0

Apologies if this is a simple solution, but I am trying to figure out how to resolve this.

I am trying to impute multi-level data, where level 1 predictors have missing values. (see sample at the end)

In doing imputation the states (level 2 cluster variable) are coded as integers for mice.

#prepping
ini <- mice(df2, maxit = 0)
predMatrix <- make.predictorMatrix(data = df2)

#marking astate as cluster variable
predMatrix[,"astate"]<--2

#Making df2$astate integer
df2$astate <- as.factor(df2$astate)
df2$astate <- as.integer(df2$astate)

#Imputating lvl1 predictors 
impMethod<-rep("2l.pmm",ncol(predMatrix))
names(impMethod)<-names(df2)

##Imputation Method
imice <- mice(df2, m = 10, predictorMatrix = predMatrix, maxit = 20, meth=impMethod, printFlag = F)

When I try to run the imputation method I get this error

iteration 1
iteration 2
Error in sort.int(d, partial = donors) : index 5 outside bounds
In addition: Warning message:
In runif(length(d), 0, a1/10^10) : NAs produced

Traceback shows:

8: sort.int(d, partial = donors)
7: FUN(newX[, i], ...)
6: apply(as.array(yhatmis), 1, .pmm.match, yhat = yhatobs, y = y[ry], 
       donors = donors, ...)
5: mice.impute.2l.pmm(y = c(30.38, 0.3, 60.71, 39.88, 0.09, 0.4, 
   8.6, 19.4, 14, 35.52, 39.93, 0.98, 9.5, 32.24, 26.66, 0.9, 1.3, 
   0.6, 0.38, 4.86, 22.6, 0.55, 6.12, 5.25, 3.77, 1.53, 8.56, 17.35, 
   29.68, 23.01, 24.65, 43.59, 3.3, 8.24, 0.23, 8, 16.17, 55.3, 
   8.5, 4.29, 9.13, 4.02, 35.7, 11.68, 2.72, 40.9, 0.07, 0.5, 2.58, 
   20.01, 6.11, 17.79, 33.5, 17.9, 0.88, 4.54, 12.92, 14.17, 17.79, 
   60.19, 0.32, 27.5, 4.35, 2.05, 5, 25.91, 23.3, 5.78, 7.65, 0.3, 
   0.3, 5.78, 1.74, 13.5, 0.2, 0.07, 4.3, 1.83, 0.8, 27.89, 0.03, 
   0.08, 0.13, 34.3, 0.5, 20.6, 6.07, 0.3, 17.9, 6.06, 0.4, 1.7, 
   55.3, 8.69, 0.06, 0.03, 53.03, 0.3, 20.6, 3.38, 5.94, 34.22, 
   0.19, 0.2, 0.1, 0.8, 31.5, 24, 0.2, 15.52, 0.12, 12.37, 24.8, 
   28.08, 25.35, 25, 0.98, 0.1, 2.13, 1.04, 7.48, 0.62, 0, 0.1, 
   5.95, 2.6, 0.61, 46.4, 13.6, 0.41, 1.61, 22.58, 13.44, 3.86, 
   0.4, 3.3, 0.3, 3.06, 0.2, 4.46, 5.61, 11.2, 0.62, 0.07, 2.52, 
   2.13, 0.9, 0.95, 2.57, 22.7, 0, 0.2, 4.51, 22.5, 0.38, 8.69, 
   30.2, 20.6, 0.02, 1.57, 4.39, 1.3, 0.3, 4.9, 0.68, 26, 1.5, 0.02, 
   1.26, 5.81, 0.73, 37.31, 2.5, 4.69, 16.33, 41.1, 1.37, 0.1, 0.5, 
   26, 2.59, 3.62, 1.36, 8.47, 1, 1, 12.34, 18.3, 0.8, 2.26, 42.11, 
   4.25, 0.45, 1.1, 7.13, 0.8, 1.83, 6.13, 0.2, 5.84, 4.1, 4.7, 
   0, 0.1, 5.22, 0.57, 3.46, 0.1, 0.14, 0.3, 15.59, 35.01, 2.28, 
    ...
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(df2, m = 10, predictorMatrix = predMatrix, maxit = 20, meth = impMethod, 
       printFlag = F)

Not sure where to go from here since I am not the best at R.

  1. I tried sorting astate variable in different ways.

  2. Other methods like 2l.norm, 2l.pan work, but I've been trying to resolve this issue to see if the imputation method works better.

  3. I've done quickpred and tried removing variables/rearranging them

Any help here is appreciated on what I need to do to impute using 2l.pmm. If I missed something please let me know.

Here is a sample of the data for anyone to try to reproduce the problem:

