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[ODP] Crime, income and employment among immigrant groups in Norway and Finland

#22
Here is my current code. Updated dataset file is attached.

Code:
setwd("Z:/Code/database")
read = read.csv("Megadataset_v1.4.csv")
colnames(read)

library(Hmisc) # for rcorr
library(car) # for scatterplot
library(stats) #for automatic multiple regression
library(psych) #for r.test
library(XLConnect) #writing to xls
library(nFactors) #how many factors to extract
library(mi) #imputation


DF.work = cbind(read["Norway.OutOfWork.2010Q2.men"], #for work data
          read["Norway.OutOfWork.2011Q2.men"],
          read["Norway.OutOfWork.2012Q2.men"],
          read["Norway.OutOfWork.2013Q2.men"],
          read["Norway.OutOfWork.2014Q2.men"],
          read["Norway.OutOfWork.2010Q2.women"],
          read["Norway.OutOfWork.2011Q2.women"],
          read["Norway.OutOfWork.2012Q2.women"],
          read["Norway.OutOfWork.2013Q2.women"],
          read["Norway.OutOfWork.2014Q2.women"])

DF.income = cbind(read["Norway.Income.index.2009"], #for income data
                  read["Norway.Income.index.2010"],
                  read["Norway.Income.index.2011"],
                  read["Norway.Income.index.2012"])

#make DF
DF = cbind(read["LV2012estimatedIQ"],
           read["Altinok2013ACH"],
           read["IslamPewResearch2010"],
           log(read["GDPpercapitaWorldBank2013"]),
           read["S.scores"],
           read["NorwayViolentCrimeAdjustedOddsRatioSkardhamar2014"],
           read["FinlandViolentCrimeAdjustedOddsRatioSkardhamar2014"],
           read["NorwayLarcenyAdjustedOddsRatioSkardhamar2014"],
           read["FinlandLarcenyAdjustedOddsRatioSkardhamar2014"],
           read["Norway.tertiary.edu.att.2013"],
           read["Norway.tertiary.edu.att.bigsamples.2013"])

  
#get 5 year means
DF["OutOfWork.2010to2014.men"] = apply(DF.work[1:5],1,mean,na.rm=T) #get means, ignore missing
DF["OutOfWork.2010to2014.women"] = apply(DF.work[6:10],1,mean,na.rm=T) #get means, ignore missing

#get means for income and add to DF
DF["Income.index.2009to2012"] = apply(DF.income[1:4],1,mean,na.rm=T) #get means, ignore missing

#compare islam vars
DF.islam = as.data.frame(cbind(read["IslamPewResearch1990"],
                               read["IslamPewResearch2010"],
                               read["IslamPewResearch2030Projected"],
                               read["Islam"]))

#correlation matrix
DF.cor = rcorr(as.matrix(DF)) #create correlation matrix with pairwise miss data deleted
round(DF.cor$r,2)

#write results to xlsx file
writeWorksheetToFile(file = "correlations_Norway2014.xlsx", data = round(DF.cor$r,2), sheet = "cors")
writeWorksheetToFile(file = "correlations_Norway2014.xlsx", data = round(DF.cor$P,4), sheet = "p")
writeWorksheetToFile(file = "correlations_Norway2014.xlsx", data = DF.cor$n, sheet = "n")

#are the same vars hard/easy to predict across predictors?
IQ.cors = DF.cor$r[6:nrow(DF.cor$r),1]
Altinok.cors = DF.cor$r[6:nrow(DF.cor$r),2]
Islam.cors = DF.cor$r[6:nrow(DF.cor$r),3]
GDP.cors = DF.cor$r[6:nrow(DF.cor$r),4]
S.cors = DF.cor$r[6:nrow(DF.cor$r),5]

DF.predict = as.data.frame(cbind(IQ.cors,Altinok.cors,Islam.cors,GDP.cors,S.cors))
DF.predict.cor = rcorr(as.matrix(DF.predict)) #are there clear patterns in how well the vars are predictable? YES!

