So I've been trying to run this imputation of the hecknorm2step. I already have the selection function (probit) runned and performed really well. I've been trying the follow the guide of this 5-year, CRAN remove package that is mice.impute.hecknorm2step, and I did everything as requested. However, when I finally try to run the imputation, the error comes as follows:
Error in str2lang(x) : <text>:2:0: unexpected end of input 1: y~
It doesn't even run the first imputation, so I'm wondering if there is something wrong with the method or if it's just the nature of my data. (It has many NA's on some of the other variables, since they are created). I'm also wondering if there is a way to apply the survey weights during the imputation.
library(sampleSelection)
library(miceMNAR)
base_imput <- data.frame(lnwhour,hombre, yearschl,yearschl2,
exp, exp2, ttrabajo, urban, region,
asal, casado,hombre_casado, edad, edad2,
dnuclear,duniper,monopar, dnuclearsinh, pninos0a17,
pam, ss, fac_men, est_d)
JointModelEq <- generate_JointModelEq(data = base_imput, varMNAR = "lnwhour")
JointModelEq[, "asal_var_sel"] <- c(0,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0)
JointModelEq[, "lnwhour_var_sel"] <- c(0,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
arg <- MNARargument(data = base_imput, varMNAR = "lnwhour", JointModelEq = JointModelEq)
arg$method["lnwhour"] <- "hecknorm2step"
#Proceso de imputacion
imputacionheck <- mice(data = arg$data_mod,
method = arg$method,
predictorMatrix = arg$predictorMatrix,
JointModelEq = arg$JointModelEq,
control = arg$control,
weights = fac_men,
maxit = 1, m = 5,
seed = 1984 #para reproducibilidad
)
Removing the weights thing doesn't work, so I think it's something more to that. When running traceback I get this
9: str2lang(x)
8: formula.character(object, env = baseenv())
7: formula(object, env = baseenv())
6: as.formula(paste("y~", paste(var_out, collapse = "+"), sep = ""))
5: mice.impute.hecknorm2step(y = c(0, 2.80171478523213, 3.03655410807423,
3.53332825234684, 3.50655779731998, 0, 3.65738078905457, 3.44201937618241,
3.77849161280362, 0, 3.65738078905457, 0, 4.8283137373023, 0,
3.65738078905457, 3.40119738166216, 3.2188758248682, 0, 3.65738078905457,
3.61655873003431, 3.2188758248682, 3.17805383034795, 0, 0, 0,
0, 3.09776480761912, 3.28786853635514, 3.04452243772342, 3.28341447100576,
0, 3.50655779731998, 3.16278620437099, 0, 0, 3.07756245965875,
0, 3.58351893845611, 0, 4.27795722961838, 0, 0, 0, 0, 0, 0, 0,
0, 2.56494935746154, 0, 3.62434093297637, 0, 3.81193965213432,
3.95124371858143, 3.68887945411394, 0, 4.19970512787993, 0, 0,
3.76274125311239, 0, 0, 4.06617362811255, 4.82053161498525, 0,
0, 3.91202300542815, 0, 4.27666611901606, 0, 0, 0, 0, 3.68887945411394,
0, 4.35052796961451, 3.94506292600634, 0, 4.39931814606966, 3.54737982784023,
4.06284581116273, 0, 3.43423717324035, 0, 0, 0, 0, 0, 0, 3.28786853635514,
3.91202300542815, 3.2188758248682, 0, 3.2188758248682, 3.91202300542815,
3.42139992897966, 0, 3.6119184929778, 0, 0, 3.18737731460882,
0, 0, 0, 0, 3.91202300542815, 3.48457912393453, 4.83823119632807,
3.13186459333311, 0, 0, 4.00733318523247, 0, 3.18292279103088,
2.99573227355399, 0, 0, 0, 0, 0, 0, 3.61655873003431, 4.1581561004216,
0, 3.08534443224368, 3.79423986977176, 4.39931814606966, 0, 0,
...
4: do.call(f, args = args)
3: sampler.univ(data = data, r = r, where = where, type = type,
formula = ff, method = theMethod, yname = j, k = k, calltype = calltype,
user = user, ignore = ignore, ...)