structure(list(astate = c("Aberdeen, South Dakota", "Aberdeen, South Dakota", 
"Aberdeen, South Dakota", "Aberdeen, South Dakota", "Abilene, Texas", 
"Abilene, Texas", "Abilene, Texas", "Abilene, Texas", "Addison, Illinois", 
"Addison, Illinois", "Addison, Illinois", "Addison, Illinois", 
"Akron, Ohio", "Akron, Ohio", "Akron, Ohio", "Akron, Ohio", "Alameda, California", 
"Alameda, California", "Alameda, California", "Alameda, California", 
"Albany, Georgia", "Albany, Georgia", "Albany, Georgia", "Albany, Georgia", 
"Albany, New York", "Albany, New York", "Albany, New York", "Albany, New York", 
"Albuquerque, New Mexico", "Albuquerque, New Mexico", "Albuquerque, New Mexico", 
"Albuquerque, New Mexico", "Alexandria, Louisiana", "Alexandria, Louisiana", 
"Alexandria, Louisiana", "Alexandria, Louisiana", "Alexandria, Virginia", 
"Alexandria, Virginia", "Alexandria, Virginia", "Alexandria, Virginia", 
"Alhambra, California", "Alhambra, California", "Alhambra, California", 
"Alhambra, California", "Aliquippa, Pennsylvania", "Aliquippa, Pennsylvania", 
"Aliquippa, Pennsylvania", "Aliquippa, Pennsylvania", "Allen Park, Michigan", 
"Allen Park, Michigan", "Allen Park, Michigan", "Allen Park, Michigan", 
"Allentown, Pennsylvania", "Allentown, Pennsylvania", "Allentown, Pennsylvania", 
"Allentown, Pennsylvania", "Alton, Illinois", "Alton, Illinois", 
"Alton, Illinois", "Alton, Illinois", "Altoona, Pennsylvania", 
"Altoona, Pennsylvania", "Altoona, Pennsylvania", "Altoona, Pennsylvania", 
"Amarillo, Texas", "Amarillo, Texas", "Amarillo, Texas", "Amarillo, Texas", 
"Ames, Iowa", "Ames, Iowa", "Ames, Iowa", "Ames, Iowa", "Anaheim, California", 
"Anaheim, California", "Anaheim, California", "Anaheim, California", 
"Anchorage, Alaska", "Anchorage, Alaska", "Anchorage, Alaska", 
"Anchorage, Alaska", "Anderson, Indiana", "Anderson, Indiana", 
"Anderson, Indiana", "Anderson, Indiana", "Anderson, South Carolina", 
"Anderson, South Carolina", "Anderson, South Carolina", "Anderson, South Carolina", 
"Ann Arbor, Michigan", "Ann Arbor, Michigan", "Ann Arbor, Michigan", 
"Ann Arbor, Michigan", "Annapolis, Maryland", "Annapolis, Maryland", 
"Annapolis, Maryland", "Annapolis, Maryland", "Anniston, Alabama", 
"Anniston, Alabama", "Anniston, Alabama", "Anniston, Alabama", 
"Antioch, California", "Antioch, California", "Antioch, California", 
"Antioch, California", "Appleton, Wisconsin", "Appleton, Wisconsin", 
"Appleton, Wisconsin", "Appleton, Wisconsin", "Arcadia, California", 
"Arcadia, California", "Arcadia, California", "Arcadia, California", 
"Arlington Heights, Illinois", "Arlington Heights, Illinois", 
"Arlington Heights, Illinois", "Arlington Heights, Illinois", 
"Arlington Town Mass, Massachusetts", "Arlington Town Mass, Massachusetts", 
"Arlington Town Mass, Massachusetts", "Arlington Town Mass, Massachusetts", 
"Arlington, Texas", "Arlington, Texas", "Arlington, Texas", "Arlington, Texas", 
"Arvada, Colorado", "Arvada, Colorado", "Arvada, Colorado", "Arvada, Colorado", 
"Asheville, North Carolina", "Asheville, North Carolina", "Asheville, North Carolina", 
"Asheville, North Carolina", "Ashland, Kentucky", "Ashland, Kentucky", 
