R 从lsmeans生成一个矩阵来对比收益

要创建数据框，请执行以下操作：

num <- sample(1:25, 20)
x <- data.frame("Day_eclosion" = num, "Developmental" = c("AP", "MA", 
"JU", "L"), "Replicate" = 1:5)

model <- glmer(Day_eclosion ~ Developmental +  (1 | Replicate), family = 
"poisson", data= x)

---

num这是一个有效的函数

pvmat = function(emm, ...) {
    emm = update(emm, by = NULL)    # need to work harder otherwise
    pv = test(pairs(emm, reverse = TRUE, ...)) $ p.value
    fmtpv = sprintf("%6.4f", pv) 
    fmtpv[pv < 0.0001] = "<.0001"
    lbls = do.call(paste, emm@grid[emm@misc$pri.vars])
    n = length(lbls)
    mat = matrix("", nrow = n, ncol = n, dimnames = list(lbls, lbls))
    mat[upper.tri(mat)] = fmtpv
    idx = seq_len(n - 1)
    mat[idx, 1 + idx]   # trim off last row and 1st col
}

您现在需要的是在剪贴板中，并准备粘贴到电子表格中

补遗
回答这个问题启发我在emmeans包中添加一个新函数
pwpm（）
。它将出现在下一个CRAN版本中，现在可从。显示均值和差值以及P值；但是用户可以选择要包括的内容

> pwpm(warp.emm)

wool = A
       L      M      H
L [44.6] 0.0007 0.0009
M 20.556 [24.0] 0.9936
H 20.000 -0.556 [24.6]

wool = B
       L      M      H
L [28.2] 0.9936 0.1704
M -0.556 [28.8] 0.1389
H  9.444 10.000 [18.8]

Row and column labels: tension
Upper triangle: P values   adjust = “tukey”
Diagonal: [Estimates] (emmean) 
Upper triangle: Comparisons (estimate)   earlier vs. later

你没有放一个。如果您希望我们帮助您，请这样做。我已经编辑到我认为可以接受的程度。请让我知道是否还需要更多。起点是
pval=as.data.frame（a$contrasts）$p.value
。这些将是实际的p值，与输出中的格式不同，因此如果需要，需要额外的编码。@RussLenth，是的，您对如何最好地从该点生成该格式有何想法？
pvmat = function(emm, ...) {
    emm = update(emm, by = NULL)    # need to work harder otherwise
    pv = test(pairs(emm, reverse = TRUE, ...)) $ p.value
    fmtpv = sprintf("%6.4f", pv) 
    fmtpv[pv < 0.0001] = "<.0001"
    lbls = do.call(paste, emm@grid[emm@misc$pri.vars])
    n = length(lbls)
    mat = matrix("", nrow = n, ncol = n, dimnames = list(lbls, lbls))
    mat[upper.tri(mat)] = fmtpv
    idx = seq_len(n - 1)
    mat[idx, 1 + idx]   # trim off last row and 1st col
}

require(emmeans)

> warp.lm = lm(breaks ~ wool * tension, data = warpbreaks)
> warp.emm = emmeans(warp.lm, ~ wool * tension)

> warp.emm
 wool tension emmean   SE df lower.CL upper.CL
 A    L         44.6 3.65 48     37.2     51.9
 B    L         28.2 3.65 48     20.9     35.6
 A    M         24.0 3.65 48     16.7     31.3
 B    M         28.8 3.65 48     21.4     36.1
 A    H         24.6 3.65 48     17.2     31.9
 B    H         18.8 3.65 48     11.4     26.1

Confidence level used: 0.95 

> pm = pvmat(warp.emm, adjust = "none")
> print(pm, quote=FALSE)
    B L    A M    B M    A H    B H   
A L 0.0027 0.0002 0.0036 0.0003 <.0001
B L        0.4170 0.9147 0.4805 0.0733
A M               0.3589 0.9147 0.3163
B M                      0.4170 0.0584
A H                             0.2682

clipr::write_clip(pm)

> pwpm(warp.emm)

wool = A
       L      M      H
L [44.6] 0.0007 0.0009
M 20.556 [24.0] 0.9936
H 20.000 -0.556 [24.6]

wool = B
       L      M      H
L [28.2] 0.9936 0.1704
M -0.556 [28.8] 0.1389
H  9.444 10.000 [18.8]

Row and column labels: tension
Upper triangle: P values   adjust = “tukey”
Diagonal: [Estimates] (emmean) 
Upper triangle: Comparisons (estimate)   earlier vs. later