2: sampler(data, m, ignore, where, imp, blocks, method, visitSequence,
predictorMatrix, formulas, blots, post, c(from, to), printFlag,
...)
1: mice(data = arg$data_mod, method = arg$method, predictorMatrix = arg$predictorMatrix,
JointModelEq = arg$JointModelEq, control = arg$control, weights = fac_men,
maxit = 1, m = 5, seed = 1984)
I've been knocking my head over this for a week now, and I don't want to resort to learning Stata (because a professor told me the methodology is quite straightforward there)
Here I leave a sample of the 750k observation data frame for it to be reproducible.
Thank you very much in advance.
structure(list(lnwhour = c(3.62434093297637, NA, NA, 0, NA, NA,
NA, NA, NA, NA, 0, 0, 0, NA, NA, NA, NA, NA, 0, NA, NA, NA, 3.36969880260278,
0, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 3.05694307647388, 0,
NA, 0, NA, 3.9528449359484, 0, NA, 3.43756499011874, NA, NA,
3.29891840946481, NA, NA, NA, NA, NA, NA, 4.19970512787993, NA,
NA, NA, 3.01635172402202, 0, NA, NA, NA, 0, 3.62434093297637,
NA, NA, NA, 3.86946346057457, NA, NA, 3.32423642052602, NA, 3.32887683674919,
0, NA, 4.01738360108597, 0, 4.1581561004216, NA, NA, NA, NA,
NA, NA, 4.30667721917122, NA, 4.60517018598809, NA, NA, NA, 0,
NA, NA, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, 3.36916511626451,
NA, NA, NA, NA, NA, NA, 3.70617084265256, NA, 3.91202300542815,
NA, 3.9528449359484, 3.62434093297637, NA, NA, NA, 3.25191555194639,
NA, NA, 0, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, 3.66690042517293,
NA, 3.78942070072712, NA, 4.2584126162067, NA, 3.50655779731998,
NA, NA, NA, 3.95458256151361, 3.28341447100576, NA, NA, NA),
hombre = structure(c(2L, NA, 2L, 2L, 1L, 2L, 2L, 2L, NA,
2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L,
2L, 1L, 1L, 2L, NA, 1L, NA, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L,
2L, 1L, NA, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L,
1L, 2L, 1L, 1L, 2L, 1L, NA, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, NA, 1L, NA, 1L, 2L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, NA, 2L, 1L, NA, 1L, 1L, 1L,
NA, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L,
2L, 2L, 2L, NA, 1L, 1L, 2L, 2L, NA, 1L, 2L, 1L, 1L, 2L, 1L,
1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
2L, 2L, 1L, 1L, 2L, 2L), levels = c("0", "1"), class = "factor"),
yearschl = c(11, NA, 6, 12, 9, 12, 3, 0, NA, 12, 9, 12, 6,
0, 13, 0, 9, 0, 12, 11, 0, 9, 9, 11, 8, 9, 0, 6, NA, 12,
NA, 21, 5, 7, 3, 15, 11, 9, 19, 4, 16, NA, 9, 0, 16, 9, 7,
6, 9, 6, 0, 6, 16, 0, 0, 0, 12, 9, 9, 9, NA, 13, 8, 4, 10,
