rm(list=ls())
# Load libraries ---------------------------
library(foreign)
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 wd for generated output ---------------------------
#setwd("/Volumes/caas-1/CMHIV/WISE/AK-R-output")
setwd("/Volumes/caas/CMHIV/WISE/AK-R-output")
# Read data ----- ----------------------
vuln_spss <- read.spss("../WISE_FULL_4-17.sav")
## Warning in read.spss("../WISE_FULL_4-17.sav"): ../WISE_FULL_4-17.sav: Long
## string missing values record found (record type 7, subtype 22), but ignored
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1954, 1955,
## 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968,
## 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981,
## 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 6157 added in
## variable: demo1
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 0.08333,
## 0.126, 0.14, 0.16666, 0.173, 0.219, 0.24999, 0.33332, 0.378, 0.41665, 0.49998,
## 0.58331, 0.66664, 0.74997, 0.8333, 0.91663, 1, 1.058, 1.082, 1.08333, 1.16666,
## 1.24999, 1.33332, 1.41665, 1.49998, 1.58331, 1.66664, 1.74997, 1.8333, 1.91663,
## 2, 2.033, 2.082, 2.16666, 2.24999, 2.33332, 2.41665, 2.49998, 3, 3.24999,
## 3.33332, 3.58331, 3.8333, 4, 4.16666, 4.49998, 4.8333, 5, 5.24999, 5.49998,
## 6.08333, 6.24999, 6.58331, 6.66664, 7, 7.49998, 9 added in variable: smhis1
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 9, 14, 30, 36 added in variable: smhis1y
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11 added in variable: smhis1m
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1757, 2067,
## 2804, 2807, 2809, 2813, 2816, 2818, 2825, 2828, 2830, 2832, 2838, 2840, 2842,
## 2852, 2860, 2861, 2863, 2864, 2865, 2874, 2879, 2882, 2883, 2885, 2886, 2887,
## 2888, 2889, 2891, 2892, 2893, 2895, 2896, 2903, 2904, 2905, 2906, 2907, 2908,
## 2909, 2910, 2911, 2914, 2915, 2919, 2920, 2921, 20920, 28400, 28955, 29200
## added in variable: demo8
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5 added in variable: hlth4
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 5, 6, 7,
## 8, 9, 10, 11, 12, 13, 15, 18, 20, 21, 22, 25, 28, 30, 33, 35, 38, 40, 45, 60,
## 90 added in variable: ftnd2
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 5, 6, 7, 8,
## 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 30, 32,
## 34 added in variable: smhis3
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 8, 9, 10,
## 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 29, 30, 33, 34,
## 35 added in variable: smhis4
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
## 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 42, 44, 45, 48
## added in variable: smhis5
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 20, 24, 25, 50 added in variable: smhis6
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 7, 8, 9, 10, 11, 12, 13, 15, 17, 18 added in variable: smhis7
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 0.002738,
## 0.0054756, 0.005476, 0.008213, 0.010951, 0.013689, 0.019165, 0.021902,
## 0.027378, 0.032854, 0.038329, 0.04928, 0.068445, 0.073921, 0.079396, 0.0793962,
## 0.08333, 0.086068, 0.0888056, 0.116184, 0.124397, 0.16666, 0.180349, 0.207727,
## 0.246056, 0.24999, 0.260941, 0.266417, 0.269155, 0.277368, 0.296533, 0.33332,
## 0.41665, 0.49998, 0.527358, 0.58331, 0.74997, 0.91663, 1, 1.180349, 1.24999,
## 1.258203, 1.33332, 1.485095, 1.49998, 1.516407, 1.672116, 2, 2.099757,
## 2.349747, 2.49998, 3, 3.852465, 4.169398, 4.2554656, 4.841513, 5, 6, 15 added
## in variable: smhis9
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4.3482, 5.3482, 8.6964, 14.0446, 15.0446, 16.0446, 17.3928, 21.741, 24.741,
## 26.0892, 27.0892, 30.4374, 34.7856, 35.7856, 39.1338, 43.482, 47.8302, 52.17,
## 57.5182, 62.8664, 67.2146, 69.5628, 78.2592, 91.3038, 92.3038, 95.652,
## 101.0002, 104.34, 108.6882, 113.0364, 119.3846, 156.51, 208.68, 213.0282,
## 214.0282, 220.3764, 223.7246, 252.162, 260.85, 265.1982, 286.9392, 313.02,
## 327.0646, 330.4128, 363.8502, 365.19, 469.53, 521.7, 573.87, 626.04, 678.21,
## 692.2546, 782.55, 834.72, 991.23, 996.5782 added in variable: smhis10
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 18, 20, 21, 22, 25, 26, 29, 30, 32, 35,
