Hi Guy, 

It's hard to say what the problem is without playing around with the data, but I'm working on a fix that should hopefully side-step this issue. I'll let you know when that's available. In the meantime, you can run Amelia without checks, by setting the "incheck" argument to FALSE. This will bypass the error checking procedures in Amelia and go straight to the imputation. 

Hope that helps!

Cheers,
matt.

On Wednesday, June 20, 2012 at 10:05 PM, Guy Grossman wrote:

Error in if (sum(non.vary == 0)) { :
  argument is not interpretable as logical

I searched online but was unable to find a way to correct this error.
I have actually relatively few missing variables. any idea what I can do to get rid of the error.

Your response would be highly appreciated!
Guy


# define variables' type
ords = c("post_elections", "prev_elections", "election_year")
noms = c("type", "region", "split_cat", "splinter", "mother", "breakup", "home_winner", "tribe_winner", "support_winner", "opposed", "irregularity", "home_loser", "tribe_loser", "support_loser", "politics_loser", "mobilize_loser", "ethnic_min", "ethnicity_dec_major", "dom_ethnic02", "turn_majority", "contig_border", "TYPE_2")
idvars = c("county_name", "district_11", "regions_67", "district_80", "district_91", "district_96", "district_01", "district_02", "district_06", "district_07")
lags = c("split_cat", "mshare_county") 
logs = c("area", "pop")
lgstc = c("mshare", "mshare_county", "cshare_county", "elf02", "eduattain", "literacy", "employee", "pio", "nag_pio", "nag_employee", "pl02", "pi02", "perclit91", "percillit91")

a.out <- amelia(DistrictFormation, m = 5, ts = "wave", cs = "id", polytime = 2, intercs = TRUE, 
                idvars=idvars, ords=ords, noms=noms, logs=logs, lgstc=lgstc)

