##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats 1.0.1 ✔ readr 2.1.5
## ✔ ggplot2 4.0.0 ✔ stringr 1.5.2
## ✔ lubridate 1.9.4 ✔ tibble 3.3.0
## ✔ purrr 1.1.0 ✔ tidyr 1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
##
## Attaching package: 'naniar'
## The following object is masked from 'package:skimr':
##
## n_complete
Data summary
| Name |
R2W_2 |
| Number of rows |
23484 |
| Number of columns |
10 |
| _______________________ |
|
| Column type frequency: |
|
| character |
3 |
| numeric |
7 |
| ________________________ |
|
| Group variables |
None |
Variable type: character
| intake_agency |
0 |
1.00 |
0 |
27 |
58 |
8 |
0 |
| main_agency |
4446 |
0.81 |
13 |
27 |
0 |
7 |
0 |
| race |
697 |
0.97 |
5 |
8 |
0 |
4 |
0 |
Variable type: numeric
| eligibility |
0 |
1.00 |
1.00 |
0.00 |
1 |
1 |
1 |
1 |
1 |
▁▁▇▁▁ |
| male |
100 |
1.00 |
0.37 |
0.48 |
0 |
0 |
0 |
1 |
1 |
▇▁▁▁▅ |
| disabled |
1174 |
0.95 |
0.08 |
0.27 |
0 |
0 |
0 |
0 |
1 |
▇▁▁▁▁ |
| married |
0 |
1.00 |
0.15 |
0.36 |
0 |
0 |
0 |
0 |
1 |
▇▁▁▁▂ |
| military |
0 |
1.00 |
0.05 |
0.22 |
0 |
0 |
0 |
0 |
1 |
▇▁▁▁▁ |
| age |
1 |
1.00 |
33.40 |
10.94 |
17 |
25 |
31 |
40 |
82 |
▇▆▂▁▁ |
| success |
7316 |
0.69 |
0.40 |
0.49 |
0 |
0 |
0 |
1 |
1 |
▇▁▁▁▆ |
## eligibility male disabled married
## Min. :1 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:1 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :1 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :1 Mean :0.3663 Mean :0.08122 Mean :0.1533
## 3rd Qu.:1 3rd Qu.:1.0000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1 Max. :1.0000 Max. :1.00000 Max. :1.0000
## NA's :100 NA's :1174
## military age intake_agency main_agency
## Min. :0.00000 Min. :17.0 Length:23484 Length:23484
## 1st Qu.:0.00000 1st Qu.:25.0 Class :character Class :character
## Median :0.00000 Median :31.0 Mode :character Mode :character
## Mean :0.05344 Mean :33.4
## 3rd Qu.:0.00000 3rd Qu.:40.0
## Max. :1.00000 Max. :82.0
## NA's :1
## success race
## Min. :0.0000 Length:23484
## 1st Qu.:0.0000 Class :character
## Median :0.0000 Mode :character
## Mean :0.4022
## 3rd Qu.:1.0000
## Max. :1.0000
## NA's :7316
## Rows: 23,484
## Columns: 10
## $ eligibility <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ male <dbl> 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0,…
## $ disabled <dbl> 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1…
## $ married <dbl> 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ military <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ age <int> 45, 37, 36, 25, 42, 37, 43, 47, 43, 23, 20, 31, 35, 32, …
## $ intake_agency <chr> "Workforce Solutions Alamo", "Workforce Solutions Alamo"…
## $ main_agency <chr> "Workforce Solutions Alamo", "Workforce Solutions Alamo"…
## $ success <dbl> NA, NA, 1, NA, NA, NA, 1, 1, NA, NA, 1, 1, 1, 1, 1, 1, 1…
## $ race <chr> "hispanic", "hispanic", "hispanic", "hispanic", "other",…
| Characteristic |
N = 23,484 |
| eligibility |
|
| 1 |
23,484 (100%) |
| male |
8,565 (37%) |
| Unknown |
100 |
| disabled |
1,812 (8.1%) |
| Unknown |
1,174 |
| married |
3,600 (15%) |
| military |
1,255 (5.3%) |
| age |
31 (25, 40) |
| Unknown |
1 |
| intake_agency |
|
| |
58 (0.2%) |
| Alamo Colleges District |
8,331 (35%) |
| COSA Dept of Human Services |
41 (0.2%) |
| Goodwill of San Antonio |
251 (1.1%) |
| Hallmark University |
291 (1.2%) |
| Project QUEST |
3,890 (17%) |
| Restore Education |
502 (2.1%) |
| Workforce Solutions Alamo |
10,120 (43%) |
| main_agency |
|
| Alamo Colleges District |
8,244 (43%) |
| COSA Dept of Human Services |
79 (0.4%) |
| Goodwill of San Antonio |
253 (1.3%) |
| Hallmark University |
291 (1.5%) |
| Project QUEST |
3,258 (17%) |
| Restore Education |
829 (4.4%) |
| Workforce Solutions Alamo |
6,084 (32%) |
| Unknown |
4,446 |
| success |