## 36, 52, 60, 86, 90 added in variable: smhis11
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5 added in variable: smhis12
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 4, 5, 6,
## 8, 9, 10, 1010, 1907, 1993, 1994, 1995, 1999, 2000, 2001, 2002, 2003, 2004,
## 2005, 2006, 2007, 2008, 2009, 2010, 2011 added in variable: smhis17
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1, 2, 3, 4,
## 5, 6, 7, 14, 18, 22, 27, 28, 30, 32, 35, 43, 45, 60, 65, 68, 73, 78, 80, 90,
## 93, 99, 110, 120, 130, 135, 140, 145, 150, 155, 172, 180, 190, 200, 210, 217,
## 240, 260, 270, 290, 306, 350, 360, 365, 366, 369, 380, 395, 400, 425, 455, 500,
## 520, 540, 670, 700, 712, 720, 730, 732, 900, 950, 1000, 1080, 1090, 1100, 1180,
## 1200, 1260, 1300, 1360, 1385, 1460, 1500, 1533, 2190, 2400 added in variable:
## smhis18
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 0.041666,
## 0.083332, 0.124998, 0.166664, 0.249996, 0.291662, 0.333328, 0.41666, 0.958318,
## 1, 1.041666, 1.083332, 2, 2.249996, 3, 4, 7, 8.041666, 10, 14, 21, 23.041666,
## 34.499992, 35, 42, 140, 644 added in variable: smhis19
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 3, 4, 5,
## 6, 7, 8, 9 added in variable: smhis24
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 3, 4, 5,
## 6, 7, 8, 9 added in variable: smhis25
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 3, 4, 5,
## 6, 7, 8, 9 added in variable: smhis26
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1, 2, 3, 4,
## 5, 6, 7, 8 added in variable: smhis27
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3
## added in variable: smhis34
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 7, 9, 10 added in variable: smhis35
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 9, 10, 11, 14, 15, 18, 20, 21, 30, 35, 40, 50, 90 added in
## variable: smhis36
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1, 4, 5
## added in variable: smhis37
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1, 2, 3, 4,
## 5, 6, 7 added in variable: smhis38
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 7, 8, 9, 10, 14, 28 added in variable: atsq18
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 9, 20 added in variable: ssq7
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 3, 4, 5,
## 6, 7, 8, 9 added in variable: ssq9
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 2, 3, 4, 5,
## 6, 7, 8, 9 added in variable: ssq10
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 6,
## 7, 10, 12, 15, 18, 20, 21, 25, 30, 40, 45, 50, 60, 63, 65, 70, 75, 80, 90, 100,
## 112, 120, 150, 180, 200, 300, 306 added in variable: opbais7
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 20, 21, 22, 25, 26, 28, 29, 30
## added in variable: drug2
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 20, 24, 30, 40 added in variable:
## drug3
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 18, 20, 22, 25, 28, 29, 30 added in
## variable: drug4
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 10, 15, 20, 30 added in variable: drug7
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 10, 11, 14, 15, 16, 17, 20, 24, 25, 28, 30 added in variable:
## drug8
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5 added in variable: drug9
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 2, 3, 5,
## 10, 30 added in variable: drug11
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 10, 12, 13, 18, 24 added in variable: drug13
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 4
## added in variable: drug14
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 9, 10, 12, 14, 15, 20, 21, 25, 30 added in variable: drug16
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 18, 19, 20, 22, 25, 30, 31, 33 added in
## variable: drug17
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5 added in variable: drug18
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5, 30 added in variable: drug20
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5, 7, 10, 25, 30 added in variable: drug21
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 1, 2, 3
## added in variable: drug22
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 19, 20, 25, 30 added in variable: drug24