0, 8, 5, 6, 12, 0, 9, 17, 0, 16, 15, 17, NA, 13, NA, 0, 0,
6, 12, 6, 12, 9, 0, 10, 9, 12, 5, 0, 6, 6, 0, 12, 15, 9,
0, 6, 0, 17, 0, 16, 10, 17, 9, 0, 6, 0, 11, 0, 9, 18, 9,
6, NA, 6, 10, 12, 16, NA, 16, 0, 10, 7, 12, 11, 12, 0, 11,
17, 9, 13, 9, 9, 11, 16, 17, 12, 12, 0, 16, 6, 17, 9, 12,
15, 0), yearschl2 = c(121, NA, 36, 144, 81, 144, 9, 0, NA,
144, 81, 144, 36, 0, 169, 0, 81, 0, 144, 121, 0, 81, 81,
121, 64, 81, 0, 36, NA, 144, NA, 441, 25, 49, 9, 225, 121,
81, 361, 16, 256, NA, 81, 0, 256, 81, 49, 36, 81, 36, 0,
36, 256, 0, 0, 0, 144, 81, 81, 81, NA, 169, 64, 16, 100,
0, 64, 25, 36, 144, 0, 81, 289, 0, 256, 225, 289, NA, 169,
NA, 0, 0, 36, 144, 36, 144, 81, 0, 100, 81, 144, 25, 0, 36,
36, 0, 144, 225, 81, 0, 36, 0, 289, 0, 256, 100, 289, 81,
0, 36, 0, 121, 0, 81, 324, 81, 36, NA, 36, 100, 144, 256,
NA, 256, 0, 100, 49, 144, 121, 144, 0, 121, 289, 81, 169,
81, 81, 121, 256, 289, 144, 144, 0, 256, 36, 289, 81, 144,
225, 0), exp = c(3, NA, 58, 22, 25, 6, 53, -3, NA, 19, 39,
10, 13, 3, 1, 58, 34, 1, 11, 0, 79, 42, 1, 16, 59, 34, 2,
0, NA, 25, NA, 28, 57, 1, 71, 3, 20, 48, 45, 37, 42, NA,
35, 3, 40, 12, 0, 4, 62, 25, 43, 1, 5, 2, -2, -1, 2, 36,
29, 29, NA, 2, 26, 74, 1, 3, 44, 1, 32, 15, 5, 5, 5, 0, 12,
1, 7, NA, 1, NA, -4, -3, 42, 31, 43, 20, 29, 3, 0, 45, 53,
2, NA, 0, 33, NA, 6, 1, 22, NA, 42, -5, 0, 40, 7, 13, 20,
0, 4, 0, 2, 16, 5, 24, 37, 12, 21, NA, 2, 1, 38, 35, NA,
7, -2, 1, 0, 63, 5, 20, 35, 0, 3, 1, 1, 15, 33, 17, 13, 1,
28, 23, 0, 2, 60, 3, 12, 25, 4, -3), exp2 = c(9, NA, 3364,
484, 625, 36, 2809, 9, NA, 361, 1521, 100, 169, 9, 1, 3364,
1156, 1, 121, 0, 6241, 1764, 1, 256, 3481, 1156, 4, 0, NA,
625, NA, 784, 3249, 1, 5041, 9, 400, 2304, 2025, 1369, 1764,
NA, 1225, 9, 1600, 144, 0, 16, 3844, 625, 1849, 1, 25, 4,
4, 1, 4, 1296, 841, 841, NA, 4, 676, 5476, 1, 9, 1936, 1,
1024, 225, 25, 25, 25, 0, 144, 1, 49, NA, 1, NA, 16, 9, 1764,
961, 1849, 400, 841, 9, 0, 2025, 2809, 4, NA, 0, 1089, NA,
36, 1, 484, NA, 1764, 25, 0, 1600, 49, 169, 400, 0, 16, 0,
4, 256, 25, 576, 1369, 144, 441, NA, 4, 1, 1444, 1225, NA,
49, 4, 1, 0, 3969, 25, 400, 1225, 0, 9, 1, 1, 225, 1089,
289, 169, 1, 784, 529, 0, 4, 3600, 9, 144, 625, 16, 9), ttrabajo = c(24,
NA, 0, 54, 0, 0, 5, 0, NA, 0, 8, 36, 48, 0, 0, 0, 0, 0, 77,
0, 0, 0, 48, 51, 0, 0, 0, 0, NA, 48, NA, 32, 0, 0, 35, 44,
0, 20, 0, 48, 40, NA, 45, 0, 57, 48, 0, 0, 0, 0, 0, 0, 48,
0, 0, 0, 48, 20, 0, 0, NA, 72, 48, 0, 0, 0, 48, 0, 40, 54,
0, 40, 40, 0, 45, 2, 40, NA, 0, NA, 0, 0, 0, 31, 0, 5, 21,
0, 0, 25, 0, 0, 0, 0, 0, 0, 45, 0, 0, 0, 0, 0, 0, 0, 30,
0, 0, 0, 0, 0, 0, 40, 0, 12, 0, 48, 48, NA, 0, 0, 54, 32,
