问题：
中介包中的Multimed函数：“参数不是数字或逻辑：返回NA”错误
傅阿苏
运行＜code＞multimed＜/code＞函数时出错：＜code＞参数不是数字或逻辑：返回NA＜/code＞。我可以从multimed运行示例代码，但不能运行我自己的数据集或“假”数据集（见下文）。不确定问题出在哪里-这是数据设置中的错误？还是代码本身的错误？
感谢您的任何帮助。
library(palmerpenguins)
library(mediation)
#> Loading required package: MASS
#> Loading required package: Matrix
#> Loading required package: mvtnorm
#> Loading required package: sandwich
#> mediation: Causal Mediation Analysis
#> Version: 4.5.0
library(tidyverse)
library(reprex)
## create a fake dataset to show example of error
glimpse(penguins)
#> Rows: 344
#> Columns: 8
#> $ species <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel~
#> $ island <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse~
#> $ bill_length_mm <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, ~
#> $ bill_depth_mm <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, ~
#> $ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186~
#> $ body_mass_g <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, ~
#> $ sex <fct> male, female, female, NA, female, male, female, male~
#> $ year <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007~
penguins %>%
filter(species!="Gentoo") %>%
mutate(treat = as.numeric(rbernoulli(n=220, 0.5))) %>%
drop_na()->df
summary(df)
#> species island bill_length_mm bill_depth_mm
#> Adelie :146 Biscoe : 44 Min. :32.1 Min. :15.50
#> Chinstrap: 68 Dream :123 1st Qu.:37.8 1st Qu.:17.50
#> Gentoo : 0 Torgersen: 47 Median :40.6 Median :18.40
#> Mean :42.0 Mean :18.37
#> 3rd Qu.:46.0 3rd Qu.:19.10
#> Max. :58.0 Max. :21.50
#> flipper_length_mm body_mass_g sex year treat
#> Min. :172.0 Min. :2700 female:107 Min. :2007 Min. :0.000
#> 1st Qu.:187.0 1st Qu.:3400 male :107 1st Qu.:2007 1st Qu.:0.000
#> Median :191.0 Median :3700 Median :2008 Median :1.000
#> Mean :191.9 Mean :3715 Mean :2008 Mean :0.514
#> 3rd Qu.:196.0 3rd Qu.:3994 3rd Qu.:2009 3rd Qu.:1.000
#> Max. :212.0 Max. :4800 Max. :2009 Max. :1.000
test<-multimed(outcome = "bill_length_mm",
med.main = "flipper_length_mm",
med.alt = "bill_depth_mm",
treat = "treat",
covariates = "year",
data=df, sims=100)
#> Warning in mean.default(data.1[, treat] * data.1[, med.main]^2): argument is not
#> numeric or logical: returning NA
#> Warning in ETM2 * sigma^2/VY: Recycling array of length 1 in vector-array arithmetic is deprecated.
#> Use c() or as.vector() instead.
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
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#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
#> Warning in mean.default(data.b[, treat]): argument is not numeric or logical:
#> returning NA
由reprex包（v2.0.1）于2022-05-18创建
共有1个答案
秦滨海
我和你有同样的问题。
对于警告：
#
您应该将表转换为.data。框架，因为包不是为TIBLE设计的。
对于警告：
平均值警告。默认值（data.1[，treat]*data.1[，med.main]^2）：参数不是
#
您应该将treat变量转换为数值，但是，对于另一个警告，我还没有找到解决方案。。。
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