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 20, 25, 30, 33 added in variable:
## drug25
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3
## added in variable: drug26
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 20, 22, 25, 28, 29, 30 added in variable:
## drug28
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25,
## 26, 27, 28, 30, 32, 33, 36, 40 added in variable: drug29
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5 added in variable: drug30
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 5,
## 10, 30 added in variable: drug32
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 8, 9, 10, 13, 15, 18, 20, 27 added in variable: drug33
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4 added in variable: drug34
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 10, 15, 20, 21, 22, 25, 28, 29, 30 added in variable: drug36
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25,
## 27, 28, 29, 30, 35, 36, 37, 38, 40, 44 added in variable: drug37
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3
## added in variable: drug38
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 4,
## 5, 7, 8, 9, 10, 15, 20, 30 added in variable: drug40
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 18, 19, 20, 25, 29, 35 added in
## variable: drug41
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3
## added in variable: drug42
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5, 6, 30 added in variable: drug44
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5, 8, 10, 16, 20 added in variable: drug45
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 20, 21, 25, 28, 29, 30 added
## in variable: drug47
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, 24, 25, 26, 27,
## 28, 30, 35, 40 added in variable: drug48
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 12, 15, 17, 18, 20, 30 added in variable: drug52
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 5, 10, 29, 30, 50, 60, 70, 80, 100, 120, 200, 300, 309, 400, 485, 500, 550,
## 580, 600, 636, 660, 675, 683, 700, 713, 714, 750, 798, 800, 900, 950, 1000,
## 1100, 1200, 1400, 1500, 1600, 1700, 2000, 2200, 2400, 2500, 3000, 4000, 4200,
## 4500, 5000, 6000, 7000, 10000, 20000, 30000, 50000 added in variable: sochis1
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 8 added in variable: sochis2
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 18, 22 added in variable: ftnd1h
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 10, 12, 13, 14, 15, 20, 23, 30, 31, 33, 34, 35, 39, 41, 45, 47, 59
## added in variable: ftnd1m
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 15 added in variable: smhis9y
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11 added in variable: smhis9m
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 10, 12, 14, 15, 17, 18, 25, 27, 29 added in variable: smhis9d
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 19 added in variable: smhis10y
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 7, 8, 9, 10, 11 added in variable: smhis10m
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3
## added in variable: smhis10w
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 6, 20, 92 added in variable: smhis19w
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 6 added in variable: smhis19d
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 6, 7, 8, 10, 12, 23 added in variable: smhis19h
## Warning in read.spss("../WISE_FULL_4-17.sav"): Undeclared level(s) 0, 1, 2, 3,
## 4, 5, 10, 11, 12, 13, 15, 18, 20, 22, 25, 30, 40, 45, 60 added in variable:
## w3ftnd2
vuln_dt <- as.data.frame(vuln_spss)
dim(vuln_dt)
## [1] 247 614
sort(colnames(vuln_dt))
