MI数据集的FMI功能正在起作用?

时间:2018-01-24 19:01:59

标签: r r-lavaan

几周前我使用了SemTools软件包中的fmi函数,效果很好!这是我保存的代码并且工作正常:

dat.imp2 <- mice(data = dat1, m = 37, method = "pmm", seed = 444)
out <- fmi(dat.imp2$imputations)
out

我用它来比较使用4个源变量和1个复合词的效率损失,所以我重新运行了两次 - 首先使用4个源变量然后使用1个复合变量,这对复合材料来说要好得多。此外,输出分别显示均值和方差的fmi。

几周后再回到这段代码,它确实无法运行!错误消息显示为:

Error in dim(robj) <- c(dX, dY) : 
  dims [product 0] do not match the length of object [1]

所以,我修改了代码如下:

imp2 <- mice(dat1, m = 37, method = "pmm", seed = 444)
out <- fmi(imp2$data)
out 

这只适用于数据集中的复合变量,并且只给出fmi的均值而不是方差。如果我用四个源变量替换这个复合变量,它会给我以下错误: 警告信息:

In lavaan(slotOptions = object@Options, slotParTable = object@ParTable,  :
  lavaan WARNING: model has NOT converged!

我不明白几周前工作的代码现在怎么办?有人遇到过这个问题吗?我无法在网上找到太多东西。 谢谢!

这是具有一个复合变量的数据集(mommh)