6,503 (40%) |
| Unknown |
7,316 |
| race |
|
| black |
4,865 (21%) |
| hispanic |
14,140 (62%) |
| other |
1,007 (4.4%) |
| white |
2,775 (12%) |
| Unknown |
697 |
## # A tibble: 10 × 3
## variable n_miss pct_miss
## <chr> <int> <num>
## 1 success 7316 31.2
## 2 main_agency 4446 18.9
## 3 disabled 1174 5.00
## 4 race 697 2.97
## 5 male 100 0.426
## 6 age 1 0.00426
## 7 eligibility 0 0
## 8 married 0 0
## 9 military 0 0
## 10 intake_agency 0 0
##
## Call:
## glm(formula = success_miss ~ male + disabled + married + military +
## age + intake_agency + main_agency + race, data = R2W_2)
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0447411 0.1225183 0.365 0.71498
## male -0.0036721 0.0069888 -0.525 0.59930
## disabled 0.0595533 0.0124761 4.773 1.83e-06
## married -0.0262937 0.0093383 -2.816 0.00487
## military -0.0093073 0.0162833 -0.572 0.56761
## age 0.0013447 0.0003174 4.237 2.28e-05
## intake_agencyAlamo Colleges District 0.2543178 0.1218859 2.087 0.03695
## intake_agencyCOSA Dept of Human Services -0.1286731 0.1146462 -1.122 0.26173
## intake_agencyGoodwill of San Antonio 0.0828720 0.3457144 0.240 0.81056
## intake_agencyHallmark University -0.0291130 0.1249104 -0.233 0.81571
## intake_agencyProject QUEST 0.3765896 0.1752833 2.148 0.03169
## intake_agencyRestore Education 0.0228652 0.1552185 0.147 0.88289
## intake_agencyWorkforce Solutions Alamo 0.0884807 0.1521523 0.582 0.56089
## main_agencyCOSA Dept of Human Services 0.4697038 0.0884152 5.312 1.09e-07
## main_agencyGoodwill of San Antonio -0.1431109 0.3313487 -0.432 0.66582
## main_agencyHallmark University NA NA NA NA
## main_agencyProject QUEST -0.2816305 0.1356364 -2.076 0.03787
## main_agencyRestore Education 0.1685019 0.1218837 1.382 0.16684
## main_agencyWorkforce Solutions Alamo 0.0528161 0.1195885 0.442 0.65875
## racehispanic -0.0011854 0.0084042 -0.141 0.88783
## raceother 0.0106804 0.0174811 0.611 0.54123
## racewhite 0.0008137 0.0121339 0.067 0.94654
##
## (Intercept)
## male
## disabled ***
## married **
## military
## age ***
## intake_agencyAlamo Colleges District *
## intake_agencyCOSA Dept of Human Services
## intake_agencyGoodwill of San Antonio
## intake_agencyHallmark University
## intake_agencyProject QUEST *
## intake_agencyRestore Education
## intake_agencyWorkforce Solutions Alamo
## main_agencyCOSA Dept of Human Services ***
## main_agencyGoodwill of San Antonio
## main_agencyHallmark University
## main_agencyProject QUEST *
## main_agencyRestore Education
## main_agencyWorkforce Solutions Alamo
## racehispanic
## raceother
## racewhite
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.190495)
##
## Null deviance: 3468.6 on 17582 degrees of freedom
## Residual deviance: 3345.5 on 17562 degrees of freedom
## (5901 observations deleted due to missingness)
## AIC: 20766
##
## Number of Fisher Scoring iterations: 2
## [1] 16168
## [1] 7316
##
## Call:
## glm(formula = main_agency_miss ~ male + disabled + married +
## military + age + success + race, data = R2W_2)
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0912801 0.0112441 8.118 5.10e-16 ***
## male 0.0051706 0.0060759 0.851 0.394781
## disabled -0.0141571 0.0113429 -1.248 0.212012
## married -0.0087003 0.0080883 -1.076 0.282096
## military 0.0499431 0.0135482 3.686 0.000228 ***
## age 0.0019048 0.0002764 6.892 5.73e-12 ***
## success 0.0419173 0.0058657 7.146 9.33e-13 ***
## racehispanic -0.0393141 0.0072231 -5.443 5.33e-08 ***
## raceother 0.0063876 0.0151213 0.422 0.672723
## racewhite -0.0264513 0.0104391 -2.534 0.011291 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1232315)
##
## Null deviance: 1869.9 on 15017 degrees of freedom
## Residual deviance: 1849.5 on 15008 degrees of freedom
## (8466 observations deleted due to missingness)
## AIC: 11188
##
## Number of Fisher Scoring iterations: 2
## [1] 19038
## [1] 4446
##
## Call:
## glm(formula = success ~ male + disabled + military + married +
## age + race, data = R2W_2)
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3578047 0.0153719 23.277 < 2e-16 ***