## [1] "ACigs21" "ACigs3" "ACigs7"
## [4] "ACigsSmk" "age" "Any_IDUse"
## [7] "Any_IVUse" "Any_UTPos_exMar" "Any_UTPositive"
## [10] "atsq1" "atsq10" "atsq11"
## [13] "atsq12" "atsq13" "atsq14"
## [16] "atsq15" "atsq16" "atsq17"
## [19] "atsq18" "atsq2" "atsq3"
## [22] "atsq4" "atsq5" "atsq6"
## [25] "atsq7" "atsq8" "atsq9"
## [28] "ATSQSC2W" "ATSQSCRE" "bis1"
## [31] "bis10" "bis10r" "bis11"
## [34] "bis12" "bis12r" "bis13"
## [37] "bis13r" "bis14" "bis15"
## [40] "bis15r" "bis16" "bis17"
## [43] "bis18" "bis19" "bis1r"
## [46] "bis2" "bis20" "bis20r"
## [49] "bis21" "bis22" "bis23"
## [52] "bis3" "bis4" "bis5"
## [55] "bis6" "bis7" "bis7r"
## [58] "bis8" "bis8r" "bis9"
## [61] "bis9r" "cesd_scr" "cesd1"
## [64] "cesd10" "cesd2" "cesd3"
## [67] "cesd4" "cesd5" "cesd6"
## [70] "cesd7" "cesd8" "cesd9"
## [73] "cid" "Cig_diff" "cond2"
## [76] "condn" "consmk" "crave1"
## [79] "crave2" "crave3" "crave4"
## [82] "crave5" "cravescr" "D1ATSQ"
## [85] "D1ATSQ1" "D1ATSQ2" "D1ATSQ3"
## [88] "D1ATSQ4" "D1ATSQ5" "D1ATSQ6"
## [91] "D1ATSQ7" "D1ATSQ8" "D2ATSQ"
## [94] "D2ATSQ1" "D2ATSQ2" "D2ATSQ3"
## [97] "D2ATSQ4" "D2ATSQ5" "D2ATSQ6"
## [100] "D2ATSQ7" "D2ATSQ8" "D3ATSQ"
## [103] "D3ATSQ1" "D3ATSQ2" "D3ATSQ3"
## [106] "D3ATSQ4" "D3ATSQ5" "D3ATSQ6"
## [109] "D3ATSQ7" "D3ATSQ8" "D4ATSQ"
## [112] "D4ATSQ1" "D4ATSQ2" "D4ATSQ3"
## [115] "D4ATSQ4" "D4ATSQ5" "D4ATSQ6"
## [118] "D4ATSQ7" "D4ATSQ8" "DATSQ_Q4"
## [121] "DATSQ1" "DATSQ2" "DATSQ3"
## [124] "DATSQ4" "DATSQ5" "DATSQ6"
## [127] "DATSQ7" "DATSQ8" "DATSQSCR"
## [130] "Days1st" "Days1st_inc" "Days1stMar"
## [133] "Days1stTrt" "Days1stUse" "Days2days"
## [136] "Days3days" "Days5cigs" "decbal1"
## [139] "decbal2" "decbal3" "decbal4"
## [142] "decbal5" "decbal6" "decbalsc"
## [145] "demo1" "demo2" "demo2b"
## [148] "demo3" "demo4" "demo4_LEHS"
## [151] "demo4r" "demo4rb" "demo5"
## [154] "demo6" "demo7" "demo7b"
## [157] "demo8" "depr_cat" "depress"
## [160] "DOR" "drug015" "drug1"
## [163] "drug10" "drug11" "drug13"
## [166] "drug14" "drug14a" "drug14b"
## [169] "drug14c" "drug14d" "drug14e"
## [172] "drug16" "drug17" "drug18"
## [175] "drug18a" "drug18b" "drug18c"
## [178] "drug18d" "drug18e" "drug19"
## [181] "drug2" "drug20" "drug21"
## [184] "drug22" "drug22a" "drug22b"
## [187] "drug22c" "drug22d" "drug22e"
## [190] "drug23" "drug24" "drug25"
## [193] "drug26" "drug26a" "drug26b"
## [196] "drug26c" "drug26d" "drug26e"
## [199] "drug27" "drug28" "drug29"
## [202] "drug3" "drug30" "drug30a"
## [205] "drug30b" "drug30c" "drug30d"
## [208] "drug30e" "drug31" "drug32"
## [211] "drug33" "drug34" "drug34a"
## [214] "drug34b" "drug34c" "drug34d"
## [217] "drug34e" "drug35" "drug36"
## [220] "drug37" "drug38" "drug38a"
## [223] "drug38b" "drug38c" "drug38d"
## [226] "drug38e" "drug39" "drug4"
## [229] "drug40" "drug41" "drug42"
## [232] "drug42a" "drug42b" "drug42c"
## [235] "drug42d" "drug42e" "drug43"
## [238] "drug44" "drug45" "drug46"
## [241] "drug47" "drug48" "drug49"
## [244] "drug50" "drug51" "drug52"
## [247] "drug53" "drug54" "drug55"
## [250] "drug6" "drug7" "drug8"
## [253] "drug9" "drug9a" "drug9b"
## [256] "drug9c" "drug9d" "drug9e"
## [259] "drugp1" "educ_lehs" "endtime"
## [262] "Fam_Encourage" "FF_Quit" "fhxmeddx"
## [265] "Final_QuitStatus" "Final_smkStatus" "FPE"
## [268] "FPE_CAT" "FPV" "FPV_CAT"
## [271] "Friend_Encourage" "ftnd1" "ftnd1h"
## [274] "ftnd1m" "FTND1R" "ftnd2"
## [277] "FTND2R" "ftnd3" "ftnd4"
## [280] "ftnd5" "ftnd6" "FTND6R"
## [283] "FTNDSCRE" "gender" "habaff"
## [286] "hass1" "hispanic" "hlth1"
## [289] "hlth2" "hlth2r" "hlth2rb"
## [292] "hlth3" "hlth3b" "hlth4"
## [295] "hlth4a" "hlth4b" "hlth4c"
## [298] "hlth4d" "hlth4e" "hlth4f"
## [301] "hlth5" "hlth6" "imp_attn"
## [304] "imp_attn2" "imp_motor" "imp_nonplan"
## [307] "INFO_Q12" "INFO_Q12r" "INFO_Q567"
## [310] "INFO_Q567d" "info1" "info1r"
## [313] "info2" "info2r" "info3"
## [316] "info4" "info5" "info6"
## [319] "info7" "info8" "isel_appr"
## [322] "isel_belong" "isel_esteem" "isel_tang"
## [325] "isel_total" "JC_SMKG_Code" "latency"
## [328] "Latency_sample" "LivingSitu" "ln_ACigs21"
## [331] "ln_ACigs3" "ln_ACigs7" "ln_ACigsSmk"
## [334] "ln_TotCigs21" "lss1" "lss2"
## [337] "lss3" "lss4" "lss5"
## [340] "lss6" "MedCond_Group" "meddx_count"
## [343] "meddx_meg" "minority" "negaff"
## [346] "newID" "noise1" "noise10"
## [349] "noise11" "noise12" "noise13"
## [352] "noise14" "noise2" "noise3"
## [355] "noise4" "noise5" "noise6"
## [358] "noise7" "noise8" "noise9"
## [361] "nsmmeddx" "NumSmk_Rels" "opbais1"
## [364] "opbais2" "opbais3" "opbais4"
## [367] "opbais5" "opbais6" "opbais7"
## [370] "opbais7a" "OPBIAS4R" "pack_years"