> dput(dat2)
structure(list(mompa = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 
1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 
1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 
0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 
0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 
0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 
0, 1, 0, 0), format.spss = "F8.2", display_width = 10L), momabhx = structure(c(1, 
0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 
1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 
0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 
0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 
0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 
0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 
0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 
0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1), format.spss = "F8.2", display_width = 10L), 
    mommh = c(63, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 35.75, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 43.25, NA, NA, 63, 41.5, 
    34.25, 38.5, 39, 38.5, NA, 49.75, 57.5, 59.25, 50, 42.75, 
    45, 49, 32.75, NA, 35.75, 64.75, 50.5, 46.5, 39.75, 51.75, 
    34.75, 61.25, 46, 43, 56.25, 47, 42.25, 36.5, 34.5, 47, 50, 
    35, 48.25, 46.5, 58.5, 35.5, 55.25, 43.5, 42.75, 35.75, 38, 
    35.5, 50, 38.25, 57, 45.75, 38.5, 44.25, 51.75, NA, 38.25, 
    39.75, 34, 57.25, 39.25, 42.25, 37.25, NA, 32.75, 52.75, 
    NA, NA, 55.75, 62.25, 59.75, 43.75, 59.75, 35.75, NA, 34.25, 
    59.25, 39, 34.75, 32.75, NA, 53.5, NA, 40.5, 50, 33.5, 45.25, 
    41, 50, NA, 38.5, 61.5, 36.25, 46.25, 46, 44.75, 44.75, 62.5, 
    38.25, 49.5, 33.75, NA, 50.25, 43, 43.75, 42.25, 60.5, NA, 
    50.25, 54.75, 42.75, 45.75, 61, 58.25, 44.5, 46.5, 34.25, 
    56.75, 40.5, 47, 42.25, 48, 44, 36.75, 39.75, 48.75, 38.25, 
    49.25, 49.25, NA, NA, 34.25, 44.5, NA, 51, 44, 50.75, 56.25, 
    35, 55, 58.75, 56.5, 68.75, 54, 53, 41.5, 50.75, NA, 32.75, 
    46.75, 32.75, 43, 57, 55.25, NA, NA, 43.75, 55.5, NA, NA, 
    32.75, NA, NA, NA, NA, 60.5, 32.75, NA, 68.25, 50.5, 32.75, 
    66.5, 33, 38.5, 43, 43.75, 62.75, 47, 36.5, 39.5, 39.5), 
    risk6 = structure(c(0, 0, 0, 0, 3, 1, 1, 1, 1, 0, 1, 1, 0, 
    0, 0, 2, 1, 1, 0, 1, 0, 1, 0, 1, 2, 1, 1, 0, 0, 2, 1, 1, 
    2, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 2, 1, 3, 2, 2, 0, 0, 0, 
    2, 0, 2, 2, 1, 2, 2, 1, 3, 2, 3, 1, 1, 0, 1, 3, 1, 2, 2, 
    0, 1, 0, 0, 1, 3, 1, 0, 1, 0, 0, 1, 3, 0, 1, 1, 0, 0, 2, 
    3, 3, 1, 2, 3, 2, 0, 0, 4, 1, 2, 1, 3, 2, 1, 2, 0, 1, 1, 
    2, 1, 1, 0, 0, 0, 0, 0, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 
    NA, 1, 1, 1, 2, 0, NA, 3, 0, 2, 2, 3, 4, 4, 0, 1, 0, 2, 3, 
    2, 2, 2, 2, 1, 3, 2, 2, 3, 1, 1, 1, 0, 0, 1, 1, 0, 2, 0, 
    1, 2, 3, 1, 1, 1, 2, 1, 2, 0, 0, 2, 2, 0, 1, 2, 0, 0, 2, 
    1, 1, 1, 1, 1, 3, 1, 0, 3, 0, 1, 0, 1, 1, 1, 2, 2, 0, 2, 
    3, 3, 0, 0, 0, 1, 2, 1, 1, 1, 0, 1, 1, 3, 1, 1, 0, 0, 3, 
    2, 0, 0, 3, 2, 1, 3, 1, 0, 3, 0, 1, 1, 2, 3, 3, 1, 4, 2, 
    3, 2, 2), format.spss = "F8.2", display_width = 10L), eadiff = structure(c(-1.26734803867686, 
    -0.355541076313792, 0.518653050779668, 1.50568568368194, 
    0.0940935989894723, 2.07356799670629, 1.01843817310907, -1.26734803867686, 
    -0.317928241044189, 0.531190662536203, 0.0940935989894723, 
    -1.47335895869369, -0.586627219843691, -1.26734803867686, 
    0.325179742519372, 0.556265886049271, 1.4179224013862, 1.2244490931259, 
    -0.586627219843691, 0.081555987232938, -0.149530156296961, 
    -0.380616299826861, -0.805175751617057, -0.368078688070326, 
    0.0940935989894723, -0.124454932783893, 0.955750114326398, 
    -0.805175751617057, 0.531190662536203, -0.830250975130125, 
    0.968287726082933, 0.749739194309568, -0.368078688070326, 
    -1.03626189514696, 3.19138587908619, -0.574089608087157, 
    1.67408376842917, -0.586627219843691, -0.343003464557258, 
    -0.162067768053496, 0.325179742519372, -1.24227281516379, 
    -1.03626189514696, 0.749739194309568, 0.325179742519372, 
    0.556265886049271, 0.762276806066102, -0.817713363373591, 
    -0.805175751617057, 0.119168822502541, -0.805175751617057, 