NA, 56, 0, 0, 0, 20, 0, 0, 0, 112, 0, 0, 0, 46, 0, 52, 6,
25, 0, 45, 0, 0, 0, 46, 45, 12, 0, 0), urban = structure(c(2L,
1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L,
2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L), levels = c("0",
"1"), class = "factor"), region = structure(c(2L, 3L, 3L,
3L, 4L, 3L, 2L, 4L, 3L, 3L, 1L, 2L, 4L, 1L, 3L, 4L, 3L, 3L,
2L, 2L, 4L, 2L, 3L, 1L, 1L, 3L, 2L, 2L, 1L, 4L, 3L, 1L, 1L,
4L, 4L, 3L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 1L, 3L, 1L, 3L, 1L,
4L, 4L, 2L, 3L, 3L, 3L, 3L, 2L, 4L, 2L, 4L, 1L, 2L, 1L, 2L,
1L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 4L, 2L, 2L,
2L, 1L, 3L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 4L, 2L, 2L, 1L, 4L,
3L, 4L, 3L, 1L, 1L, 1L, 4L, 1L, 1L, 2L, 4L, 4L, 1L, 3L, 4L,
1L, 2L, 4L, 3L, 3L, 1L, 3L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 3L,
3L, 4L, 1L, 3L, 2L, 3L, 4L, 1L, 1L, 4L, 1L, 4L, 3L, 2L, 3L,
3L, 2L, 1L, 3L, 4L, 4L, 1L, 3L, 2L, 2L, 1L, 3L), levels = c("1",
"2", "3", "4"), class = "factor"), asal = c(1, NA, NA, 1,
NA, NA, 0, NA, NA, NA, 0, 0, 0, NA, NA, NA, NA, NA, 0, NA,
NA, NA, 1, 1, NA, NA, NA, NA, NA, 0, NA, 1, NA, NA, 1, 1,
NA, 1, NA, 1, 0, NA, 1, NA, 0, 1, NA, NA, NA, NA, NA, NA,
1, NA, NA, NA, 1, 0, NA, NA, NA, 1, 1, NA, NA, NA, 1, NA,
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NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, 1, NA, 1, NA, 1, 1,
NA, NA, NA, 1, 1, NA, 0, NA, NA, NA, 1, NA, NA, NA, 0, NA,
NA, NA, 1, NA, 1, 0, 1, NA, 1, NA, NA, NA, 1, 1, 0, NA, NA
), casado = structure(c(1L, NA, 2L, 1L, 2L, 1L, 2L, NA, NA,
2L, 2L, 1L, 2L, NA, 1L, 2L, 2L, NA, 1L, 1L, 2L, 2L, 1L, 1L,
1L, 2L, NA, 1L, NA, 1L, NA, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L,
2L, 2L, NA, 2L, NA, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, NA,
NA, NA, 1L, 2L, 2L, 2L, NA, 1L, 2L, 2L, 1L, NA, 2L, 1L, 2L,
2L, NA, 2L, 1L, NA, 1L, 1L, 1L, NA, 1L, NA, NA, NA, 2L, 2L,
2L, 1L, 2L, NA, 1L, 2L, 2L, 1L, NA, 1L, 1L, NA, 1L, 1L, 2L,
NA, 2L, NA, 1L, 1L, 1L, 2L, 1L, 1L, NA, 1L, NA, 2L, NA, 2L,
2L, 2L, 2L, NA, 1L, 1L, 2L, 2L, NA, 1L, NA, 1L, 1L, 2L, 1L,
2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, NA, 1L,
2L, 1L, 2L, 1L, 1L, NA), levels = c("0", "1"), class = "factor"),
hombre_casado = structure(c(1L, NA, 2L, 1L, 1L, 1L, 2L, NA,
NA, 2L, 2L, 1L, 2L, NA, 1L, 1L, 1L, NA, 1L, 1L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, NA, 1L, NA, 2L, 1L, 1L, 1L, 1L, 2L, 1L,
1L, 2L, 1L, NA, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, NA, 1L, 1L, 2L, 1L, NA, 1L, 2L, 2L, 1L, NA, 2L, 1L,