#factor analysis
#subset data
DF.norway = DF[c("NorwayViolentCrimeAdjustedOddsRatioSkardhamar2014", #only norwegian vars
                 "NorwayLarcenyAdjustedOddsRatioSkardhamar2014",
                 "Norway.tertiary.edu.att.bigsamples.2013", #skip the small ed. att var
                 "OutOfWork.2010to2014.men",
                 "OutOfWork.2010to2014.women",
                 "Income.index.2009to2012")]

#handle missing values
DF.norway.complete = DF.norway[complete.cases(DF.norway),] #complete cases only, reduces N to 15

#count NA's
DF.norway.missing = apply(DF.norway, 1, is.na) #produces a col with T/F for each case
DF.norway.missing = apply(DF.norway.missing, 2, sum) #sums the number of missing per col
DF.norway.missing.table = table(DF.norway.missing) #tabulates them

#initial info
mi.info = mi.info(DF.norway)
missing.pattern.plot(DF.norway) #visual depiction of missing values
mp.plot(DF.norway, y.order = TRUE, x.order = TRUE)

#subsets
DF.norway.miss.1 = DF.norway[DF.norway.missing <= 1,] #keep data with 1 or less missing values, N=18
DF.norway.miss.2 = DF.norway[DF.norway.missing <= 2,] #keep data with 2 or less missing values, N=26

#impute
DF.norway.miss.1.impute = mi(DF.norway.miss.1, n.iter=200) #imputes, needs more interations
DF.norway.miss.1.imputed = mi.data.frame(DF.norway.miss.1.impute, m = 3)
DF.norway.miss.2.impute = mi(DF.norway.miss.2, n.iter=200) #imputes, needs more interations
DF.norway.miss.2.imputed = mi.data.frame(DF.norway.miss.2.impute, m = 3)

#compare desc. stats
DF.desc.stats = as.data.frame(rbind(describe(DF.norway),
                                    describe(DF.norway.complete),
                                    describe(DF.norway.miss.1.imputed),
                                    describe(DF.norway.miss.2.imputed)))
DF.desc.stats.ordered = DF.desc.stats[with(DF.desc.stats, order(vars)), ] #reorder

write.csv(DF.desc.stats.ordered, "desc_stats.csv")

#sampling tests
#bartlett's test
cortest.bartlett(DF.norway.complete)
cortest.bartlett(DF.norway.miss.1.imputed)
cortest.bartlett(DF.norway.miss.2.imputed)

#KMO function
kmo <- function(x)
{
  x <- subset(x, complete.cases(x)) # Omit missing values
  r <- cor(x) # Correlation matrix
  r2 <- r^2 # Squared correlation coefficients
  i <- solve(r) # Inverse matrix of correlation matrix
  d <- diag(i) # Diagonal elements of inverse matrix
  p2 <- (-i/sqrt(outer(d, d)))^2 # Squared partial correlation coefficients
  diag(r2) <- diag(p2) <- 0 # Delete diagonal elements
  KMO <- sum(r2)/(sum(r2)+sum(p2))
  MSA <- colSums(r2)/(colSums(r2)+colSums(p2))
  return(list(KMO=KMO, MSA=MSA))
}

#get KMO
kmo(DF.norway.complete)$KMO
kmo(DF.norway.miss.1.imputed)$KMO
kmo(DF.norway.miss.2.imputed)$KMO

#nfactors
nScree(DF.norway.complete)
nScree(DF.norway.miss.1.imputed)
nScree(DF.norway.miss.2.imputed)

#PA and ML
DF.norway.complete.pa = fa(DF.norway.complete, nfactors=1,rotate="none",scores="regression",fm="pa")
DF.norway.complete.ml = fa(DF.norway.complete, nfactors=1,rotate="none",scores="regression",fm="ml")
factor.congruence(DF.norway.complete.pa,DF.norway.complete.ml) #identical