    -0.149530156296961, 0.0940935989894723, -1.48589657045022, 
    1.01843817310907, 0.312642130762837, 1.21191148136937, -0.355541076313792, 
    -1.04879950690349, -0.368078688070326, -0.124454932783893, 
    0.312642130762837, -1.25481042692032, -0.136992544540427, 
    1.01843817310907, -0.124454932783893, -0.368078688070326, 
    -0.805175751617057, 0.081555987232938, -0.805175751617057, 
    0.325179742519372, 2.97283734731282, 0.337717354275906, 0.0690183754764037, 
    -0.136992544540427, -0.830250975130125, 3.03552540609549, 
    0.0940935989894723, 0.0690183754764037, -0.124454932783893, 
    -0.817713363373591, -0.355541076313792, 0.312642130762837, 
    0.980825337839467, -0.343003464557258, 0.993362949596001, 
    -0.586627219843691, -0.574089608087157, -1.02372428339042, 
    -0.561551996330623, -0.111917321027358, -0.136992544540427, 
    -0.149530156296961, -0.830250975130125, 0.568803497805805, 
    0.0690183754764037, -0.805175751617057, -0.830250975130125, 
    0.556265886049271, 0.968287726082933, 0.531190662536203, 
    0.312642130762837, 0.337717354275906, 0.774814417822636, 
    0.337717354275906, 0.337717354275906, -0.586627219843691, 
    0.106631210746007, -1.02372428339042, -0.574089608087157, 
    -0.355541076313792, 0.737201582553033, 0.325179742519372, 
    0.312642130762837, 0.556265886049271, 0.0940935989894723, 
    0.300104519006303, -0.330465852800723, 0.0940935989894723, 
    -0.355541076313792, -0.599164831600226, 0.312642130762837, 
    0.531190662536203, -1.25481042692032, 0.531190662536203, 
    1.89263230020253, -0.817713363373591, -1.02372428339042, 
    0.980825337839467, -0.149530156296961, -0.586627219843691, 
    1.23698670488244, 0.556265886049271, 0.325179742519372, -0.817713363373591, 
    1.01843817310907, -1.02372428339042, -0.805175751617057, 
    -0.355541076313792, 1.67408376842917, 0.0690183754764037, 
    -0.368078688070326, -0.124454932783893, 0.980825337839467, 
    -1.03626189514696, 0.119168822502541, -1.03626189514696, 
    -1.03626189514696, 1.4555352366558, -0.136992544540427, -1.04879950690349, 
    0.749739194309568, -0.792638139860522, 0.312642130762837, 
    -0.0993797092708241, -0.17460537981003, -0.343003464557258, 
    -0.586627219843691, 0.300104519006303, -0.355541076313792, 
    -0.805175751617057, 0.518653050779668, -1.26734803867686, 
    -1.25481042692032, -0.368078688070326, -0.805175751617057, 
    -0.343003464557258, -0.343003464557258, -0.599164831600226, 
    -0.124454932783893, 1.66154615667263, -0.586627219843691, 
    -0.586627219843691, -0.124454932783893, 0.955750114326398, 
    -0.355541076313792, -0.343003464557258, 0.0940935989894723, 
    -0.792638139860522, -0.599164831600226, NA, -0.586627219843691, 
    -1.26734803867686, 0.762276806066102, 1.2244490931259, 0.081555987232938, 
    -0.574089608087157, -1.01118667163389, 0.312642130762837, 
    0.081555987232938, -0.368078688070326, -1.26734803867686, 
    1.63647093315956, -0.368078688070326, 0.531190662536203, 
    0.081555987232938, 0.543728274292737, 0.0564807637198694, 
    0.955750114326398, -1.25481042692032, 1.44299762489927, -1.04879950690349, 
    0.106631210746007, -0.586627219843691, 0.0940935989894723, 
    -0.162067768053496, 0.0940935989894723, -0.111917321027358, 
    0.968287726082933, 0.0940935989894723, 0.312642130762837, 
    -0.586627219843691, 0.543728274292737, -0.124454932783893, 
    0.543728274292737, -0.817713363373591, -0.586627219843691, 
    -0.368078688070326, 0.0940935989894723, -0.599164831600226, 
    -1.03626189514696, 0.774814417822636, 0.106631210746007, 
    -0.111917321027358, -0.817713363373591, -0.330465852800723, 
    0.993362949596001, -0.368078688070326, 1.19937386961283, 
    0.531190662536203, 0.749739194309568, 1.6490085449161, 0.0690183754764037, 
    -0.574089608087157, -0.368078688070326, 1.00590056135254, 
    1.4555352366558, -0.574089608087157, -0.586627219843691, 
    -0.817713363373591, -0.817713363373591, 0.0940935989894723, 
    -0.792638139860522, 0.0690183754764037), format.spss = "F8.2", display_width = 10L)), .Names = c("mompa", 
"momabhx", "mommh", "risk6", "eadiff"), row.names = c(NA, -244L
), class = "data.frame")