## [373] "pervul1" "pervul2" "pervul3"
## [376] "pervul4" "pervul5" "pervul6"
## [379] "pni_family" "pni_friends" "posaff"
## [382] "PostRel_AnyUse" "PostRel_DrugTrt" "PostRel_MarUse"
## [385] "prosmk" "PSS_Grp" "pss_scre"
## [388] "pss1" "pss10" "pss2"
## [391] "pss3" "pss4" "pss4r"
## [394] "pss5" "pss5r" "pss6"
## [397] "pss7" "pss7r" "pss8"
## [400] "pss8r" "pss9" "Quit_tlfb"
## [403] "Quit2day" "Quit3day" "Quit5cig"
## [406] "race_eth" "Release" "ROB"
## [409] "ROB_CAT" "scrn7" "scrn7r"
## [412] "scrn7r_b" "smdrg30r" "smhis1"
## [415] "smhis1_12m" "smhis1_1m" "smhis1_24m"
## [418] "smhis1_3m" "smhis1_6m" "smhis1_8m"
## [421] "smhis1_original" "smhis10" "smhis10m"
## [424] "smhis10w" "smhis10y" "smhis11"
## [427] "smhis12" "smhis12a" "smhis12b"
## [430] "smhis12c" "smhis12d" "smhis12e"
## [433] "smhis12i" "smhis12j" "smhis12k"
## [436] "smhis12l" "smhis12m" "smhis12n"
## [439] "smhis12o" "smhis12p" "smhis12q"
## [442] "smhis12r" "smhis12s" "smhis12t"
## [445] "smhis13" "smhis14" "smhis15"
## [448] "smhis16" "smhis17" "smhis18"
## [451] "smhis19" "smhis19d" "smhis19h"
## [454] "smhis19w" "smhis1m" "smhis1y"
## [457] "smhis2" "smhis20" "smhis21"
## [460] "smhis22" "smhis23" "smhis24"
## [463] "smhis25" "smhis26" "smhis27"
## [466] "smhis28" "smhis28r" "smhis29"
## [469] "smhis3" "smhis30" "smhis31"
## [472] "smhis32" "smhis33" "smhis34"
## [475] "smhis34a" "smhis34b" "smhis34c"
## [478] "smhis34d" "smhis35" "smhis36"
## [481] "smhis37" "smhis38" "smhis4"
## [484] "smhis5" "smhis6" "smhis7"
## [487] "smhis8" "smhis9" "smhis9d"
## [490] "smhis9m" "smhis9y" "smk_drug"
## [493] "SMKDATE" "SmkDays_Pct" "smkdrg30"
## [496] "smkdxrsk" "SMKTIME" "smmeddx"
## [499] "Smoke_less" "sochis1" "sochis2"
## [502] "sochis2a" "sochis2b" "sochis2c"
## [505] "sochis2d" "sochis2e" "sochis2f"
## [508] "sochis2g" "sochis2h" "sochis2i"
## [511] "sochis2j" "sochis3" "sochis4"
## [514] "sochis5" "spendyr" "ssq_aware"
## [517] "ssq_importance" "ssq_kidhealth" "ssq_smkbeh"
## [520] "ssq_total" "ssq1" "ssq10"
## [523] "ssq11" "ssq12" "ssq13"
## [526] "ssq14" "ssq15" "ssq16"
## [529] "ssq17" "ssq18" "ssq19"
## [532] "ssq1r" "ssq2" "ssq20"
## [535] "ssq21" "ssq22" "ssq23"
## [538] "ssq24" "ssq25" "ssq26"
## [541] "ssq27" "ssq2r" "ssq3"
## [544] "ssq3r" "ssq4" "ssq4r"
## [547] "ssq4rm" "ssq5" "ssq5r"
## [550] "ssq6" "ssq6r" "ssq7"
## [553] "ssq7_r" "ssq7_ra" "ssq8"
## [556] "ssq8r" "ssq9" "stat1"
## [559] "stat10" "stat11" "stat12"
## [562] "stat13" "stat14" "stat15"
## [565] "stat16" "stat2" "stat3"
## [568] "stat4" "stat5" "stat6"
## [571] "stat7" "stat8" "stat9"
## [574] "Sx_group" "temp1" "temp2"
## [577] "temp3" "temp4" "temp5"
## [580] "temp6" "temp7" "temp8"
## [583] "temp9" "test5a" "test5b"
## [586] "test5c" "test5d" "TLFB_Days"
## [589] "TOR" "TOT_ATS1" "Tot_SmkDays"
## [592] "total_medgrp" "TotCigs21" "TotCigs3"
## [595] "TotCigs7" "trt_grp" "UT_Missing"
## [598] "UT1" "UT10" "UT11"
## [601] "UT2" "UT3" "UT4"
## [604] "UT5" "UT6" "UT7"
## [607] "UT8" "UT9" "w3ftnd2"
## [610] "Week3data" "With1Day" "With1Hr"
## [613] "With1Wk" "wtgain"
# Cids to be potentially ignored ---------------------------
cids.to.ignore <- as.character(
c(4019, 4021, 4026, 4027, 4031, 4032, 4040,
4042, 4058, 4075, 4080, 4081, 4087, 4091,
4093, 4104, 4116, 4120, 4121, 4125, 4129,
4138, 4141, 4147, 4153, 4160, 4170, 4180,
8009, 8016, 8027, 8029, 8031, 8033, 8035,
8051, 8052, 8058, 8061, 8062, 8065, 8070,
8071, 8076, 8078, 8082, 8084, 8085, 8088,
8089, 8042)
)
cid_num4 <- substr(vuln_dt$cid, 1, 4)
vuln_dt$cid_num4 <- cid_num4
ids.to.ignore <- which(vuln_dt$cid_num4 %in% cids.to.ignore)
vuln_dt_alt <- vuln_dt[-ids.to.ignore,]
dim(vuln_dt_alt)
## [1] 196 615
# Replace don't know/refuse to answer with NA
#vuln_dt <- na_if(vuln_dt, "Don't Know")
#vuln_dt <- na_if(vuln_dt, "Refuse to Answer")
vuln_dt <- vuln_dt %>%
mutate(across(where(is.character),
~na_if(na_if(., "Don't Know"), "Refuse to Answer")))
# Recreate Table 1 ---------------------------
n <- nrow(vuln_dt)
n_alt <- nrow(vuln_dt_alt)
## age
class(vuln_dt$age)
## [1] "numeric"
summary(vuln_dt$age) # column I
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 19.00 28.00 35.00 35.58 42.75 56.00 5