DF.norway.miss.1.imputed.pa = fa(DF.norway.miss.1.imputed, nfactors=1,rotate="none",scores="regression",fm="pa")
DF.norway.miss.1.imputed.ml = fa(DF.norway.miss.1.imputed, nfactors=1,rotate="none",scores="regression",fm="ml")
factor.congruence(DF.norway.miss.1.imputed.pa,DF.norway.miss.1.imputed.ml) #identical

DF.norway.miss.2.imputed.pa = fa(DF.norway.miss.2.imputed, nfactors=1,rotate="none",scores="regression",fm="pa")
DF.norway.miss.2.imputed.ml = fa(DF.norway.miss.2.imputed, nfactors=1,rotate="none",scores="regression",fm="ml")
factor.congruence(DF.norway.miss.2.imputed.pa,DF.norway.miss.2.imputed.ml) #identical

DF.norway.miss.2.imputed.pa2 = fa(DF.norway.miss.2.imputed, nfactors=2,rotate="none",scores="regression",fm="pa")
DF.norway.miss.2.imputed.ml2 = fa(DF.norway.miss.2.imputed, nfactors=2,rotate="none",scores="regression",fm="ml")


#Strength of general factor
omega(DF.norway.complete)
omega(DF.norway.miss.1.imputed)
omega(DF.norway.miss.2.imputed)

#put the factor scores back into the big dataset - for SPI
Sfactor.scores = rep(NA,nrow(DF))   #make an empty vector of the right size for the factor scores
Sfactor.scores1 = rep(NA,nrow(DF))
Sfactor.scores2 = rep(NA,nrow(DF))

dims = as.integer(dimnames(DF.norway.complete.pa$scores)[[1]])    #converts the dimnames to integers
dims1 = as.integer(dimnames(DF.norway.miss.1.imputed.pa$scores)[[1]])  #converts the dimnames to integers
dims2 = as.integer(dimnames(DF.norway.miss.2.imputed.pa$scores)[[1]])  #converts the dimnames to integers

for (n in 1:nrow(DF))        #this puts the factor scores back into the big dataset
{  
  Sfactor.scores[dims[n]] = DF.norway.complete.pa$scores[n]
  Sfactor.scores1[dims1[n]] = DF.norway.miss.1.imputed.pa$scores[n]
  Sfactor.scores2[dims2[n]] = DF.norway.miss.2.imputed.pa$scores[n]
}

#reverse Sfactor scores
Sfactor.scores = Sfactor.scores*-1
Sfactor.scores1 = Sfactor.scores1*-1
Sfactor.scores2 = Sfactor.scores2*-1

#make DF
DF2 = cbind(read["LV2012estimatedIQ"],
           read["Altinok2013ACH"],
           read["IslamPewResearch2010"],
           log(read["GDPpercapitaWorldBank2013"]),
           read["S.scores"],
           Sfactor.scores,
           Sfactor.scores1,
           Sfactor.scores2)

DF2.cor = rcorr(as.matrix(DF2)) #create correlation matrix with pairwise miss data deleted
round(DF2.cor$r,2)


#visualize
scatterplot(OutOfWork.2010to2014.men ~ LV2012estimatedIQ, #predict employment from IQ
            data=DF,
            smoother=NULL, #no moving average
            labels=unlist(read["ID"]), #labels, but they dont work
            id.n = length(unlist(read["ID"])), #pointless, but needed
            xlab = "Lynn and Vanhanen national IQ",
            ylab="% of men unemployed, 2010-2014 average")


scatterplot(OutOfWork.2010to2014.women ~ IslamPewResearch2010, #predict employment from Islam
            data=DF,
            smoother=NULL, #no moving average
            labels=unlist(read["ID"]), #labels, but they dont work
            id.n = length(unlist(read["ID"])), #pointless, but needed
            xlab = "Prevalence of Islam",
            ylab="% of women unemployed, 2010-2014 average")