"Ashland, Kentucky", "Ashland, Kentucky", "Athens, Georgia", 
"Athens, Georgia", "Athens, Georgia", "Athens, Georgia", "Atlanta, Georgia", 
"Atlanta, Georgia", "Atlanta, Georgia", "Atlanta, Georgia", "Atlantic City, New Jersey", 
"Atlantic City, New Jersey", "Atlantic City, New Jersey", "Atlantic City, New Jersey", 
"Auburn, Alabama", "Auburn, Alabama", "Auburn, Alabama", "Auburn, Alabama", 
"Auburn, New York", "Auburn, New York", "Auburn, New York", "Auburn, New York", 
"Augusta, Georgia", "Augusta, Georgia", "Augusta, Georgia", "Augusta, Georgia", 
"Aurora, Colorado", "Aurora, Colorado", "Aurora, Colorado", "Aurora, Colorado", 
"Aurora, Illinois", "Aurora, Illinois", "Aurora, Illinois", "Aurora, Illinois", 
"Austin, Texas", "Austin, Texas", "Austin, Texas", "Austin, Texas", 
"Azusa, California", "Azusa, California", "Azusa, California", 
"Azusa, California", "Bakersfield, California", "Bakersfield, California", 
"Bakersfield, California", "Bakersfield, California", "Baldwin Park, California", 
"Baldwin Park, California", "Baldwin Park, California", "Baldwin Park, California", 
"Baltimore, Maryland", "Baltimore, Maryland", "Baltimore, Maryland", 
"Baltimore, Maryland", "Bangor, Maine", "Bangor, Maine", "Bangor, Maine", 
"Bangor, Maine", "Barberton, Ohio", "Barberton, Ohio", "Barberton, Ohio", 
"Barberton, Ohio", "Baton Rouge, Louisiana", "Baton Rouge, Louisiana", 
"Baton Rouge, Louisiana", "Baton Rouge, Louisiana", "Battle Creek, Michigan", 
"Battle Creek, Michigan", "Battle Creek, Michigan", "Battle Creek, Michigan", 
"Bay City, Michigan", "Bay City, Michigan", "Bay City, Michigan", 
"Bay City, Michigan", "Bayonne, New Jersey", "Bayonne, New Jersey", 
"Bayonne, New Jersey", "Bayonne, New Jersey", "Baytown, Texas", 
"Baytown, Texas", "Baytown, Texas", "Baytown, Texas", "Beaumont, Texas", 
"Beaumont, Texas", "Beaumont, Texas", "Beaumont, Texas", "Bell Gardens, California", 
"Bell Gardens, California", "Bell Gardens, California", "Bell Gardens, California", 
"Belleville, Illinois", "Belleville, Illinois", "Belleville, Illinois", 
"Belleville, Illinois", "Belleville, New Jersey", "Belleville, New Jersey", 
"Belleville, New Jersey", "Belleville, New Jersey", "Bellevue, Washington", 
"Bellevue, Washington", "Bellevue, Washington", "Bellevue, Washington", 
"Bellflower, California", "Bellflower, California", "Bellflower, California", 
"Bellflower, California", "Bellingham, Washington", "Bellingham, Washington", 
"Bellingham, Washington", "Bellingham, Washington", "Belmont Town Mass, Massachusetts", 
"Belmont Town Mass, Massachusetts", "Belmont Town Mass, Massachusetts", 
"Belmont Town Mass, Massachusetts", "Beloit, Wisconsin", "Beloit, Wisconsin", 
"Beloit, Wisconsin", "Beloit, Wisconsin", "Bergenfield, New Jersey", 
"Bergenfield, New Jersey", "Bergenfield, New Jersey", "Bergenfield, New Jersey", 
"Berkeley, California", "Berkeley, California", "Berkeley, California", 
"Berkeley, California", "Berwyn, Illinois", "Berwyn, Illinois", 
"Berwyn, Illinois", "Berwyn, Illinois", "Bessemer, Alabama", 
"Bessemer, Alabama", "Bessemer, Alabama", "Bessemer, Alabama", 
