R 3.3.2 : lme4 + lmerTest problems under Mac OS Sierra-6ren

R 3.3.2 : lme4 + lmerTest problems under Mac OS Sierra

转载作者：行者123 更新时间：2023-12-04 12:52:00

在使用 lme4 和 lmerTest 时，我偶然发现了影响 R 3.3.2(和 .3 也是!)的 Mac OS 版本的问题。

lmerTest 产生错误:

Error in calculation of the Satterthwaite's approximation. The output of lme4 package is returned summary from lme4 is returned some computational error has occurred in lmerTest

问题不出现使用 MacOS 下的 R 3.2 和 Windows 下的任何 R 版本。但是，这不是安装问题，因为我在重新安装 R 后以及在另一台 Mac 上重现了该错误。

这是示例代码:

 library(lme4)

#' start of data creation

mydat <- 
  structure(list(ID = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
                        13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29, 
                        1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
                        20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 6, 7, 
                        8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 
                        24, 25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
                        13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 
                        29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 
                        18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 
                        6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
                        23, 24, 25, 26, 27, 28, 29), sex = c(1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
                       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ROI = structure(c(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, 1L, 1L, 1L, 1L, 1L, 
                       1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
                       1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
                       3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
                       3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
                       2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
                       2L, 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), .Label = c("calf", 
                       "DSCAT", "KM", "neck", "SSCAT", "VAT"), class = "factor"), 
                        value = c(0.674, 
                      0.561, 0.543, 0.563, 0.697, 0.608, 0.56, 0.448, 0.626, 0.515, 
                      0.568, 0.528, 0.587, 0.532, 0.547, 0.514, 0.587, 0.572, 0.559, 
                      0.569, 0.462, 0.531, 0.477, 0.582, 0.583, 0.569, 0.563, 0.576, 
                      0.84, 0.638, 0.69, 0.707, 0.704, 0.627, 0.769, 0.637, 0.515, 
                      0.669, 0.699, 0.626, 0.59, 0.639, 0.501, 0.632, 0.624, 0.641, 
                      0.669, 0.656, 0.556, 0.569, 0.633, 0.608, 0.616, 0.664, 0.666, 
                      0.669, 0.545, 0.514, 0.45, 0.585, 0.547, 0.572, 0.577, 0.458, 
                      0.47, 0.537, 0.532, 0.455, 0.62, 0.501, 0.506, 0.44, 0.499, 0.577, 
                      0.457, 0.481, 0.522, 0.516, 0.513, 0.559, 0.571, 0.515, 0.575, 
                      0.521, 0.44, 0.637, 0.521, 0.634, 0.552, 0.581, 0.55, 0.553, 
                      0.522, 0.634, 0.631, 0.512, 0.603, 0.593, 0.58, 0.442, 0.53, 
                      0.463, 0.587, 0.538, 0.48, 0.557, 0.482, 0.53, 0.592, 0.445, 
                      0.526, 0.45, 0.551, 0.51, 0.678, 0.64, 0.599, 0.589, 0.627, 0.621, 
                      0.601, 0.526, 0.619, 0.599, 0.668, 0.615, 0.621, 0.561, 0.532, 
                      0.56, 0.578, 0.686, 0.57, 0.457, 0.563, 0.61, 0.513, 0.638, 0.594, 
                      0.777, 0.562, 0.663, 0.538, 0.471, 0.518, 0.47, 0.535, 0.644, 
                      0.605, 0.474, 0.468, 0.563, 0.539, 0.47, 0.538, 0.453, 0.494, 
                      0.576, 0.418, 0.609, 0.528, 0.453, 0.569, 0.484, 0.486, 0.558, 
                      0.621, 0.465, 0.691, 0.398, 0.539, 0.574), Alter = c(45, 47, 
                     51, 44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 23, 26, 29, 29, 50, 
                     45, 61, 61, 58, 32, 27, 49, 45, 64, 28, 45, 47, 51, 44, 35, 26, 
                     60, 44, 50, 42, 51, 57, 23, 26, 29, 29, 50, 45, 61, 61, 58, 32, 
                     27, 49, 27, 45, 64, 28, 45, 47, 51, 44, 35, 26, 60, 44, 42, 50, 
                     42, 51, 57, 23, 26, 29, 29, 50, 45, 61, 61, 58, 32, 27, 49, 27, 
                     45, 64, 28, 45, 47, 51, 44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 
                     23, 26, 29, 29, 50, 45, 61, 61, 58, 32, 27, 49, 27, 45, 64, 28, 
                     45, 47, 51, 44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 23, 26, 29, 
                     29, 50, 45, 61, 61, 58, 32, 27, 49, 27, 45, 64, 28, 45, 47, 51, 
                     44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 23, 26, 29, 29, 50, 45, 
                     61, 61, 58, 32, 27, 49, 27, 45, 64, 28), 
                      BMI = c(29.7506923675537, 
                  28.8, 28.8385677337646, 41.48, 27.7186069488525, 29.54, 38.06, 
                  35.8453826904297, 35.57, 31.77, 31.75, 32.78, 30.5336246490479, 
                  29.1074104309082, 36.4690246582031, 31.7769088745117, 31.5393238067627, 
                  31.5596752166748, 27.593786239624, 30.8192825317383, 27.0799140930176, 
                  31.481481552124, 29.0328979492188, 24.52, 29.4029197692871, 35.6112785339355, 
                  28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
                  41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 31.77, 
                  31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
                  31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
                  30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
                  24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
                  28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
                  41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
                  31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
                  31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
                  30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
                  24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
                  28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
                  41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
                  31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
                  31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
                  30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
                  24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
                  28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
                  41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
                  31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
                  31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
                  30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
                  24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
                  28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
                  41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
                  31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
                  31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
                  30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
                  24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
                  28.2401905059814, 28.8979587554932)), .Names = c("ID", "sex", 
                  "ROI", "value", "Alter", "BMI"), row.names = c(NA, -172L), class = c("tbl_df","tbl", "data.frame"))