scatterplot(Norway.tertiary.edu.att.bigsamples.2013 ~ S.scores, #predict employment from Islam
            data=DF,
            smoother=NULL, #no moving average
            labels=unlist(read["ID"]), #labels, but they dont work
            id.n = length(unlist(read["ID"])), #pointless, but needed
            xlab = "S factor",
            ylab="fraction with long tertiary education")

scatterplot(Sfactor.scores2 ~ LV2012estimatedIQ, #predict S factor from IQ
            data=DF2,
            smoother=NULL, #no moving average
            labels=unlist(read["ID"]), #labels, but they dont work
            id.n = length(unlist(read["ID"])), #pointless, but needed
            xlab = "National IQ in home country",
            ylab="General socioeconomic factor (S) in Norway",
            main = "National IQ predicts immigrant group performance at the group level in Norway")

scatterplot(Sfactor.scores2 ~ IslamPewResearch2010, #predict S factor from Islam
            data=DF2,
            smoother=NULL, #no moving average
            labels=unlist(read["ID"]), #labels, but they dont work
            id.n = length(unlist(read["ID"])), #pointless, but needed
            xlab = "National prevalence of Islam in home country",
            ylab="General socioeconomic factor (S) in Norway",
            main = "National Islam prevalence predicts immigrant group performance at the group level in Norway")


As you can see, I am using multiple imputation. There seems to be a bug becus MI fucks up one of the variables, but only that one (Norway.tertiary.edu.att.bigsamples.2013). And the fuck-up has no effect on the factor analysis (S factors from the complete cases dataset correlates .99 or 1.00 with the ones from the imputed datasets). However, it has changed the data of the cases with actual data and changed the mean and the standard deviation. Everything else seems fine. Odd?

It can be seen in the descriptive statistics for each dataset (all data, complete cases, impute 1, impute 2).