"Bethel Park, Pennsylvania", "Bethel Park, Pennsylvania", "Bethel Park, Pennsylvania", 
"Bethel Park, Pennsylvania", "Bethlehem, Pennsylvania", "Bethlehem, Pennsylvania", 
"Bethlehem, Pennsylvania", "Bethlehem, Pennsylvania", "Beverly Hills, California", 
"Beverly Hills, California", "Beverly Hills, California", "Beverly Hills, California", 
"Beverly, Massachusetts", "Beverly, Massachusetts", "Beverly, Massachusetts", 
"Beverly, Massachusetts", "Billings, Montana", "Billings, Montana", 
"Billings, Montana", "Billings, Montana", "Biloxi, Mississippi", 
"Biloxi, Mississippi", "Biloxi, Mississippi", "Biloxi, Mississippi", 
"Binghamton, New York", "Binghamton, New York", "Binghamton, New York", 
"Binghamton, New York", "Birmingham, Alabama", "Birmingham, Alabama", 
"Birmingham, Alabama", "Birmingham, Alabama"), pbp = c(NA, NA, 
0, 0.13, 4.82, 4.9, 5.8, 6.75, NA, NA, 0.1, 0.88, 8.65, 13, 17.5, 
22.19, 8.24, 4.9, 2.6, 4.17, 42.83, 36.2, 37.9, 47.5, 4.27, 8.3, 
12.2, 15.93, 1.26, 1.8, 2.2, 2.32, 41.43, 43.3, 36.3, 47.81, 
12.34, 11.4, 14.1, 22.35, 0.23, 0.2, 0.3, 1.04, NA, NA, NA, NA, 
NA, 0.2, 0.1, 0.44, 0.43, 0.7, 1.8, 3.06, 11.8, 11.5, 16.2, 20.69, 
0.89, 1.1, 1.3, 1.63, 4.84, 5.6, 5.3, 5.51, NA, 0.4, 0.8, 1.83, 
NA, NA, 0.1, 1.24, NA, 5.1, 2.2, 5.38, 4.85, 8.8, 10.2, 13.71, 
NA, 20.1, 25.7, 29.47, 4.5, 4.7, 6.7, 9.43, NA, NA, 29, NA, 30.38, 
33.9, 34.5, 40.3, NA, NA, 0.1, 1.44, 0.01, NA, 0.1, 0.06, NA, 
0.1, 0.1, 0.21, NA, NA, 0, 0.56, NA, NA, NA, NA, NA, 0.8, 0.6, 
2.82, NA, NA, 0.1, 0.37, 23.46, 19, 17.1, 21.25, 2.51, 2.6, 2.4, 
2.15, 27.3, 29.1, 23.1, 27.35, 36.61, 38.3, 51.5, 66.62, 27.22, 
36.2, 43.7, 49.58, NA, NA, 16.9, 16.1, 2.46, 3.5, 4.8, 5.37, 
40.98, 45, 49.9, 53.5, NA, 0.6, 1.2, 6.83, 2.28, 3.5, 6.5, 10.4, 
13.34, 13.1, 11.7, 12.19, NA, NA, 0.1, 1.66, 4.29, 14.5, 13.3, 
10.49, NA, 0.1, 0.5, 1.04, 23.7, 34.7, 46.4, 54.77, 0.63, 1.7, 
0.9, 0.44, 4.28, 4.4, 3.8, 3.86, 27.95, 29.8, 28.7, 36.39, 7.99, 
14.9, 20, 22.63, 0.62, 1.1, 1.4, 1.47, 2.37, 3.2, 4.3, 4.11, 
NA, 6.7, 4.9, 8.76, 29.33, 29.3, 30.2, 36.61, NA, NA, 0.1, 0.3, 
0.6, 0.5, 0.6, 1.98, 2.43, 2.1, 2.3, 2.64, NA, NA, 0.6, 1.36, 
NA, NA, 0, 1.61, 0.09, 0.1, 0.3, 0.41, NA, NA, NA, NA, 4.65, 
6.4, 7.3, 11.34, NA, 0.1, 0.5, 1.9, 11.68, 19.6, 24, 20.01, 0.01, 
NA, 0, 0.01, 60.71, 57.4, 51.8, 51.27, NA, NA, 0.6, 1.56, 1.08, 
1.3, 1.9, 2.22, 2.72, 2.1, 1, 1.29, 0.13, 0.1, 0.4, 0.18, 0.59, 
0.4, 0.3, 0.3, 12.21, 12.6, 13.6, 17.89, 1, 1.6, 2.2, 3.51, 39.88, 
39.6, 41.3, 55.62), pdm = c(4.87, 1.4, 1.34, 4.28, 5.34, 2.38, 
2.55, 4.91, NA, 1.03, 1.62, 4.54, 7.1, 3.39, 4.21, 8.07, 6.05, 
3.04, 4.59, 9.34, 4.78, 1.55, 2.54, 6, 6.97, 1.57, 2.21, 5.07, 
5.18, 2.55, 3.51, 7.97, 6.04, 2.41, 2.83, 5.1, 4.4, 2.16, 3.76, 
8.45, 6.09, 3.02, 4.77, 7.03, NA, 0.92, NA, 2.74, 4.77, 1.31, 
1.8, 3.67, 6.88, 1.83, 2.93, 5.15, 8.32, 2.57, 3.64, 7.18, 7.17, 
1.63, 2.21, 4.27, 6.18, 2.85, 3.61, 6.69, 2.85, 0.65, 0.81, 2.45, 
6.55, 2.24, 4.07, 7.86, NA, 4.97, 5.03, 8.7, 8.12, 4.27, 4.91, 
9.59, 4.8, 1.1, 2.03, 5.25, 3.82, 1.47, 1.89, 5.8, 6.38, 2.11, 
3.06, 7.24, 5.11, 2.37, 3.02, 7.19, 5.95, 2.89, 3.31, 7.1, 5.51, 
1.32, 1.79, 4.34, 4.82, 2.09, 2.59, 5.17, 5.08, 0.68, 1.28, 3.47, 