#' end of data creation


library(lmerTest)
mod <- lmer(value~Alter+ROI+BMI+(1|ID),data=mydat,REML=F)
summary(mod)
sessionInfo()

系统信息如下:

R version 3.3.3 (2017-03-06)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.3

locale:
[1] C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] lmerTest_2.0-33 lme4_1.1-12     Matrix_1.2-8   

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.9         Formula_1.2-1       knitr_1.15.1        magrittr_1.5            cluster_2.0.5       splines_3.3.3       MASS_7.3-45         munsell_0.4.3    [9] colorspace_1.3-2    lattice_0.20-34     minqa_1.2.4         stringr_1.1.0       plyr_1.8.4          tools_3.3.3         nnet_7.3-12         grid_3.3.3    [17] data.table_1.10.0   checkmate_1.8.2     htmlTable_1.8       gtable_0.2.0        nlme_3.1-131        latticeExtra_0.6-28 htmltools_0.3.5     digest_0.6.11    [25] survival_2.40-1     lazyeval_0.2.0      assertthat_0.1      tibble_1.2          gridExtra_2.2.1     RColorBrewer_1.1-2  nloptr_1.0.4        ggplot2_2.2.1    [33] base64enc_0.1-3     acepack_1.4.1       rpart_4.1-10        stringi_1.1.2       backports_1.0.4     scales_0.4.1        Hmisc_4.0-2         foreign_0.8-67

最佳答案

经过反复尝试，代码在R3.3.3下运行，虽然我的系统没有变化。我是在做梦吗？有点超自然……我很困惑。抱歉打扰了。

R version 3.3.3 (2017-03-06) Platform: x86_64-apple-darwin13.4.0 (64-bit) Running under: macOS Sierra 10.12.3

locale: [1] C

attached base packages: [1] stats graphics grDevices utils
datasets methods base

other attached packages: [1] lmerTest_2.0-33 lme4_1.1-12
Matrix_1.2-8

loaded via a namespace (and not attached): [1] Rcpp_0.12.9
nloptr_1.0.4 RColorBrewer_1.1-2 plyr_1.8.4
base64enc_0.1-3 tools_3.3.3 rpart_4.1-10
digest_0.6.12 [9] tibble_1.2 nlme_3.1-131
gtable_0.2.0 htmlTable_1.9 checkmate_1.8.2
lattice_0.20-34 gridExtra_2.2.1 stringr_1.2.0 [17] cluster_2.0.5 knitr_1.15.1 htmlwidgets_0.8 grid_3.3.3 nnet_7.3-12 data.table_1.10.0 survival_2.40-1
foreign_0.8-67 [25] latticeExtra_0.6-28 minqa_1.2.4
Formula_1.2-1 ggplot2_2.2.1 magrittr_1.5
Hmisc_4.0-2 scales_0.4.1 backports_1.0.5 [33] htmltools_0.3.5 MASS_7.3-45 splines_3.3.3
assertthat_0.1 colorspace_1.3-2 stringi_1.1.2
acepack_1.4.1 lazyeval_0.2.0 [41] munsell_0.4.3

关于R 3.3.2 : lme4 + lmerTest problems under Mac OS Sierra，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/42705396/

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R 3.3.2 : lme4 + lmerTest problems under Mac OS Sierra