A generics::tidy() method for fits from cjoint::amce(): one row per attribute level, with normal-approximation confidence intervals.
Usage
# S3 method for class 'amce'
tidy(x, alpha = 0.05, ...)Arguments
- x
A fit from
cjoint::amce().- alpha
The significance level for the confidence intervals. Defaults to 0.05, which gives 95 percent intervals.
- ...
Not used.
Value
A data frame with columns attribute, level, estimate, std.error, statistic, p.value, conf.low, and conf.high.
Examples
# \donttest{
library(cjoint)
#> Loading required package: sandwich
#> Loading required package: lmtest
#> Loading required package: zoo
#>
#> Attaching package: ‘zoo’
#> The following objects are masked from ‘package:base’:
#>
#> as.Date, as.Date.numeric
#> Loading required package: survey
#> Loading required package: grid
#> Loading required package: Matrix
#> Loading required package: survival
#>
#> Attaching package: ‘survey’
#> The following object is masked from ‘package:graphics’:
#>
#> dotchart
#> cjoint: AMCE Estimator for Conjoint Experiments
#> Version: 2.1.3
#> Authors: Soubhik Barari [aut],
#> Elissa Berwick [aut],
#> Jens Hainmueller [aut],
#> Daniel Hopkins [aut],
#> Sean Liu [aut],
#> Anton Strezhnev [aut, cre],
#> Teppei Yamamoto [aut]
data(immigrationconjoint)
data(immigrationdesign)
# Run AMCE estimator using all attributes in the design
results <- amce(Chosen_Immigrant ~ Gender + Education + `Language Skills` +
`Country of Origin` + Job + `Job Experience` + `Job Plans` +
`Reason for Application` + `Prior Entry`, data = immigrationconjoint,
cluster = TRUE, respondent.id = "CaseID", design = immigrationdesign)
tidy(results)
#> attribute level estimate std.error
#> 1 Country of Origin Germany 0.047160626 0.016671472
#> 2 Country of Origin France 0.026912000 0.017382320
#> 3 Country of Origin Mexico 0.010474179 0.017579179
#> 4 Country of Origin Philippines 0.034025766 0.017482232
#> 5 Country of Origin Poland 0.032579818 0.017653990
#> 6 Country of Origin China -0.011254307 0.019551176
#> 7 Country of Origin Sudan -0.051811584 0.019958733
#> 8 Country of Origin Somalia -0.053097324 0.019408848
#> 9 Country of Origin Iraq -0.112660797 0.020362819
#> 10 Education 4th grade 0.033068508 0.015010234
#> 11 Education 8th grade 0.057744013 0.015013278
#> 12 Education high school 0.119483476 0.015154028
#> 13 Education two-year college 0.148820530 0.017368527
#> 14 Education college degree 0.180076992 0.017560545
#> 15 Education graduate degree 0.176068029 0.016749075
#> 16 Gender male -0.026023159 0.008040397
#> 17 Job waiter -0.006814709 0.016914981
#> 18 Job child care provider 0.014886098 0.016865958
#> 19 Job gardener 0.013171373 0.016940321
#> 20 Job financial analyst 0.063934683 0.029772752
#> 21 Job construction worker 0.037824466 0.016877341
#> 22 Job teacher 0.073287616 0.016814161
#> 23 Job computer programmer 0.079101210 0.028607217
#> 24 Job nurse 0.084736815 0.016450766
#> 25 Job research scientist 0.127636596 0.028625588
#> 26 Job doctor 0.157302433 0.028799940
#> 27 Job Experience 1-2 years 0.065290374 0.011059530
#> 28 Job Experience 3-5 years 0.107817867 0.011603473