2.22, 0.54, 0.58, 1.98, 4.38, 1.69, 3.14, 6.51, NA, 1.22, 1.64, 
5.82, 6.63, 1.91, 2.97, 5.91, 6, 2.9, 2.79, 6.07, 3.87, 1.4, 
1.81, 4.27, 6.07, 2.69, 4.79, 8.81, 8.99, 2.76, 3.99, 6.6, 1.59, 
0.84, 0.94, 2.44, 6.13, 1.17, 1.6, 4.9, 6.86, 3.21, 4.36, 8.43, 
2.92, 1.65, 2.71, 7.69, 6.92, 2.31, 3.03, 6.13, 5.81, 2.58, 2.75, 
7.23, 5.1, 2.77, 4.12, 7.42, 9.97, 4.11, 4.19, 7.77, NA, 2.98, 
3.77, 5.38, 6.69, 2.39, 3.53, 6.41, 8.13, 3.13, 3.51, 8.18, 6.71, 
2.67, 3.94, 7.08, 3.96, 1.71, 2.16, 5.01, 8.66, 4.14, 5.38, 6.45, 
6.83, 2.36, 3.28, 4.88, 4.76, 1.04, 1.48, 3.62, 5.12, 2.3, 2.8, 
5.98, 6.91, 3.18, 3.34, 6.88, NA, 3.36, 6.93, 6.24, 5.67, 1.85, 
3.06, 5.44, 4.76, 0.67, 1.42, 3.83, NA, 1.2, 2.11, 6.46, NA, 
5.02, 6.25, 10.04, 8.42, 3.43, 3.56, 6.97, NA, 0.76, 1.1, 2.73, 
6.48, 2.5, 2.59, 5.6, 4.67, 0.61, 0.96, 2.51, 5.59, 3.09, 4.44, 
7.89, 5.16, 1.54, 2.58, 5.68, 6, 2.04, 3.41, 6.05, 4.12, 0.59, 
0.95, 2.5, 5.59, 1.32, 1.92, 3.66, 6.99, 3.89, 5.36, 6.77, 6.47, 
1.22, 1.57, 4.21, 7.48, 3.16, 3.44, 7.21, 5.43, 3.48, 3.68, 7.29, 
7.21, 1.94, 2.37, 5.95, 5.99, 2.54, 4.16, 8.03), teen = c(NA, 
NA, 13, 11.03, 9.39, 8.65, 10.31, 10.6, NA, NA, 7.21, 10.29, 
5.92, 6.32, 9.27, 9, 5.76, 10.97, 8.48, 7.71, 6.68, 6.95, 9.9, 
10.62, 6.28, 7.11, 10.02, 10.5, 6.74, 7.11, 10.11, 9.66, 6.7, 
7.22, 9.5, 9.87, 5.26, 6.45, 7.33, 5.87, 5.02, 6.51, 6.76, 7.03, 
NA, NA, NA, NA, NA, 6.49, 11.39, 9.37, 6.29, 6.29, 8.26, 8.55, 
6.56, 6.94, 8.75, 8.64, 6.55, 6.97, 8.68, 9.3, 7.01, 9.47, 9.44, 
8.49, NA, 13.68, 18.32, 16.29, NA, 5.96, 9.97, 9.27, NA, 5.24, 
8.49, 8.75, 6.54, 7.2, 9.07, 9.23, NA, 8.22, 9.77, 9.92, 10.85, 
12.14, 12.58, 11.73, NA, NA, NA, NA, 7.31, 7.94, 9.53, 8.37, 
NA, NA, 8.4, 8.97, 7.33, 7.45, 10.69, 10.28, NA, 7.52, 8.76, 
9.33, NA, 5.9, 9.3, 9.81, NA, NA, NA, NA, NA, 6.99, 9.89, 8.99, 
NA, NA, 8.51, 10.15, 6.39, 6.64, 8.19, 7.57, 7.19, 7.1, 8.67, 
8.04, 9.59, 11.59, 14.96, 15.5, 7.15, 7.31, 9.42, 9.31, 5.25, 
5.54, 6.76, 7.87, NA, NA, 18.88, 19.48, 6.06, 6.07, 9.39, 7.99, 
7.16, 7.76, 9.8, 8.43, NA, 7.56, 9.89, 8.29, 5.74, 7.15, 8.87, 
9.02, 8.43, 9.41, 10.93, 9.81, NA, NA, 10.47, 8.94, 5.88, 7.32, 
9.74, 8.5, NA, 7.71, 8.89, 9.73, 6.27, 6.95, 8.91, 9.65, 6.66, 
7.54, 9.72, 9.82, 6.13, 6.44, 9.53, 8.28, 7.19, 8.55, 11.46, 
11.26, 6.22, 6.8, 9.02, 7.91, 6.99, 7.78, 9.94, 9.39, 6.4, 6.77, 
8.43, 7.76, NA, 7.67, 9.61, 8.74, 6.75, 7.33, 9.97, 9.04, NA, 
NA, 7.75, 9.09, 5.61, 6.06, 8.96, 8.48, 6.41, 6.82, 6.81, 7.5, 
NA, NA, 9.41, 10.2, NA, 7.5, 8.86, 7.94, 6.45, 8.05, 12.64, 10.1, 
NA, NA, NA, NA, 7.26, 7.68, 10.28, 9.71, NA, 6.21, 9.82, 8.91, 
6.19, 8.86, 9.33, 9.57, 5.37, 6.16, 6.65, 6.82, 7.32, 8.1, 10.44, 
8.71, NA, NA, 8.94, 10.07, 7.11, 7.78, 10.28, 10.16, 4.9, 6.43, 
7.5, 7.56, 6.92, 7.73, 10.56, 10.39, 6.33, 7.28, 10.81, 9.03, 
16.77, 17, 14.1, 13.39, 6.07, 6.19, 8.27, 7.95, 6.8, 7.14, 9.57, 
8.73), twent = c(NA, NA, 11.75, 12.51, 10.97, 10.51, 11.46, 13.17, 
NA, NA, 8.61, 10.88, 7.76, 5.82, 9.18, 10.41, 9.75, 12.8, 14.62, 
10.72, 9.17, 7.33, 10.63, 9.89, 7.47, 6.27, 11.16, 13.89, 9.43, 
7.21, 9.02, 10.67, 7.63, 6.87, 8, 9.45, 7.46, 8.71, 13.83, 10.94, 
5.4, 5.85, 9.26, 10.23, NA, NA, NA, NA, NA, 2.69, 5.74, 8.54, 