2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 1L, NA, 1L, NA, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, NA, 1L, 1L, NA, 1L, 1L,
1L, NA, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA,
1L, 2L, 2L, 2L, NA, 1L, 1L, 2L, 2L, NA, 1L, NA, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L,
1L, 2L, 1L, 1L, 1L, 1L, NA), levels = c("0", "1"), class = "factor"),
edad = c(20, NA, 70, 40, 40, 24, 62, 3, NA, 37, 54, 28, 25,
9, 20, 64, 49, 7, 29, 17, 85, 57, 16, 33, 73, 49, 8, 12,
NA, 43, NA, 55, 68, 14, 80, 24, 37, 63, 70, 47, 64, NA, 50,
9, 62, 27, 13, 16, 77, 37, 49, 13, 27, 8, 4, 5, 20, 51, 44,
44, NA, 21, 40, 84, 17, 9, 58, 12, 44, 33, 11, 20, 28, 6,
34, 22, 30, NA, 20, NA, 2, 3, 54, 49, 55, 38, 44, 9, 16,
60, 71, 13, NA, 12, 45, NA, 24, 22, 37, NA, 54, 1, 23, 46,
29, 29, 43, 15, 10, 12, 8, 33, 11, 39, 61, 27, 33, NA, 14,
17, 56, 57, NA, 29, 4, 17, 13, 81, 22, 38, 41, 17, 26, 16,
20, 30, 48, 34, 35, 24, 46, 41, 6, 24, 72, 26, 27, 43, 25,
3), edad2 = c(400, NA, 4900, 1600, 1600, 576, 3844, 9, NA,
1369, 2916, 784, 625, 81, 400, 4096, 2401, 49, 841, 289,
7225, 3249, 256, 1089, 5329, 2401, 64, 144, NA, 1849, NA,
3025, 4624, 196, 6400, 576, 1369, 3969, 4900, 2209, 4096,
NA, 2500, 81, 3844, 729, 169, 256, 5929, 1369, 2401, 169,
729, 64, 16, 25, 400, 2601, 1936, 1936, NA, 441, 1600, 7056,
289, 81, 3364, 144, 1936, 1089, 121, 400, 784, 36, 1156,
484, 900, NA, 400, NA, 4, 9, 2916, 2401, 3025, 1444, 1936,
81, 256, 3600, 5041, 169, NA, 144, 2025, NA, 576, 484, 1369,
NA, 2916, 1, 529, 2116, 841, 841, 1849, 225, 100, 144, 64,
1089, 121, 1521, 3721, 729, 1089, NA, 196, 289, 3136, 3249,
NA, 841, 16, 289, 169, 6561, 484, 1444, 1681, 289, 676, 256,
400, 900, 2304, 1156, 1225, 576, 2116, 1681, 36, 576, 5184,
676, 729, 1849, 625, 9), dnuclear = structure(c(NA, NA, 1L,
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2L, 1L, 2L, 1L, 1L, 1L, NA, 1L, NA, 1L, NA, NA, 1L, NA, 1L,
1L, 2L, 1L, NA, 1L, 1L, 1L, NA, NA, NA, 1L, 1L, NA, 1L, 1L,
1L, NA, NA, NA, 1L, 1L, 1L, 2L, 2L, 2L, 1L, NA, 1L, 2L, NA,
2L, NA, 2L, 1L, 1L, NA, 1L, 1L, 2L, 1L, 1L, 1L, 1L, NA, NA,
1L, NA, NA, 1L, 2L, NA, NA, 1L, 1L, NA, 1L, NA, NA, 1L, 1L,
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1L, 2L, NA, NA, NA, 2L, 2L, NA, 1L, 1L, NA, 1L, 1L, 1L, 1L,
1L, 1L, NA, NA, NA, 1L, 1L, NA, NA, 1L, NA, 1L), levels = c("0",
"1"), class = "factor"), duniper = structure(c(1L, NA, 2L,
1L, 1L, 1L, 2L, 1L, NA, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
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1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, NA, 1L, 1L, NA, 1L, 1L, 1L,
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