#> 29 Job Experience 5+ years 0.113148256 0.011395097
#> 30 Job Plans contract with employer 0.124929937 0.011723682
#> 31 Job Plans interviews with employer 0.025217294 0.011811404
#> 32 Job Plans no plans to look for work -0.157301077 0.011785335
#> 33 Language Skills broken English -0.056319723 0.011352484
#> 34 Language Skills tried English but unable -0.126359527 0.011409971
#> 35 Language Skills used interpreter -0.159740917 0.011629605
#> 36 Prior Entry once as tourist 0.055954954 0.012506698
#> 37 Prior Entry many times as tourist 0.054748425 0.012957702
#> 38 Prior Entry six months with family 0.075317887 0.012647739
#> 39 Prior Entry once w/o authorization -0.110084275 0.013072266
#> 40 Reason for Application seek better job -0.038318972 0.008978289
#> 41 Reason for Application escape persecution 0.055634454 0.016908419
#> statistic p.value conf.low conf.high
#> 1 2.8288220 4.671968e-03 0.0144851413 0.07983611
#> 2 1.5482398 1.215646e-01 -0.0071567208 0.06098072
#> 3 0.5958286 5.512897e-01 -0.0239803797 0.04492874
#> 4 1.9463056 5.161804e-02 -0.0002387791 0.06829031
#> 5 1.8454648 6.496995e-02 -0.0020213667 0.06718100
#> 6 -0.5756332 5.648631e-01 -0.0495739084 0.02706529
#> 7 -2.5959354 9.433379e-03 -0.0909299825 -0.01269318
#> 8 -2.7357278 6.224249e-03 -0.0911379667 -0.01505668
#> 9 -5.5326718 3.153893e-08 -0.1525711900 -0.07275040
#> 10 2.2030641 2.759023e-02 0.0036489891 0.06248803
#> 11 3.8461961 1.199658e-04 0.0283185283 0.08716950
#> 12 7.8846018 3.155402e-15 0.0897821271 0.14918483
#> 13 8.5684027 1.049303e-17 0.1147788432 0.18286222
#> 14 10.2546354 1.128009e-24 0.1456589551 0.21449503
#> 15 10.5121046 7.597876e-26 0.1432404450 0.20889561
#> 16 -3.2365512 1.209835e-03 -0.0417820481 -0.01026427
#> 17 -0.4028801 6.870364e-01 -0.0399674639 0.02633805
#> 18 0.8826121 3.774459e-01 -0.0181705721 0.04794277
#> 19 0.7775161 4.368543e-01 -0.0200310460 0.04637379
#> 20 2.1474227 3.175965e-02 0.0055811617 0.12228820
#> 21 2.2411389 2.501708e-02 0.0047454851 0.07090345
#> 22 4.3586841 1.308468e-05 0.0403324663 0.10624277
#> 23 2.7650788 5.690905e-03 0.0230320943 0.13517033
#> 24 5.1509344 2.591918e-07 0.0524939070 0.11697972
#> 25 4.4588289 8.240869e-06 0.0715314752 0.18374172
#> 26 5.4619014 4.710617e-08 0.1008555882 0.21374928
#> 27 5.9035395 3.557843e-09 0.0436140931 0.08696666
#> 28 9.2918621 1.516123e-20 0.0850754790 0.13056026
#> 29 9.9295561 3.096308e-23 0.0908142762 0.13548224
#> 30 10.6562033 1.631214e-26 0.1019519424 0.14790793
#> 31 2.1349955 3.276138e-02 0.0020673680 0.04836722
#> 32 -13.3471879 1.230053e-40 -0.1803999091 -0.13420225
#> 33 -4.9610045 7.012955e-07 -0.0785701821 -0.03406926
#> 34 -11.0744824 1.668414e-28 -0.1487226603 -0.10399639
#> 35 -13.7357127 6.204256e-43 -0.1825345244 -0.13694731
#> 36 4.4739991 7.677008e-06 0.0314422770 0.08046763
#> 37 4.2251645 2.387663e-05 0.0293517947 0.08014505
#> 38 5.9550477 2.599960e-09 0.0505287747 0.10010700
#> 39 -8.4212085 3.726204e-17 -0.1357054444 -0.08446310
#> 40 -4.2679592 1.972694e-05 -0.0559160957 -0.02072185
#> 41 3.2903404 1.000662e-03 0.0224945619 0.08877435
# }