7.55, 5.21, 8.15, 10.24, 7.89, 6.03, 6.9, 9.06, 6.96, 4.81, 6.5, 
8.06, 8.63, 7.78, 7.75, 9.92, NA, 18.97, 26.03, 30.78, NA, 4.95, 
9.43, 11.84, NA, 8.45, 13.24, 11.51, 8.28, 7.22, 9.05, 9.64, 
NA, 6.64, 7.85, 8.84, 21.93, 17.88, 21.29, 22.04, NA, NA, NA, 
NA, 8.71, 6.56, 7.2, 7.85, NA, NA, 7.28, 8.82, 8.02, 6.02, 8.4, 
10.29, NA, 3.9, 5.35, 7.07, NA, 2.81, 5.39, 7.36, NA, NA, NA, 
NA, NA, 6.6, 12.57, 12.53, NA, NA, 4.35, 8.05, 8.02, 5.24, 6.5, 
7.6, 8.1, 5.73, 5.9, 8.01, 16.24, 15.77, 23.81, 25.71, 9.56, 
7.84, 10.24, 10.96, 6.4, 4.65, 5.37, 7.65, NA, NA, 29.31, 32.49, 
7.54, 5.23, 8.01, 9.51, 8.3, 6.62, 9.42, 10.38, NA, 8.34, 11.8, 
10.04, 6.73, 7.02, 9.19, 10.07, 12.87, 10.55, 15.52, 16.85, NA, 
NA, 10.39, 13.04, 7.02, 5.06, 7.49, 10.73, NA, 6.28, 7.61, 9.95, 
7.99, 6.11, 8.28, 9.94, 8.2, 9.21, 11.05, 12.52, 8.02, 6.32, 
8.5, 9.56, 10.85, 8.18, 11.79, 13.82, 8.97, 6.06, 8.58, 9.98, 
7.67, 5.86, 7.49, 10.45, 8.4, 5.29, 8.05, 8.99, NA, 5.27, 7.51, 
10.42, 8.55, 6.38, 8.29, 10.29, NA, NA, 9.48, 10.25, 7.71, 5.22, 
7.29, 8.96, 7.43, 5.69, 8.16, 9.32, NA, NA, 5.48, 10.21, NA, 
7.22, 12.2, 12.64, 7.32, 6.63, 15.23, 16.95, NA, NA, NA, NA, 
8.34, 6.9, 8.24, 10.42, NA, 3.57, 7.4, 8.5, 12.71, 11.57, 21.23, 
17.54, 6.56, 5.72, 7.35, 7.91, 8.63, 5.57, 6.61, 9.03, NA, NA, 
3.91, 6.94, 8.57, 6.05, 8.78, 11.18, 5.74, 3.98, 4.84, 5.64, 
6.68, 4.74, 7.46, 9.53, 7.8, 5.73, 8.87, 11.04, 17.49, 13.46, 
17.89, 15.05, 7.03, 5.55, 7.8, 11.25, 8.71, 6.46, 8.24, 10.55
), tfive = c(NA, NA, 5.81, 8.58, 9.28, 8.26, 6.4, 8.92, NA, NA, 
10.75, 9.25, 9.39, 6.02, 6.42, 9.13, 11.43, 6.66, 8.45, 10.32, 
10.2, 7.96, 7.31, 9.33, 7.59, 5.59, 6.18, 9.77, 10.47, 7.47, 
7.14, 10.25, 8.74, 6, 5.34, 7.76, 10.61, 8.22, 11.77, 14.51, 
7.04, 5.06, 8.04, 10.58, NA, NA, NA, NA, NA, 3.64, 5.31, 7.71, 
8.19, 5.65, 5.8, 8.47, 8.2, 5.96, 5.7, 8, 7.67, 4.71, 5.17, 7.16, 
9.54, 7.77, 6.77, 9.49, NA, 9.23, 8.13, 10.65, NA, 7.57, 7.55, 
9.92, NA, 9.85, 9.29, 12.14, 9.08, 6.52, 6.95, 8.14, NA, 7.06, 
5.84, 7.4, 12.54, 9.67, 11.32, 13.79, NA, NA, NA, NA, 9.1, 6.06, 
5.47, 7.84, NA, NA, 8.75, 9.54, 7.86, 5.86, 6.24, 9.2, NA, 3.93, 
4.82, 5.3, NA, 5.06, 6.76, 6.91, NA, NA, NA, NA, NA, 8.94, 10.05, 
11.62, 0, NA, 7.02, 8.87, 8.69, 5.75, 5.71, 8.03, 8.4, 6.06, 
5.84, 7.04, 10.27, 7.14, 7.53, 9.96, 9.38, 6.83, 8.07, 10.22, 
7, 4.72, 4.49, 6.63, NA, NA, 7.3, 7.59, 8.36, 5.55, 6.14, 9.47, 
9.21, 5.72, 5.96, 8.77, NA, 8.84, 8.5, 12.39, 7.79, 6.23, 7.76, 
10, 10.64, 7.23, 8.32, 13.15, NA, NA, 7.17, 10.39, 8.63, 5.66, 
7.02, 10.45, NA, 6.22, 7.49, 9.39, 9.2, 6.04, 6.53, 8.88, 7.84, 
7.52, 6.29, 9.85, 9.36, 6.21, 6.12, 8.52, 10.69, 6.44, 6.94, 
9.78, 8.93, 5.78, 6.36, 9.22, 7.94, 5.23, 5.85, 9, 9.68, 5.94, 
6.27, 8.39, NA, 6.06, 7.33, 10.16, 9.36, 6.39, 6.01, 9.3, NA, 
NA, 8.75, 9.61, 8.89, 5.53, 5.64, 8.15, 8.52, 6.41, 7.62, 9.55, 
NA, NA, 7.46, 8.32, NA, 6.25, 8.24, 10.22, 7.06, 5.13, 6.62, 
10.64, NA, NA, NA, NA, 7.85, 6.14, 6.63, 8.71, NA, 4.78, 6.48, 
7.91, 11, 8.02, 11.86, 13.02, 7.35, 5.81, 6.21, 7.43, 8.28, 5.35, 
5.23, 8.12, NA, NA, 5.83, 7.05, 8.9, 5.72, 5.8, 7.63, 6.08, 3.56, 
4.47, 6.01, 7.72, 5.88, 6.14, 9.11, 8.37, 6.03, 6.41, 9.86, 10.57, 