sd(vuln_dt$age, na.rm = T)
## [1] 9.187048
summary(vuln_dt_alt$age) # column I
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 19.00 27.00 35.00 34.94 42.00 55.00 3
sd(vuln_dt_alt$age, na.rm = T)
## [1] 9.195893
## race ethnicity
class(vuln_dt$race_eth)
## [1] "factor"
summary(vuln_dt$race_eth)
## White, non-Hispanic Hispanic Black, non-Hispanic Other, non-Hispanic
## 127 49 43 25
## NA's
## 3
summary(vuln_dt$race_eth)/n
## White, non-Hispanic Hispanic Black, non-Hispanic Other, non-Hispanic
## 0.51417004 0.19838057 0.17408907 0.10121457
## NA's
## 0.01214575
summary(vuln_dt_alt$race_eth)
## White, non-Hispanic Hispanic Black, non-Hispanic Other, non-Hispanic
## 97 41 35 21
## NA's
## 2
summary(vuln_dt_alt$race_eth)/n_alt
## White, non-Hispanic Hispanic Black, non-Hispanic Other, non-Hispanic
## 0.49489796 0.20918367 0.17857143 0.10714286
## NA's
## 0.01020408
## gender
class(vuln_dt$gender)
## [1] "factor"
summary(vuln_dt$gender)
## Male Female
## 161 86
summary(vuln_dt$gender)/n
## Male Female
## 0.6518219 0.3481781
summary(vuln_dt_alt$gender)
## Male Female
## 133 63
summary(vuln_dt_alt$gender)/n_alt
## Male Female
## 0.6785714 0.3214286
## education level
table(vuln_dt$demo4rb, exclude = NA)
##
## less than HS HS beyond HS
## 157 49 37
table(vuln_dt$demo4rb, exclude = NA)/n
##
## less than HS HS beyond HS
## 0.6356275 0.1983806 0.1497976
## smoking-related medical conditions
class(vuln_dt$smmeddx)
## [1] "factor"
table(vuln_dt$smmeddx, exclude=NA)
##
## No Yes
## 158 89
table(vuln_dt$smmeddx)/n
##
## No Yes
## 0.6396761 0.3603239
## smoking prior to ACI #TRIED FTND2 and FTNDSCRE but the answer is different
summary(as.numeric(as.character(vuln_dt$ftnd2)))
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 2.00 15.00 20.00 21.65 25.00 90.00 3
sd(as.numeric(as.character(vuln_dt$ftnd2)), na.rm = TRUE)
## [1] 11.73011
summary(as.numeric(as.character(vuln_dt_alt$ftnd2)))
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 2.00 15.00 20.00 21.81 25.00 90.00 2
sd(as.numeric(as.character(vuln_dt_alt$ftnd2)), na.rm = TRUE)
## [1] 12.15529
## Years since smoked daily
class(vuln_dt$smhis1_original) #1_original has the correct continuous coding - 1_6m is discretized
## [1] "numeric"
table(vuln_dt$smhis1_original, exclude=NULL)
##
## 0 0.08333 0.126 0.14 0.16666 0.173 0.219 0.24999 0.33332 0.378
## 5 17 1 1 22 1 1 26 16 1
## 0.41665 0.49998 0.58331 0.66664 0.74997 0.8333 0.91663 1 1.058 1.082
## 12 14 13 6 4 6 3 17 1 1
## 1.08333 1.16666 1.24999 1.33332 1.41665 1.49998 1.58331 1.66664 1.74997 1.8333
## 1 4 2 2 3 3 2 6 2 2
## 1.91663 2 2.033 2.082 2.16666 2.24999 2.33332 2.41665 2.49998 3
## 1 6 1 1 2 3 1 1 1 4
## 3.24999 3.33332 3.58331 3.8333 4 4.16666 4.49998 4.8333 5 5.24999
## 2 1 1 1 1 2 2 1 3 1
## 5.49998 6.08333 6.24999 6.58331 6.66664 7 7.49998 9 14 30
## 2 1 2 1 1 1 1 1 1 1
## 36 <NA>
## 1 3
table(vuln_dt$smhis1_original, exclude=NULL)/n
##
## 0 0.08333 0.126 0.14 0.16666 0.173
## 0.020242915 0.068825911 0.004048583 0.004048583 0.089068826 0.004048583
## 0.219 0.24999 0.33332 0.378 0.41665 0.49998
## 0.004048583 0.105263158 0.064777328 0.004048583 0.048582996 0.056680162
## 0.58331 0.66664 0.74997 0.8333 0.91663 1
## 0.052631579 0.024291498 0.016194332 0.024291498 0.012145749 0.068825911
## 1.058 1.082 1.08333 1.16666 1.24999 1.33332
## 0.004048583 0.004048583 0.004048583 0.016194332 0.008097166 0.008097166
## 1.41665 1.49998 1.58331 1.66664 1.74997 1.8333
## 0.012145749 0.012145749 0.008097166 0.024291498 0.008097166 0.008097166
## 1.91663 2 2.033 2.082 2.16666 2.24999
## 0.004048583 0.024291498 0.004048583 0.004048583 0.008097166 0.012145749
## 2.33332 2.41665 2.49998 3 3.24999 3.33332
## 0.004048583 0.004048583 0.004048583 0.016194332 0.008097166 0.004048583
## 3.58331 3.8333 4 4.16666 4.49998 4.8333
## 0.004048583 0.004048583 0.004048583 0.008097166 0.008097166 0.004048583
## 5 5.24999 5.49998 6.08333 6.24999 6.58331
## 0.012145749 0.004048583 0.008097166 0.004048583 0.008097166 0.004048583
## 6.66664 7 7.49998 9 14 30
## 0.004048583 0.004048583 0.004048583 0.004048583 0.004048583 0.004048583
## 36 <NA>
## 0.004048583 0.012145749
summary(as.numeric(vuln_dt$smhis1_original)) # computing mean/sd not appropriate?
