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 
  59. 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 
  60. 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 
  61. 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 
  62. 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 
  63. 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L), 
  64.     Quintile = structure(c(5L, 2L, 3L, 3L, 2L, 2L, 4L, 2L, 5L, 
  65.     5L, 1L, 4L, 2L, 5L, 4L, 3L, 3L, 4L, 3L, 3L, 1L, 3L, 1L, 2L, 
  66.     1L, 5L, 2L, 4L, 1L, 4L, 3L, 2L, 5L, 3L, 4L, 4L, 3L, 1L, 4L, 
  67.     3L, 4L, 1L, 4L, 4L, 5L, 1L, 5L, 2L, 2L, 2L, 3L, 5L, 3L, 3L, 
  68.     4L, 1L, 3L, 1L, 1L, 5L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 4L, 
  69.     5L, 3L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 
  70.     2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 
  71.     5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 
  72.     2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 
  73.     5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 
  74.     2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 
  75.     5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 
  76.     2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L), levels = c("Q1", "Q2", 
  77.     "Q3", "Q4", "Q5"), class = "factor"), sex = structure(c(2L, 
  78.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
  79.     1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
  80.     1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
  81.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
  82.     1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
  83.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  84.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  85.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  86.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  87.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  88.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  89.     2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  90.     2L, 2L), levels = c("F", "M"), class = "factor"), yr_qun = structure(c(6L, 
  91.     8L, 14L, 18L, 21L, 26L, 32L, 35L, 43L, 48L, 2L, 10L, 13L, 
  92.     20L, 23L, 27L, 31L, 37L, 41L, 46L, 2L, 9L, 1L, 1L, 1L, 1L, 
  93.     30L, 37L, 39L, 47L, 4L, 8L, 16L, 18L, 23L, 28L, 31L, 34L, 
  94.     42L, 46L, 5L, 7L, 15L, 19L, 24L, 25L, 33L, 35L, 40L, 45L, 
  95.     4L, 11L, 14L, 18L, 23L, 25L, 4L, 7L, 12L, 20L, 21L, 28L, 
  96.     29L, 36L, 40L, 47L, 17L, 22L, 28L, 33L, 36L, 41L, 44L, 3L, 
  97.     8L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 3L, 8L, 14L, 
  98.     17L, 21L, 27L, 33L, 38L, 40L, 48L, 3L, 8L, 14L, 17L, 1L, 
  99.     1L, 1L, 38L, 40L, 1L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 
  100.     40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 
  101.     1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 
  102.     17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 
  103.     27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 
  104.     38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 
  105.     48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L), levels = c("", 
  106.     "2001_Q1", "2001_Q2", "2001_Q3", "2001_Q4", "2001_Q5", "2002_Q1", 
  107.     "2002_Q2", "2002_Q3", "2002_Q4", "2002_Q5", "2003_Q1", "2003_Q2", 
  108.     "2003_Q3", "2003_Q4", "2003_Q5", "2004_Q1", "2004_Q3", "2004_Q4", 
  109.     "2004_Q5", "2005_Q2", "2005_Q3", "2005_Q4", "2005_Q5", "2006_Q1", 
  110.     "2006_Q2", "2006_Q3", "2006_Q4", "2007_Q1", "2007_Q2", "2007_Q3", 
  111.     "2007_Q4", "2007_Q5", "2008_Q1", "2008_Q2", "2008_Q3", "2008_Q4", 
  112.     "2008_Q5", "2009_Q1", "2009_Q2", "2009_Q3", "2009_Q4", "2009_Q5", 
  113.     "2010_Q1", "2010_Q2", "2010_Q3", "2010_Q4", "2010_Q5"), class = "factor")), class = "data.frame", row.names = c(NA, 
  114. -183L))
r

