无法使用emmeans获得arcsin反转换。

huangapple
go评论104阅读模式
英文:

Can't get arcsin back-transformation with emmeans to work

问题

I am doing a GAM with my response variable as a percentage (0-100). I have used an arcsin transformation to improve model fit (asin(sqrt(myvariable/100))). I now want to evaluate contrasts between levels of my explanatory factor variable on the original scale. I have been trying to use emmeans and followed the steps in the Transformations and link functions vignette to set up my model with the transformation in a format emmeans can read. However, when I run the emmeans function I get the following error: Error in link$mu.eta(object@bhat[estble]) : attempt to apply non-function.

I set up the transformation object like this:

  1. tran <- make.tran("asin.sqrt", 100)

I am confident that bit works, because when I tried it on a linear model with emmeans, it worked:

  1. warp.t <- with(tran, lm(linkfun(breaks)~wool*tension, warpbreaks))
  2. emmeans(warp.t, ~wool|tension, type="response")
  3. tension = L:
  4.  wool response   SE df lower.CL upper.CL
  5.  A        44.2 4.00 48     36.3     52.3
  6.  B        27.7 3.61 48     20.8     35.3
  8. tension = M:
  9.  wool response   SE df lower.CL upper.CL
  10.  A        23.5 3.41 48     17.0     30.7
  11.  B        28.4 3.63 48     21.4     35.9
  13. tension = H:
  14.  wool response   SE df lower.CL upper.CL
  15.  A        23.9 3.43 48     17.4     31.1
  16.  B        18.6 3.13 48     12.7     25.3
  18. Confidence level used: 0.95 
  19. Intervals are back-transformed from the asin(sqrt(mu/100)) scale

However, if I try it in a gam (both straight into emmeans() or using regrid()), it doesn't work:

  1. dat <- data.frame("x" = rep(1:3, times=12), 
  2.                   "y" = rep(4:6, times=12), 
  3.                   "z" = runif(36, 0, 100), 
  4.                   "m" = rep(1:12, times=3))
  6. gam.t <- with(tran, gam(linkfun(z) ~ x * y + s(m), data=dat))
  8. emmeans(gam.t, ~x|y, type="response")
  9. Error in linkinv(result[[cnm[1]]]) : could not find function "linkinv"
  11. #or
  12. regrid(emmeans(gam.t, ~x|y), transform="response")
  13. Error in flink$mu.eta(object@bhat[estble]) : 
  14.   attempt to apply non-function

It's like it's looking for the inverse link function in the gam, but it's not where emmeans expects it to be. Can I assign it to the gam somehow? Does it not work with gams? Am I doing something wrong?

英文:

I am doing a GAM with my response variable as a percentage (0-100). I have used an arcsin transformation to improve model fit (asin(sqrt(myvariable/100))). I now want to evaluate contrasts between levels of my explanatory factor variable on the original scale. I have been trying to use emmeans and followed the steps in the Transformations and link functions vignette to set up my model with the transformation in a format emmeans can read. However, when I run the emmeans function I get the following error: Error in link$mu.eta(object@bhat[estble]) : attempt to apply non-function.

I set up the transformation object like this:

  1. tran <- make.tran("asin.sqrt", 100)

I am confident that bit works, because when I tried it on a linear model with emmeans, it worked:

  1. warp.t <- with(tran, lm(linkfun(breaks)~wool*tension, warpbreaks))
  2. emmeans(warp.t, ~wool|tension, type="response")
  3. tension = L:
  4.  wool response   SE df lower.CL upper.CL
  5.  A        44.2 4.00 48     36.3     52.3
  6.  B        27.7 3.61 48     20.8     35.3
  8. tension = M:
  9.  wool response   SE df lower.CL upper.CL
  10.  A        23.5 3.41 48     17.0     30.7
  11.  B        28.4 3.63 48     21.4     35.9
  13. tension = H:
  14.  wool response   SE df lower.CL upper.CL
  15.  A        23.9 3.43 48     17.4     31.1
  16.  B        18.6 3.13 48     12.7     25.3
  18. Confidence level used: 0.95 
  19. Intervals are back-transformed from the asin(sqrt(mu/100)) scale

However, if I try it in a gam (both straight into emmeans() or using regrid()), it doesn't work:

  1. dat <- data.frame("x" = rep(1:3, times=12), 
  2.                   "y" = rep(4:6, times=12), 
  3.                   "z" = runif(36, 0, 100), 
  4.                   "m" = rep(1:12, times=3))
  6. gam.t <- with(tran, gam(linkfun(z) ~ x * y + s(m), data=dat))
  8. emmeans(gam.t, ~x|y, type="response")
  9. Error in linkinv(result[[cnm[1]]]) : could not find function "linkinv"
  11. #or
  12. regrid(emmeans(gam.t, ~x|y), transform="response")
  13. Error in flink$mu.eta(object@bhat[estble]) : 
  14.   attempt to apply non-function

It's like it's looking for the inverse link function in the gam, but it's not where emmeans expects it to be. Can I assign it to the gam somehow? Does it not work with gams? Am I doing something wrong?

答案1

得分: 2

  1. 按照文中在标题“事后指定变换”下的说明，我认为以下代码会给你想要的结果：

gam.t2 <- gam(asin(sqrt(z/100)) ~ x * y + s(m), data = dat)

refgrid_gam.t2 <- update(ref_grid(gam.t2), tran = tran)

emmeans(refgrid_gam.t2, ~ x | y, type = "response")

  2. 在`gam()`调用中，响应变量被转换，然后我们在参考网格上调用`update()`来指定使用了什么变换。我得到的输出再次以百分比为单位：

y = 5:
x response SE df lower.CL upper.CL
2 52 10.3 32 31.5 72.2

置信水平使用: 0.95
区间从asin(sqrt(mu/100))的比例重新转换

英文:

Following the instructions in the vignette under the heading "Specifying a transformation after the fact" I think gives you the result you are looking for:

  1. gam.t2 &lt;- gam(asin(sqrt(z/100)) ~ x * y + s(m), data = dat)
  3. refgrid_gam.t2 &lt;- update(ref_grid(gam.t2), tran = tran)
  5. emmeans(refgrid_gam.t2, ~ x | y, type = &quot;response&quot;)

The response variable is transformed in the call to gam(), then we call update() on the reference grid to specify what transformation was used. The output I get is on the percent scale again:

  1. y = 5:
  2.  x response   SE df lower.CL upper.CL
  3.  2       52 10.3 32     31.5     72.2
  5. Confidence level used: 0.95 
  6. Intervals are back-transformed from the asin(sqrt(mu/100)) scale

huangapple
  • 本文由 发表于 2023年4月13日 23:09:01
  • 转载请务必保留本文链接：https://go.coder-hub.com/76007051.html
  • emmeans
  • gam
  • lsmeans
  • r
匿名

发表评论

匿名网友

:?: :razz: :sad: :evil: :!: :smile: :oops: :grin: :eek: :shock: :???: :cool: :lol: :mad: :twisted: :roll: :wink: :idea: :arrow: :neutral: :cry: :mrgreen:

确定