这是与4个源变量相同的数据集(depr,anxt,host,bpsipdr1)

> dput(dat3)
structure(list(mompa = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 
1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 
1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 
0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 
0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 
0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 
0, 1, 0, 0), format.spss = "F8.2", display_width = 10L), momabhx = structure(c(1, 
0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 
1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 
0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 
0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 
0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 
0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 
0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 
0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1), format.spss = "F8.2", display_width = 10L), 
    risk6 = structure(c(0, 0, 0, 0, 3, 1, 1, 1, 1, 0, 1, 1, 0, 
    0, 0, 2, 1, 1, 0, 1, 0, 1, 0, 1, 2, 1, 1, 0, 0, 2, 1, 1, 
    2, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 2, 1, 3, 2, 2, 0, 0, 0, 
    2, 0, 2, 2, 1, 2, 2, 1, 3, 2, 3, 1, 1, 0, 1, 3, 1, 2, 2, 
    0, 1, 0, 0, 1, 3, 1, 0, 1, 0, 0, 1, 3, 0, 1, 1, 0, 0, 2, 
    3, 3, 1, 2, 3, 2, 0, 0, 4, 1, 2, 1, 3, 2, 1, 2, 0, 1, 1, 
    2, 1, 1, 0, 0, 0, 0, 0, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 
    NA, 1, 1, 1, 2, 0, NA, 3, 0, 2, 2, 3, 4, 4, 0, 1, 0, 2, 3, 
    2, 2, 2, 2, 1, 3, 2, 2, 3, 1, 1, 1, 0, 0, 1, 1, 0, 2, 0, 
    1, 2, 3, 1, 1, 1, 2, 1, 2, 0, 0, 2, 2, 0, 1, 2, 0, 0, 2, 
    1, 1, 1, 1, 1, 3, 1, 0, 3, 0, 1, 0, 1, 1, 1, 2, 2, 0, 2, 
    3, 3, 0, 0, 0, 1, 2, 1, 1, 1, 0, 1, 1, 3, 1, 1, 0, 0, 3, 
    2, 0, 0, 3, 2, 1, 3, 1, 0, 3, 0, 1, 1, 2, 3, 3, 1, 4, 2, 
    3, 2, 2), format.spss = "F8.2", display_width = 10L), eadiff = structure(c(-1.26734803867686, 
    -0.355541076313792, 0.518653050779668, 1.50568568368194, 
    0.0940935989894723, 2.07356799670629, 1.01843817310907, -1.26734803867686, 
    -0.317928241044189, 0.531190662536203, 0.0940935989894723, 
    -1.47335895869369, -0.586627219843691, -1.26734803867686, 
    0.325179742519372, 0.556265886049271, 1.4179224013862, 1.2244490931259, 
    -0.586627219843691, 0.081555987232938, -0.149530156296961, 
    -0.380616299826861, -0.805175751617057, -0.368078688070326, 
    0.0940935989894723, -0.124454932783893, 0.955750114326398, 
    -0.805175751617057, 0.531190662536203, -0.830250975130125, 
    0.968287726082933, 0.749739194309568, -0.368078688070326, 
    -1.03626189514696, 3.19138587908619, -0.574089608087157, 
    1.67408376842917, -0.586627219843691, -0.343003464557258, 
    -0.162067768053496, 0.325179742519372, -1.24227281516379, 
    -1.03626189514696, 0.749739194309568, 0.325179742519372, 
    0.556265886049271, 0.762276806066102, -0.817713363373591, 
    -0.805175751617057, 0.119168822502541, -0.805175751617057, 
    -0.149530156296961, 0.0940935989894723, -1.48589657045022, 
    1.01843817310907, 0.312642130762837, 1.21191148136937, -0.355541076313792, 
    -1.04879950690349, -0.368078688070326, -0.124454932783893, 
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0 个答案:

没有答案