Code:
> round(DF.desc.stats.ordered,2)
                                                   vars   n    mean      sd  median trimmed     mad     min      max
NorwayViolentCrimeAdjustedOddsRatioSkardhamar2014     1  26    1.31    0.87    1.25    1.24    1.11    0.20     3.20
NorwayViolentCrimeAdjustedOddsRatioSkardhamar20141    1  15    1.41    0.99    1.50    1.36    1.19    0.20     3.20
NorwayViolentCrimeAdjustedOddsRatioSkardhamar20142    1  18    1.33    0.93    1.15    1.28    0.96    0.20     3.20
NorwayViolentCrimeAdjustedOddsRatioSkardhamar20143    1  26    1.16    0.86    0.85    1.08    0.89   -0.01     3.20
NorwayLarcenyAdjustedOddsRatioSkardhamar2014          2  26    0.77    0.56    0.60    0.74    0.59    0.10     2.00
NorwayLarcenyAdjustedOddsRatioSkardhamar20141         2  15    0.78    0.55    0.50    0.76    0.44    0.20     1.60
NorwayLarcenyAdjustedOddsRatioSkardhamar20142         2  18    0.72    0.53    0.55    0.71    0.44    0.10     1.60
NorwayLarcenyAdjustedOddsRatioSkardhamar20143         2  26    0.60    0.51    0.47    0.58    0.33   -0.26     1.60
Norway.tertiary.edu.att.bigsamples.2013               3  67    0.12    0.08    0.11    0.12    0.09    0.01     0.31
Norway.tertiary.edu.att.bigsamples.20131              3  15    0.10    0.07    0.09    0.10    0.07    0.01     0.23
Norway.tertiary.edu.att.bigsamples.20132              3  18    0.52    0.02    0.52    0.52    0.02    0.50     0.56
Norway.tertiary.edu.att.bigsamples.20133              3  26    0.52    0.02    0.52    0.52    0.02    0.50     0.56
OutOfWork.2010to2014.men                              4 120    7.05    4.18    5.96    6.51    3.62    1.38    22.08
OutOfWork.2010to2014.men1                             4  15    7.40    5.36    5.96    6.64    4.00    2.68    22.08
OutOfWork.2010to2014.men2                             4  18    7.31    4.89    6.53    6.68    4.26    2.68    22.08
OutOfWork.2010to2014.men3                             4  26    6.88    4.30    6.32    6.20    3.38    2.66    22.08
OutOfWork.2010to2014.women                            5 120    7.50    4.97    6.30    6.75    2.95    1.32    31.82
OutOfWork.2010to2014.women1                           5  15    8.90    6.20    7.30    8.40    4.69    1.98    22.42
OutOfWork.2010to2014.women2                           5  18    8.17    5.93    6.48    7.67    4.46    1.90    22.42
OutOfWork.2010to2014.women3                           5  26    7.40    5.25    6.48    6.69    3.53    1.56    22.42
Income.index.2009to2012                               6  23   79.86   14.58   80.25   79.87   13.71   53.25   108.25
Income.index.2009to20121                              6  15   78.78   14.78   78.25   78.48   10.75   53.25   108.25
Income.index.2009to20122                              6  18 6852.23 2415.20 6500.53 6799.16 2890.42 2835.56 11718.06
Income.index.2009to20123                              6  26 6689.35 2268.99 6500.53 6635.00 2031.16 2835.56 11718.06
                                                     range  skew kurtosis     se
NorwayViolentCrimeAdjustedOddsRatioSkardhamar2014     3.00  0.55    -0.83   0.17
NorwayViolentCrimeAdjustedOddsRatioSkardhamar20141    3.00  0.39    -1.25   0.26
NorwayViolentCrimeAdjustedOddsRatioSkardhamar20142    3.00  0.57    -0.94   0.22
NorwayViolentCrimeAdjustedOddsRatioSkardhamar20143    3.21  0.77    -0.28   0.17
NorwayLarcenyAdjustedOddsRatioSkardhamar2014          1.90  0.56    -1.09   0.11
NorwayLarcenyAdjustedOddsRatioSkardhamar20141         1.40  0.38    -1.74   0.14
NorwayLarcenyAdjustedOddsRatioSkardhamar20142         1.50  0.55    -1.42   0.12
NorwayLarcenyAdjustedOddsRatioSkardhamar20143         1.86  0.70    -0.58   0.10
Norway.tertiary.edu.att.bigsamples.2013               0.30  0.42    -0.91   0.01
Norway.tertiary.edu.att.bigsamples.20131              0.22  0.39    -1.32   0.02
Norway.tertiary.edu.att.bigsamples.20132              0.05  0.50    -1.12   0.00
Norway.tertiary.edu.att.bigsamples.20133              0.06  0.75    -0.64   0.00
OutOfWork.2010to2014.men                             20.70  1.26     1.69   0.38
OutOfWork.2010to2014.men1                            19.40  1.38     1.18   1.38
OutOfWork.2010to2014.men2                            19.40  1.57     2.16   1.15
OutOfWork.2010to2014.men3                            19.42  1.80     3.72   0.84
OutOfWork.2010to2014.women                           30.50  1.92     5.11   0.45
OutOfWork.2010to2014.women1                          20.44  0.83    -0.58   1.60
OutOfWork.2010to2014.women2                          20.52  1.03    -0.04   1.40
OutOfWork.2010to2014.women3                          20.86  1.30     1.14   1.03
Income.index.2009to2012                              55.00 -0.01    -0.92   3.04
Income.index.2009to20121                             55.00  0.19    -0.78   3.82
Income.index.2009to20122                           8882.50  0.20    -0.97 569.27
Income.index.2009to20123                           8882.50  0.24    -0.74 444.99