8.17, 5.75, 9.64, 7.72, 5.51, 5.87, 8.6, 9.16, 6.32, 6.08, 9.82
), unemp = c(NA, NA, 4.6, 4.14, 2.45, 5.4, 3.7, 3.69, NA, NA, 
NA, 3.56, 6.92, 6, 4.9, 10.05, 10.16, 5.9, 4.9, 4.76, 6.1, 4.4, 
4.6, 8.49, 5.08, 5.2, 3.5, 6.38, 3.75, 4.5, 5.3, 6.35, 5.42, 
7.2, 5.4, 7.15, 2.56, 2.6, 2, 3.38, 4.67, 3.9, 3.9, 3.99, NA, 
NA, NA, NA, NA, 4.3, 2.6, 8.53, 4.07, 4.2, 2.5, 5.41, 5.49, 4.9, 
6.1, 10.1, 4.94, 6, 3.4, 10.22, 2.78, 3.3, 3.2, 3.37, NA, 2.1, 
4.2, 3.97, NA, 4.6, 5.8, 4.69, NA, 12.7, 7.8, 8.28, 3, 4, 5.5, 
14.91, NA, 4, 3.3, 6.66, 3.25, 2.7, 3.3, 4.11, NA, NA, 2.5, NA, 
5.32, 7.2, 5, 10.52, NA, NA, 5.8, 7.83, 2.52, 2.4, 2.7, 5.63, 
NA, 3.1, 3.5, 2.7, NA, 1.4, 1.8, 2.91, NA, NA, NA, NA, NA, 3.7, 
3.5, 2.71, NA, NA, 2.3, 3.73, 5.32, 3.8, 4.8, 6.77, 5.36, 7.2, 
3.2, 10.24, 3.92, 3.8, 3.1, 8.34, 3.7, 3.6, 4, 8.07, 7.98, 9.8, 
8.9, 11.18, NA, NA, NA, 4.64, 5.46, 7, 6.4, 11.5, 5.95, 5.6, 
5.1, 9.46, NA, 2.8, 3.5, 3.72, 2.71, 2.9, 2.8, 6.78, 2.79, 3.3, 
3.2, 3.85, NA, NA, 6.6, 6.22, 8.2, 5.5, 5.4, 5.11, NA, 6.4, 6.3, 
7.81, 5.82, 6.5, 4.6, 10.76, 8.15, 5.8, 4.1, 8.31, 7.39, 6.4, 
4, 10.01, 4.55, 6.1, 4.6, 5.84, 4.99, 7.4, 6.1, 11.41, 6.09, 
7.8, 7.1, 15.45, 7.83, 5, 3.3, 6.96, NA, 3.9, 2.9, 5.28, 6.07, 
5.2, 4.4, 5.76, NA, NA, 8.6, 9.81, 3.31, 4.1, 4.3, 6.11, 3.87, 
3.1, 3.6, 6.25, NA, NA, 5.5, 4.45, NA, 5.2, 5.5, 5.79, 7.13, 
9.3, 8.3, 10.61, NA, NA, NA, NA, 3.48, 3.2, 5.3, 9.41, NA, 2.6, 
3.4, 5.43, 6.6, 5.3, 8.3, 6.8, 1.94, 2, 2.2, 5.31, 9.87, 9.9, 
6.1, 9.49, NA, NA, 3.8, 4.86, 4.21, 4.1, 2, 6.01, 5.4, 4.8, 4.5, 
4.01, 4.53, 3.4, 3.3, 4.23, 5.68, 6.6, 6.1, 6.61, 4.08, 8.4, 
5.6, 9.12, 5.29, 4.6, 5, 7.23, 4.8, 6.4, 4.8, 8.67), manuf = c(NA, 
NA, 9, 14.21, 10.5, 10.8, 12, 10.81, NA, NA, 35.2, 35.03, 48.4, 
44, 38.4, 29.58, 16.8, 20.7, 15.5, 14.64, 17.2, 16.3, 19, 21.8, 
16.3, 14.3, 10.7, 6.87, 7.2, 9.4, 7, 8.86, 11.9, 8.6, 11, 8.28, 
6.9, 7.2, 6.3, 4.96, 24.1, 25.8, 20, 21.3, NA, NA, NA, NA, NA, 
48.5, 39.7, 31.56, 42.6, 41.7, 39.1, 35.76, 41.2, 42.1, 37.6, 
28.22, 11, 19.7, 26.1, 19.84, 10.7, 11.9, 11.6, 15.79, NA, 7.1, 
4.1, 6.72, NA, 35.3, 31.9, 28.86, NA, 4.1, 3.4, 3.15, 53.8, 47.5, 
47.5, 36.13, NA, 42.4, 35.3, 30.92, 15.2, 12.8, 14.2, 11.82, 
NA, NA, 8, NA, 34.3, 28, 27.8, 20.02, NA, NA, 35.7, 24.13, 37.8, 
36.7, 31.6, 30.18, NA, 24.4, 20.6, 16.41, NA, 31.3, 27.2, 23.5, 
NA, NA, NA, NA, NA, 37.6, 36.9, 23.78, NA, NA, 19.3, 18.52, 13.1, 
18.1, 20.8, 21.47, 28.2, 33.3, 28.2, 25.9, 15.8, 18.9, 14.2, 
14.29, 16.8, 17.9, 16.7, 13.17, 6.7, 8.1, 10.1, 7.92, NA, NA, 
8.6, 8.3, 47.1, 38.6, 35.9, 30.42, 22.8, 21.4, 19.4, 15.88, NA, 
14.5, 12.5, 11.65, 39.3, 41.4, 43.3, 39.1, 6.6, 7.5, 8.7, 11.4, 
NA, NA, 34.8, 33.54, 6.9, 9.6, 7.1, 7.44, NA, 34.6, 34, 36.26, 
29, 28, 25.6, 18.79, 14.6, 15.2, 13.6, 11.56, 61, 52.7, 48.2, 
40.51, 23.7, 18.2, 15.5, 12.89, 37.9, 31.7, 30.8, 29, 41.6, 40.2, 
37.2, 28.98, 47.5, 42.2, 36.2, 25.49, NA, 37, 28.9, 25.93, 21, 
19.8, 19.9, 19.68, NA, NA, 46.6, 49.8, 30.9, 27.4, 19.5, 14.75, 
42.9, 39, 33.9, 27.77, NA, NA, 25.6, 21.6, NA, 38, 33, 29.51, 
20.9, 19.7, 16.4, 14.63, NA, NA, NA, NA, 52.7, 48.3, 45.7, 44.95, 
NA, 29.4, 25.8, 21.64, 16.5, 13.5, 9.7, 8.43, 44, 40.9, 35.7, 