1条答案

按热度按时间
ergxz8rk

ergxz8rk1#

为了使用plot_models()重新排列翻转的x轴上的值，您可以以不同的顺序“传入”数据，例如。

  1. library(sjPlot)
  2. library(ggplot2)
  3. library(forcats)
  4. library(lme4)       # linear mixed-effects models
  5. #> Loading required package: Matrix
  6. # install.packages("lmerTest")
  7. library(lmerTest)   # test for linear mixed-effects models
  8. #> 
  9. #> Attaching package: 'lmerTest'
  10. #> The following object is masked from 'package:lme4':
  11. #> 
  12. #>     lmer
  13. #> The following object is masked from 'package:stats':
  14. #> 
  15. #>     step
  16. library(gtsummary)
  18. trajectories <- structure(list(id = 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, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L),
  19.                                year = c(2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L),
  20.                                distance = c(15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 21, 20, 21.5, 23, 21, 21.5, 21, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24, 15, 20, 21.5, 23, 21, 21.5, 24, 25.5, 20.5, 24),
  21.                                age = c(8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 9L, 10L, 11L, 12L, 13L, 14L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 28L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L),
  22.                                Quintile = structure(c(5L, 2L, 3L, 3L, 2L, 2L, 4L, 2L, 5L, 5L, 1L, 4L, 2L, 5L, 4L, 3L, 3L, 4L, 3L, 3L, 1L, 3L, 1L, 2L, 1L, 5L, 2L, 4L, 1L, 4L, 3L, 2L, 5L, 3L, 4L, 4L, 3L, 1L, 4L, 3L, 4L, 1L, 4L, 4L, 5L, 1L, 5L, 2L, 2L, 2L, 3L, 5L, 3L, 3L, 4L, 1L, 3L, 1L, 1L, 5L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 4L, 5L, 3L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L, 2L, 2L, 3L, 1L, 2L, 3L, 5L, 5L, 2L, 5L),
  23.                                                       levels = c("Q1", "Q2", "Q3", "Q4", "Q5"), class = "factor"), sex = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 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, 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),
  24.                                                                                                                                    levels = c("F", "M"), class = "factor"), yr_qun = structure(c(6L, 8L, 14L, 18L, 21L, 26L, 32L, 35L, 43L, 48L, 2L, 10L, 13L, 20L, 23L, 27L, 31L, 37L, 41L, 46L, 2L, 9L, 1L, 1L, 1L, 1L, 30L, 37L, 39L, 47L, 4L, 8L, 16L, 18L, 23L, 28L, 31L, 34L, 42L, 46L, 5L, 7L, 15L, 19L, 24L, 25L, 33L, 35L, 40L, 45L, 4L, 11L, 14L, 18L, 23L, 25L, 4L, 7L, 12L, 20L, 21L, 28L, 29L, 36L, 40L, 47L, 17L, 22L, 28L, 33L, 36L, 41L, 44L, 3L, 8L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 3L, 8L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 3L, 8L, 14L, 17L, 1L, 1L, 1L, 38L, 40L, 1L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L, 1L, 1L, 14L, 17L, 21L, 27L, 33L, 38L, 40L, 48L), levels = c("", "2001_Q1", "2001_Q2", "2001_Q3", "2001_Q4", "2001_Q5", "2002_Q1", "2002_Q2", "2002_Q3", "2002_Q4", "2002_Q5", "2003_Q1", "2003_Q2", "2003_Q3", "2003_Q4", "2003_Q5", "2004_Q1", "2004_Q3", "2004_Q4", "2004_Q5", "2005_Q2", "2005_Q3", "2005_Q4", "2005_Q5", "2006_Q1", "2006_Q2", "2006_Q3", "2006_Q4", "2007_Q1", "2007_Q2", "2007_Q3", "2007_Q4", "2007_Q5", "2008_Q1", "2008_Q2", "2008_Q3", "2008_Q4", "2008_Q5", "2009_Q1", "2009_Q2", "2009_Q3", "2009_Q4", "2009_Q5", "2010_Q1", "2010_Q2", "2010_Q3", "2010_Q4", "2010_Q5"), class = "factor")), class = "data.frame", row.names = c(NA, -183L))
  26. trajectories$year1 <- factor(trajectories$year)
  28. m1 <- lmer(distance ~ year1 + (1 | id), data = trajectories)
  29. m2 <- lmer(distance ~ year1 + sex + (1 | id), data = trajectories)
  30. #> boundary (singular) fit: see help('isSingular')
  32. trajectories$year2 <- factor(trajectories$year, levels = c("2010","2009","2008","2007","2006", "2005","2004","2003","2002", "2001", "2000"))
  34. m3 <- lmer(distance ~ year2 + (1 | id), data = trajectories)
  35. m4 <- lmer(distance ~ year2 + sex + (1 | id), data = trajectories)
  36. #> boundary (singular) fit: see help('isSingular')
  38. plot_models(m1,m2) +
  39.   coord_cartesian() +
  40.   theme(legend.position = "top")
  41. #> Coordinate system already present. Adding new coordinate system, which will
  42. #> replace the existing one.

  1. plot_models(m3,m4) +
  2.   coord_cartesian() +
  3.   theme(legend.position = "top")
  4. #> Coordinate system already present. Adding new coordinate system, which will
  5. #> replace the existing one.

创建于2023-04-24带有reprex v2.0.2

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