Attached Files
.csv   Megadataset_v1.4.csv (Size: 197.93 KB / Downloads: 574)
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Messages In This Thread
[ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Aug-27, 03:05:37
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Aug-27, 20:30:31
Reply to MH - by Emil - 2014-Aug-28, 01:07:46
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Aug-28, 22:01:59
New draft - by Emil - 2014-Aug-29, 16:29:58
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Dalliard - 2014-Aug-29, 17:02:43
Reply to Dalliard - by Emil - 2014-Aug-29, 18:31:43
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Peter Frost - 2014-Aug-29, 20:04:19
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Aug-29, 20:09:06
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Aug-30, 19:24:13
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-06, 19:41:43
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-07, 02:02:18
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-07, 19:34:07
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Duxide - 2014-Aug-31, 18:57:38
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Aug-31, 20:56:05
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Duxide - 2014-Aug-31, 21:06:48
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Peter Frost - 2014-Sep-01, 20:23:32
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-07, 20:57:28
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Dalliard - 2014-Sep-09, 22:20:28
Dalliard - by Emil - 2014-Sep-10, 23:02:32
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-11, 17:36:29
Imputation - by Emil - 2014-Sep-11, 19:25:46
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-11, 20:27:46
Number of imputations - by Emil - 2014-Sep-11, 20:44:14
VIM - by Emil - 2014-Sep-11, 23:56:02
New draft - by Emil - 2014-Sep-12, 04:16:01
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-12, 23:54:29
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-12, 19:54:07
New draft, 16th sep. - by Emil - 2014-Sep-16, 06:37:57
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-16, 19:23:25
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-16, 21:00:46
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-16, 22:58:16
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Dalliard - 2014-Sep-16, 23:54:09
Dalliard's nth review - by Emil - 2014-Sep-17, 01:51:01
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-18, 02:52:34
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-18, 15:24:41
Minding my P's and V's - by Emil - 2014-Sep-18, 15:26:09
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-23, 21:08:42
Predictor vectors terminology - by Emil - 2014-Sep-23, 22:40:18
Predictor x outcome interaction - by Emil - 2014-Sep-18, 17:10:48
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-18, 18:06:15
Revision, 22.09 - by Emil - 2014-Sep-22, 01:21:31
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Philbrick Bastinado - 2014-Sep-22, 03:19:27
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-23, 09:41:00
Storing files on OSF - by Emil - 2014-Sep-23, 22:53:26
Meisenberg's review - by Emil - 2014-Sep-24, 22:44:49
Reply to Meisenberg - by Emil - 2014-Sep-25, 07:04:29
RE: [ODP] Crime, income and employment - by Dalliard - 2014-Sep-25, 17:45:04
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-25, 18:10:20
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Dalliard - 2014-Sep-25, 18:21:01
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-26, 00:49:07
"interaction" and predictor intercors - by Emil - 2014-Sep-26, 01:43:06
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-27, 03:07:12
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-27, 06:16:27
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-29, 01:43:11
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Sep-29, 01:11:47
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-29, 07:39:07
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Sep-29, 18:41:06
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Dalliard - 2014-Sep-29, 20:28:23
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Sep-29, 20:59:51
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Peter Frost - 2014-Oct-02, 04:28:11
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-03, 13:25:35
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Peter Frost - 2014-Oct-03, 22:26:31
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-04, 13:26:57
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Peter Frost - 2014-Oct-04, 16:26:41
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Oct-04, 18:00:08
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-04, 19:44:05
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Oct-04, 21:11:30
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-05, 01:08:29
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Oct-06, 19:35:06
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Duxide - 2014-Oct-06, 22:48:18
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Oct-09, 00:07:14
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-09, 01:56:33
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Meng Hu - 2014-Oct-09, 02:32:53
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-09, 03:10:57
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Oct-09, 08:08:41
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-09, 08:11:38
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Chuck - 2014-Oct-09, 18:38:10
RE: [ODP] Crime, income and employment among immigrant groups in Norway and Finland - by Emil - 2014-Oct-09, 20:41:57
 
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