27.07, 27, 31.1, 30.4, 27.14, NA, NA, 23.3, 19.06, 57.9, 52.3, 
46.2, 39.64, 13.1, 13.9, 10.5, 9.63, 38.8, 38.1, 29.1, 23.24, 
10.2, 11.6, 8.3, 7.52, 14.9, 12.2, 10.1, 10.4, 37.9, 36.3, 30.2, 
24.51, 25.1, 24.8, 21.6, 16.82), msy= c(0, 0, 12.3, 8.94205578671598, 
11.3, 12.1, 12.3, 11.1661496211158, 0, 0, 0, 3.80053093181895, 
10.4, 10.8, 12, 14.728662560029, 12.1, 12.1, 12.4, 7.6692977510493, 
8.8, 10.5, 11.5, 24.0038347803778, 10.3, 10.9, 12.1, 16.1343596095432, 
12.1, 12.4, 12.6, 12.2543833473492, 8.7, 9.6, 11.5, 23.7855134296519, 
12.2, 12.3, 12.7, 8.89679025741884, 12.2, 12.1, 12.4, 11.5329257912249, 
8.5, 9, 0, NA, 0, 12.1, 12.2, 2.05579599953211, 9.2, 10, 11.5, 
11.2184120742497, 9.1, 10.2, 11.4, 15.3200081940827, 9.5, 10.1, 
11.7, 11.9941133186166, 11.3, 12.1, 12.3, 9.77618441332172, 0, 
13.3, 15, 11.8317859093392, 0, 12.3, 12.5, 7.61156531136149, 
0, 12.4, 12.6, 7.13519959181567, 9.8, 10.1, 12, 12.2899760414251, 
0, 8.7, 10.7, 18.9982792077033, 12.8, 13.7, 15.4, 12.9966841413037, 
0, 0, 12.4, NA, 8.4, 9.6, 11, 23.2225722318193, 0, 0, 12.2, 7.19490195159666, 
10.7, 12, 12.3, 5.76128201653341, 0, 12.7, 12.9, 4.00269600382659, 
0, 12.7, 12.9, 2.55762599068304, 0, 0, 0, NA, 0, 12.3, 12.6, 
5.83213105744068, 0, 0, 12.7, 3.91600454029512, 10.3, 11.7, 12, 
16.3428699400929, 9.6, 11, 12.1, 14.8869346733668, 9.8, 10.9, 
12.5, 21.4482126489459, 9.5, 10.5, 11.5, 26.4979224604844, 8.9, 
9, 10, 23.9682579168636, 0, 0, 0, 28.3727301464648, 9.1, 9.8, 
11.8, 11.8225390192946, 7.9, 8.7, 9.8, 29.407557014222, 0, 12.5, 
12.6, 5.32259691779958, 10.5, 11.2, 12.1, 8.55424206266222, 11.5, 
11.9, 12.5, 15.0198555120754, 0, 0, 11.8, 11.2049012933969, 11.5, 
12, 12.4, 11.0518790656276, 0, 10.6, 11.3, 14.8989199667682, 
8.6, 8.9, 10, 22.4303009119507, 11.7, 12.2, 12.4, 13.64598805423, 
9.9, 10.5, 11.6, 10.8164431447682, 10.6, 11.9, 12.3, 17.8813138333508, 
10.7, 10.8, 11.7, 17.5288321576531, 9.2, 10.3, 11.5, 13.0478686317409, 
9.1, 10.1, 11.4, 9.51465863145111, 0, 11.5, 12.1, 10.2243381409975, 
10, 11.1, 11.7, 15.3409764440907, 0, 0, 10.4, 24.9201277955272, 
8.9, 9.8, 11.6, 7.50601250601251, 9.7, 10.3, 11.6, 6.74640201317612, 
NA, NA, 14.3, 4.80900640028145, 0, 11.4, 12.2, 9.76029640163919, 
10.9, 12, 12.4, 15.8295846617461, NA, NA, NA, NA, 10.7, 11.2, 
12.2, 11.2278808191553, 0, 11.8, 12.2, 3.21886733416771, 12.7, 
12.9, 14.3, 19.3829358934655, 9.8, 10.5, 11.5, 5.34056223185127, 
7.7, 8.5, 9.9, 25.3427463834347, 0, 0, 12.7, 2.38239102287441, 
9.5, 10.5, 11.9, 10.4219031795396, 12.7, 12.7, 13, 8.882503784719, 
12.1, 12.2, 12.4, 7.09069180719692, 12.1, 12.3, 12.6, 9.80119165244468, 
10.2, 11.8, 12.2, 13.9745695686561, 9.9, 10.5, 12.1, 14.9910490511994, 
9.4, 10.1, 11.2, 21.6790371748127)), row.names = c(NA, -300L), class = c("tbl_df", 
"tbl", "data.frame"))
Villinger
  • 1
  • 2
  • Can you provide `dput(df2)` that doesn't involve dropbox? Or make a reproducible example with `iris` or `mtcars`? https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example – jrcalabrese Jun 14 '23 at 14:37
  • @jrcalabrese - yes sorry, I updated the post with a sample – Villinger Jun 15 '23 at 22:14

0 Answers0