## male 0.0925661 0.0084212 10.992 < 2e-16 ***
## disabled -0.0479609 0.0157796 -3.039 0.002374 **
## military -0.0577141 0.0188473 -3.062 0.002201 **
## married 0.0385373 0.0112511 3.425 0.000616 ***
## age 0.0003441 0.0003846 0.895 0.370987
## racehispanic 0.0021915 0.0100515 0.218 0.827411
## raceother -0.0103909 0.0210422 -0.494 0.621448
## racewhite 0.0090200 0.0145265 0.621 0.534652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.2386339)
##
## Null deviance: 3618.0 on 15017 degrees of freedom
## Residual deviance: 3581.7 on 15009 degrees of freedom
## (8466 observations deleted due to missingness)
## AIC: 21112
##
## Number of Fisher Scoring iterations: 2
## (Intercept) male disabled military married age
## 1.4301863 1.0969857 0.9531711 0.9439198 1.0392895 1.0003442
## racehispanic raceother racewhite
## 1.0021939 0.9896629 1.0090608
##
## Call:
## glm(formula = success ~ main_agency + intake_agency, data = R2W_2)
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.5506 0.2794 1.970 0.04880
## main_agencyCOSA Dept of Human Services -0.1340 0.2433 -0.551 0.58190
## main_agencyGoodwill of San Antonio -1.1953 0.4392 -2.722 0.00650
## main_agencyHallmark University -0.4270 0.2809 -1.520 0.12853
## main_agencyProject QUEST -0.2274 0.5530 -0.411 0.68090
## main_agencyRestore Education -0.6491 0.2831 -2.293 0.02186
## main_agencyWorkforce Solutions Alamo -0.7033 0.2812 -2.501 0.01238
## intake_agencyAlamo Colleges District -0.2743 0.2794 -0.982 0.32614
## intake_agencyCOSA Dept of Human Services 0.4994 0.1781 2.804 0.00505
## intake_agencyGoodwill of San Antonio 1.0422 0.4164 2.503 0.01233
## intake_agencyHallmark University NA NA NA NA
## intake_agencyProject QUEST 0.1527 0.5341 0.286 0.77501
## intake_agencyRestore Education 0.6678 0.2456 2.719 0.00656
## intake_agencyWorkforce Solutions Alamo 0.6215 0.2422 2.566 0.01029
##
## (Intercept) *
## main_agencyCOSA Dept of Human Services
## main_agencyGoodwill of San Antonio **
## main_agencyHallmark University
## main_agencyProject QUEST
## main_agencyRestore Education *
## main_agencyWorkforce Solutions Alamo *
## intake_agencyAlamo Colleges District
## intake_agencyCOSA Dept of Human Services **
## intake_agencyGoodwill of San Antonio *
## intake_agencyHallmark University
## intake_agencyProject QUEST
## intake_agencyRestore Education **
## intake_agencyWorkforce Solutions Alamo *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.2266987)
##
## Null deviance: 3290.0 on 13823 degrees of freedom
## Residual deviance: 3130.9 on 13811 degrees of freedom
## (9660 observations deleted due to missingness)
## AIC: 18729
##
## Number of Fisher Scoring iterations: 2
## (Intercept)
## 1.7343616
## main_agencyCOSA Dept of Human Services
## 0.8746139
## main_agencyGoodwill of San Antonio
## 0.3026065
## main_agencyHallmark University
## 0.6524616
## main_agencyProject QUEST
## 0.7965760
## main_agencyRestore Education
## 0.5224995
## main_agencyWorkforce Solutions Alamo
## 0.4949415
## intake_agencyAlamo Colleges District
## 0.7600805
## intake_agencyCOSA Dept of Human Services
## 1.6477187
## intake_agencyGoodwill of San Antonio
## 2.8353690
## intake_agencyHallmark University
## NA
## intake_agencyProject QUEST
## 1.1649479
## intake_agencyRestore Education
## 1.9500038
## intake_agencyWorkforce Solutions Alamo
## 1.8617814
##
## Attaching package: 'mice'
## The following object is masked from 'package:stats':
##
## filter
## The following objects are masked from 'package:base':
##
## cbind, rbind
## Warning: Number of logged events: 3