Publications by Ali
New PTH
res2 <- compareGroups(sex ~ kind_headache+ education, data = PTH) ## Warning in chisq.test(xx, correct = FALSE): Chi-squared approximation may be ## incorrect createTable(res2, show.ratio = TRUE) ## ## --------Summary descriptives table by 'sex'--------- ## ## _________________________________________________________________________________...
515 sym R (68711 sym/53 pcs) 27 img 15 tbl
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Q9.2 Have you ever applied for State or Federal employment? Q9.3.1 When you applied for State or Federal employment, have you claimed: - A 5-point Veteran’s Preference Q9.3.2 When you applied for State or Federal employment, have you claimed: - A 10-point Veteran’s Preference Q9.4 How many times have you applied to a job claiming a 5-point Ve...
6965 sym 10 tbl
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Q8.2 Post 9/11 Pre 9/11 Overall Female(N=326) Male(N=261) Other(N=6) Female(N=118) Male(N=465) Other(N=7) Female(N=444) Male(N=726) Other(N=13) Q8.2 Just a little 84 (25.8%) 53 (20.3%) 2 (33.3%) 20 (16.9%) 80 (17.2%) 1 (14.3%) 104 (23.4%) 133 (18.3%) 3 (23.1%) Not at all 49 (15.0%) 70 (26.8%) 2 (33.3%) 37 (31.4%) 230 (49.5%) 3 (42.9%) 86 (19...
7045 sym 21 tbl
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Factors about continuing education (Veteran) Female Male Other Overall Post 9/11(N=326) Pre 9/11(N=118) Post 9/11(N=262) Pre 9/11(N=466) Post 9/11(N=6) Pre 9/11(N=7) Post 9/11(N=594) Pre 9/11(N=591) I.had.to.provide.for.take.care.of.a.spouse.partner No 232 (71.2%) 90 (76.3%) 176 (67.2%) 330 (70.8%) 6 (100%) 5 (71.4%) 414 (69.7%) 425 (71.9%) ...
15974 sym R (587 sym/5 pcs) 9 tbl
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#df_v[df_v == "No Info"] <- NA #df_v[df_v == "NEFTQ"] <- NA #write.csv(Q2.5_exp, file = 'Serve_date.csv') serve_date<- read.csv("C:/Users/u6032404/OneDrive/backup 9.9.19/MJ/NDAA/CODE_Q/Serve_date.csv",header = T) serve_date$September<- as.factor(serve_date$September) serve_date$NEFTQ<- as.factor(serve_date$NEFTQ) library(dplyr) serve_da...
3679 sym R (4455 sym/4 pcs) 1 tbl
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Veteran survey – please separate by pre/post 9-11 and gender (only men and women) Q17.3 In the past year (12 months), how many places have you/your family lived? Q17.5 Are you worried or concerned that in the next 60 days you may not have stable housing that you own, rent, or share with others as part of a household? For the non-Veterans, I’d...
4222 sym R (738 sym/4 pcs) 4 tbl
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## Loading required package: carData ## ## Attaching package: 'ROCit' ## The following object is masked from 'package:car': ## ## logit psychological + health ## ## Method used: empirical ## Number of positive(s): 175 ## Number of negative(s): 79 ## Area under curve: 0.7957 ## ...
163 sym R (7376 sym/33 pcs) 12 img
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Q8.6 TAP Q8.7 TAP_yr Q8.8 TAP_length Q8.9 TAP_effective Q8.6 Post 9/11 Pre 9/11 Overall Female(N=326) Male(N=261) Female(N=118) Male(N=465) Female(N=444) Male(N=726) Q8.6 No 244 (74.8%) 137 (52.5%) 73 (61.9%) 229 (49.2%) 317 (71.4%) 366 (50.4%) TAP was not available when I served and discharged 26 (8.0%) 28 (10.7%) 31 (26.3%) 211 (45.4%) 57...
3504 sym 4 tbl
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Example 1 (mean=0, sd =365) library(dplyr) ## ## 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 set.seed(100) age <- sample(seq(as.Date('1960-01-01'), as.Date('1985-01-01'), b...
479 sym R (3032 sym/24 pcs) 8 img
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knitr::include_graphics("1PRO.png") getwd() ## [1] "C:/Users/ali_r/OneDrive/backup 9.9.19/MJ/Minute/2 year" ## ## 1 2 3 4 ## 83 93 86 458 ## ## 1 2 3 4 ## 0.1152778 0.1291667 0.1194444 0.6361111 ## [1] 721 ## [1] 30 ## [1] 720 ## [1] 720 ## [1] 720 ## [1] 721 ## ## 1 2 4 ## 94 93 5...
20 sym R (408 sym/13 pcs) 3 img