Error in if (sum(non.vary == 0)) { : 
  argument is not interpretable as logical


> str(DistrictFormation)
'data.frame': 474 obs. of  109 variables:
 $ id                   : num  1 1 1 2 2 2 3 3 3 4 ...
 $ wave                 : int  1 2 3 1 2 3 1 2 3 1 ...
 $ county_name          : chr  "BUJUMBA" "BUJUMBA" "BUJUMBA" "KYAMUSWA" ...
 $ county_id02          : num  1011 1011 1011 1012 1012 ...
 $ region               : Factor w/ 4 levels "CENTRAL","EASTERN",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ district_11          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ regions_67           : chr  "MASAKA" "MASAKA" "MASAKA" "MASAKA" ...
 $ district_80          : chr  "MASAKA" "MASAKA" "MASAKA" "MASAKA" ...
 $ district_91          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ district_96          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ district_01          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ district_02          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ district_06          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ district_07          : chr  "KALANGALA" "KALANGALA" "KALANGALA" "KALANGALA" ...
 $ ndist80              : num  18 18 18 18 18 18 18 18 18 18 ...
 $ ndist91              : num  39 39 39 39 39 39 39 39 39 39 ...
 $ ndist02              : num  56 56 56 56 56 56 56 56 56 56 ...
 $ ndist06              : num  72 72 72 72 72 72 72 72 72 72 ...
 $ ndist07              : num  80 80 80 80 80 80 80 80 80 80 ...
 $ ndist11              : num  109 109 109 109 109 109 109 109 109 109 ...
 $ n1991                : num  2 2 2 2 2 2 1 1 1 4 ...
 $ n1996                : num  2 2 2 2 2 2 1 1 1 4 ...
 $ n2001                : num  2 2 2 2 2 2 1 1 1 3 ...
 $ n2006                : num  2 2 2 2 2 2 1 1 1 2 ...
 $ ncounties            : num  2 2 2 2 2 2 1 1 1 4 ...
 $ type                 : chr  "COUNTY" "COUNTY" "COUNTY" "COUNTY" ...
 $ post_elections       : num  2001 2006 2011 2001 2006 ...
 $ prev_elections       : num  1996 2001 2006 1996 2001 ...
 $ split_cat            : Factor w/ 3 levels "No Split","Splinter",..: 1 1 1 1 1 1 1 1 1 3 ...
 $ splinter             : num  0 0 0 0 0 0 0 0 0 0 ...
 $ mother               : num  0 0 0 0 0 0 0 0 0 1 ...
 $ breakup              : num  0 0 0 0 0 0 0 0 0 1 ...
 $ election_year        : int  2001 2006 2011 2001 2006 2011 2001 2006 2011 2001 ...
 $ mshare_county        : num  0.667 0.539 0.639 0.677 0.535 ...
 $ cshare_county        : num  0.317 0.403 0.296 0.304 0.421 ...
 $ mmargin_county       : num  0.343 0.137 0.342 0.365 0.115 ...
 $ mshare               : num  0.693 0.585 0.689 0.693 0.585 ...
 $ mshare_cat           : num  0.695 0.622 0.706 0.695 0.622 ...
 $ MP_nrm_share         : num  -999 1 1 -999 0 1 -999 1 1 -999 ...
 $ home_winner          : int  0 0 0 1 1 1 1 1 1 0 ...
 $ tribe_winner         : Factor w/ 37 levels "ACHOLI","ALUR",..: 6 6 6 6 6 6 6 6 6 6 ...
 $ support_winner       : int  0 0 1 1 1 1 1 1 1 1 ...
 $ opposed              : int  1 1 0 1 1 0 0 1 1 1 ...
 $ irregularity         : int  0 0 0 0 0 0 0 0 0 0 ...
 $ home_loser           : int  1 1 0 0 0 0 1 1 1 0 ...
 $ tribe_loser          : Factor w/ 37 levels "ACHOLI","ALUR",..: 6 6 6 6 6 6 6 13 13 6 ...
 $ support_loser        : int  1 1 0 0 0 0 0 0 0 0 ...
 $ politics_loser       : int  0 1 0 0 1 0 0 1 0 1 ...
 $ mobilize_loser       : int  0 0 0 0 0 0 0 0 0 1 ...
 $ county_dec_share     : num  0.6 0.4 0.6 0.4 0.6 ...
 $ ethnic_min           : num  0 0 0 0 0 0 0 0 0 0 ...
 $ ethnicity_dec_major  : Factor w/ 37 levels "ACHOLI","ALUR",..: 6 6 6 6 6 6 6 6 6 6 ...
 $ control_dec_ethnicity: num  1 1 0.8 1 1 ...
 $ pop                  : num  17271 17271 17271 17428 17428 ...
 $ dom_ethnic02         : Factor w/ 37 levels "ACHOLI","ALUR",..: 6 6 6 6 6 6 6 6 6 6 ...
 $ share_dom_ethnic02   : num  67.7 67.7 67.7 60.2 60.2 ...
 $ turn_majority        : num  0 0 0 0 0 0 0 0 0 0 ...
 $ pop02                : int  17271 17271 17271 17428 17428 17428 229297 229297 229297 137199 ...
 $ elf02                : num  0.528 0.528 0.528 0.624 0.624 ...
 $ schools_tot_pop      : num  0.811 0.811 0.811 0.689 0.689 ...
 $ schools_tot          : num  14 14 14 12 12 12 260 260 260 170 ...
 $ other_tot_pop        : num  0.116 0.116 0.116 0 0 ...
 $ other_tot            : num  2 2 2 0 0 0 1 1 1 1 ...
 $ primary_tot_pop      : num  0.579 0.579 0.579 0.631 0.631 ...
 $ primary_tot          : num  10 10 10 11 11 11 229 229 229 142 ...
 $ sec_tot_pop          : num  0.1158 0.1158 0.1158 0.0574 0.0574 ...
 $ sec_tot              : num  2 2 2 1 1 1 30 30 30 27 ...
 $ gov_primary_pop      : num  0.521 0.521 0.521 0.459 0.459 ...
 $ gov_primary          : num  9 9 9 8 8 8 188 188 188 81 ...
 $ gov_sec_pop          : num  0.1158 0.1158 0.1158 0.0574 0.0574 ...
 $ gov_sec              : num  2 2 2 1 1 1 7 7 7 6 ...
 $ eduattain            : num  0.222 0.222 0.222 0.241 0.241 ...
 $ literacy             : num  0.818 0.818 0.818 0.826 0.826 ...
 $ pl02                 : num  0.12 0.12 0.12 0.04 0.04 ...
 $ se_po02              : num  1.89 1.89 1.89 0.93 0.93 ...
 $ pg02                 : int  2 2 2 1 1 1 10 10 10 9 ...
 $ se_pg02              : num  0.48 0.48 0.48 0.2 0.2 ...
 $ pi02                 : num  0.0033 0.0033 0.0033 0.0036 0.0036 ...
 $ sepi02               : num  1.14 1.14 1.14 1.63 1.63 ...
 $ npoor02              : int  2014 2014 2014 772 772 772 79497 79497 79497 45674 ...
 $ se_npoor02           : int  326 326 326 162 162 162 3164 3164 3164 1962 ...
 $ elf91                : num  0.43 0.43 0.43 0.458 0.458 ...
 $ area                 : num  2356 2356 2356 6672 6672 ...
 $ pop91                : int  7335 7335 7335 6872 6872 6872 132711 132711 132711 105562 ...
 $ pl91                 : num  0.365 0.365 0.365 0.261 0.261 ...
 $ pg91                 : num  10.1 10.1 10.1 7.1 7.1 ...
 $ gini91               : num  29.9 29.9 29.9 32.6 32.6 ...
 $ popdensity91         : num  3.11 3.11 3.11 1.03 1.03 ...
 $ censuspop91          : int  9192 9192 9192 7179 7179 7179 141607 141607 141607 108098 ...
 $ perclit91            : num  0.711 0.711 0.711 0.729 0.729 ...
 $ percillit91          : num  0.289 0.289 0.289 0.271 0.271 ...
 $ distance_border      : num  81855 81855 81855 94097 94097 ...
 $ contig_border        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ distance_kampala     : num  86.6 86.6 86.6 80.2 80.2 ...
 $ pio                  : num  0.668 0.668 0.668 0.704 0.704 ...
 $ employee             : num  0.358 0.358 0.358 0.393 0.393 ...
 $ nag_pio              : num  0.249 0.249 0.249 0.15 0.15 ...
 $ nag_employee         : num  0.1628 0.1628 0.1628 0.0701 0.0701 ...
 $ pop_county18         : num  10257 10257 10257 12185 12185 ...
  [list output truncated]