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.0000 0.2500 0.5833 1.5155 1.5208 36.0000 3
sd(as.numeric(vuln_dt$smhis1_original), na.rm = T)
## [1] 3.381317
## Age started smoking daily
table(vuln_dt$smhis4)
##
## 2 8 9 10
## 1 1 3 5
## 11 12 13 14
## 12 23 23 40
## 15 16 17 18
## 34 33 10 17
## 19 20 21 22
## 8 8 4 3
## 23 25 26 27
## 4 2 1 1
## 29 30 33 34
## 1 5 1 1
## 35 Don't Know Refuse to Answer Not Applicable
## 1 2 0 0
summary(as.numeric(as.character(vuln_dt$smhis4)))
## Warning in summary(as.numeric(as.character(vuln_dt$smhis4))): NAs introduced by
## coercion
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 2.00 13.00 15.00 15.73 17.00 35.00 5
sd(as.numeric(as.character(vuln_dt$smhis4)), na.rm = TRUE)
## Warning in is.data.frame(x): NAs introduced by coercion
## [1] 4.474919
## Readiness to quit
table(vuln_dt$smhis24)
##
## Not Ready 2 3 4
## 10 12 8 10
## 5 6 7 8
## 27 15 15 23
## 9 Very Ready Don't Know Refuse to Answer
## 11 47 0 0
## Not Applicable
## 66
smhis24.numeric <-
vuln_dt %>%
select(smhis24) %>%
pull()
smhis24.numeric <- recode(smhis24.numeric,
"Not Ready" = "1" ,
"Very Ready" = "10")
table(smhis24.numeric)
## smhis24.numeric
## 1 2 3 4
## 10 12 8 10
## 5 6 7 8
## 27 15 15 23
## 9 10 Don't Know Refuse to Answer
## 11 47 0 0
## Not Applicable
## 66
smhis24.numeric <- as.numeric(as.character(smhis24.numeric))
## Warning: NAs introduced by coercion
summary(smhis24.numeric)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 1.000 5.000 7.000 6.635 10.000 10.000 69
sd(smhis24.numeric, na.rm=TRUE)
## [1] 2.879171
## Motivation
class(vuln_dt$smhis26)
## [1] "factor"
table(vuln_dt$smhis26)
##
## Not at all motivated 2 3
## 15 8 15
## 4 5 6
## 6 31 14
## 7 8 9
## 16 17 16
## Very Motivated Don't Know Refuse to Answer
## 40 0 0
## Not Applicable
## 66
smhis26.numeric <-
vuln_dt %>%
select(smhis26) %>%
pull()
smhis26.numeric <- recode(smhis26.numeric,
"Not at all motivated" = "1" ,
"Very Motivated" = "10")
table(smhis26.numeric)
## smhis26.numeric
## 1 2 3 4
## 15 8 15 6
## 5 6 7 8
## 31 14 16 17
## 9 10 Don't Know Refuse to Answer
## 16 40 0 0
## Not Applicable
## 66
smhis26.numeric <- as.numeric(as.character(smhis26.numeric))
## Warning: NAs introduced by coercion
summary(smhis26.numeric)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 1.000 5.000 6.500 6.354 9.000 10.000 69
sd(smhis26.numeric, na.rm=TRUE)
## [1] 2.948429
## Stress Scale
summary(vuln_dt$pss_scre)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 2.00 19.00 21.00 21.82 26.00 39.00 6
sd(vuln_dt$pss_scre, na.rm=TRUE)
## [1] 6.287543
## CES-D
summary(vuln_dt$cesd_scr)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.0 9.0 13.0 12.7 16.0 27.0 4
sd(vuln_dt$cesd_scr, na.rm = TRUE)
## [1] 5.448129
## Health Status
table(vuln_dt$hlth2r)
##
## Poor/Fair Good to Excellent
## 75 169
table(vuln_dt$hlth2r)/n
##
## Poor/Fair Good to Excellent
## 0.3036437 0.6842105
table(vuln_dt$hlth2rb)
##
## Poor/Fair/Good Very Good/Excellent
## 192 52
table(vuln_dt$hlth2rb)/n
##
## Poor/Fair/Good Very Good/Excellent
## 0.7773279 0.2105263
## Family history medical conditions
class(vuln_dt$fhxmeddx)
## [1] "factor"
table(vuln_dt$fhxmeddx, exclude=NA)
##
## No Yes
## 129 118
table(vuln_dt$fhxmeddx)/n
##
## No Yes
## 0.5222672 0.4777328
## health concerns (OPBAIS5):
## "Do you have any concerns about your health because of smoking?"
table(vuln_dt$opbais5, exclude = NULL)
##
## None A little A moderate amount A lot
## 25 89 67 62
## Don't Know Refuse to Answer Not Applicable <NA>
## 1 0 0 3
table(vuln_dt$opbais5, exclude = NULL)/n
##
## None A little A moderate amount A lot
## 0.101214575 0.360323887 0.271255061 0.251012146
## Don't Know Refuse to Answer Not Applicable <NA>
## 0.004048583 0.000000000 0.000000000 0.012145749
## recode as variable ropbais5: RECODE OPBAIS5 (2,1 =0) (4,3=1) INTO ROPBAIS5.
class(vuln_dt$opbais5)
## [1] "factor"
levels(vuln_dt$opbais5)
## [1] "None" "A little" "A moderate amount"
## [4] "A lot" "Don't Know" "Refuse to Answer"
## [7] "Not Applicable"
ropbais5 <- recode(vuln_dt$opbais5,
"None" = "0",
"A little" = "0",
"A moderate amount" ="1",
"A lot" = "1"
)
xtabs(~factor(ropbais5, exclude = NULL) +
factor(vuln_dt$opbais5, exclude = NULL))
## factor(vuln_dt$opbais5, exclude = NULL)
## factor(ropbais5, exclude = NULL) None A little A moderate amount A lot
## 0 25 89 0 0
## 1 0 0 67 62
## Don't Know 0 0 0 0
## <NA> 0 0 0 0
## factor(vuln_dt$opbais5, exclude = NULL)
## factor(ropbais5, exclude = NULL) Don't Know <NA>
## 0 0 0
## 1 0 0
## Don't Know 1 0
## <NA> 0 3
table(ropbais5)/n
## ropbais5
## 0 1 Don't Know Refuse to Answer
## 0.461538462 0.522267206 0.004048583 0.000000000
## Not Applicable
## 0.000000000
## FREQUENCIES VARIABLES = smhis1_6m RACE_ETH GENDER demo4RB smmeddx HLTH2r fhxmeddx FTND2 SMHIS4 SMHIS24 SMHIS26 FPV TRT_GRP scrn7r_b .
## DESCRIPTIVES VARIABLES = AGE HLTH2r FTND2 SMHIS4 SMHIS24 SMHIS26 FPV TRT_GRP scrn7r_b .
################################################################################
#FUNCTION TO COMPUTE SUMMARIES OF REMAINING COLS
################################################################################
printSummaryCols <- function(X){
age.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$age)),
use="complete.obs") #age
race.out <- summary(aov(as.numeric(X) ~ vuln_dt$race_eth)) #race
gender.out <- summary(aov(as.numeric(X) ~ vuln_dt$gender)) #gender
demo4rb.out <- summary(aov(as.numeric(X) ~ vuln_dt$demo4rb)) #education
smmeddx.out <- summary(aov(as.numeric(X) ~ vuln_dt$smmeddx)) #smkg medx
ftnd2.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$ftnd2)),
use="complete.obs") #ciggs prior to ACL
smhis1_original.out <- cor(as.numeric(X),
as.numeric(as.character(vuln_dt$smhis1_original)),
use="complete.obs") #yrs since smoked daily
smhis4.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$smhis4)),
use="complete.obs") # Age started smoking daily
smhis24.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$smhis24)),
use="complete.obs") #readiness to quit
smhis26.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$smhis26)),
use="complete.obs") #motivation
pss_scre.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$pss_scre)),
use="complete.obs") #stress scale
cesd_scr.out <- cor(as.numeric(X), as.numeric(as.character(vuln_dt$cesd_scr)),
use="complete.obs") #ces-d
hlth2rb.out <- summary(aov(as.numeric(X) ~ vuln_dt$hlth2rb)) #health status
fhxmeddx.out <- summary(aov(as.numeric(X) ~ vuln_dt$fhxmeddx)) #family hist
return(c(age.out,
race.out,
gender.out,
demo4rb.out,
smmeddx.out,
ftnd2.out,
smhis1_original.out,
smhis4.out,
smhis24.out,
smhis26.out,
pss_scre.out,
cesd_scr.out,
hlth2rb.out,
fhxmeddx.out))
}
print_summaries_cont <- function(X){
# compute pvals and double check
# corrs for continuous variables
age.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$age)),
use="complete.obs") #age
cat("age: corr = ", age.out$estimate, "p-value = ", age.out$p.value, "\n")
ftnd2.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$ftnd2)),
use="complete.obs") #ciggs prior to ACL
cat("cigs prior to ACI: corr = ", ftnd2.out$estimate, "p-value = ", ftnd2.out$p.value, "\n")
smhis1_original.out <- cor.test(as.numeric(X),
as.numeric(as.character(vuln_dt$smhis1_original)),
use="complete.obs") #yrs since smoked daily
cat("yrs since smoked daily: corr = ", smhis1_original.out$estimate,
"p-value = ", smhis1_original.out$p.value, "\n")
smhis4.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$smhis4)),
use="complete.obs") # Age started smoking daily
cat("age started smoked daily: corr = ", smhis4.out$estimate,
"p-value = ", smhis4.out$p.value, "\n")
smhis24.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$smhis24)),
use="complete.obs") #readiness to quit
cat("readiness to quit: corr = ", smhis24.out$estimate,
"p-value = ", smhis24.out$p.value, "\n")
smhis26.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$smhis26)),
use="complete.obs") #motivation
cat("motivation: corr = ", smhis26.out$estimate,
"p-value = ", smhis26.out$p.value, "\n")
pss_scre.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$pss_scre)),
use="complete.obs") #stress scale
cat("stress scale: corr = ", pss_scre.out$estimate,
"p-value = ", pss_scre.out$p.value, "\n")
cesd_scr.out <- cor.test(as.numeric(X), as.numeric(as.character(vuln_dt$cesd_scr)),
use="complete.obs") #ces-d
cat("ces-d: corr = ", cesd_scr.out$estimate,
"p-value = ", cesd_scr.out$p.value, "\n")
}
compute_n_cont_vars <- function(v, w, df=vuln_dt){
#compute ns of corrs for
#continuous variables
na.v <- which(is.na(v))
na.w <- which(is.na(w))
na.v.and.w <- union(na.v, na.w)
return(nrow(df) - length(na.v.and.w))
}
print_n_cont <- function(v, w, df=vuln_dt){
#print "effective" ns
age.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$age)),
w=w)
cat("age: eff n = ", age.n, "\n")
ftnd2.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$ftnd2)),
w=w)
cat("cigs prior to ACI: eff n = ", ftnd2.n, "\n")
smhis1_original.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$smhis1_original)),
w=w)
cat("yrs since smoked daily: eff n = ", smhis1_original.n, "\n")
smhis4.out.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$smhis4.out)),
w=w)
cat("age started smoking dailyI: eff n = ", smhis4.out.n, "\n")
smhis24.out.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$smhis24.out )),
w=w)
cat("readiness to quit: eff n = ", smhis24.out.n, "\n")
smhis26.out.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$smhis26.out)),
w=w)
cat("motivation: eff n = ", smhis26.out.n, "\n")
pss_scre.out.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$pss_scre.out )),
w=w)
cat("stress scale: eff n = ", pss_scre.out.n, "\n")
cesd_scr.out.n <- compute_n_cont_vars(v=as.numeric(as.character(vuln_dt$cesd_scr.out )),
w=w)
cat("ces-d eff n = ", cesd_scr.out.n, "\n")
}
################################################################################
# COMPUTE SUMMARIES
################################################################################
##perceived future vulnerability
FPV <- vuln_dt$FPV
printSummaryCols(X=FPV)
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## [[1]]
## [1] 0.00181169
##
## [[2]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$race_eth 3 153.2 51.066 3.1604 0.02537 *
## Residuals 237 3829.5 16.158
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[3]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$gender 1 6.8 6.7885 0.4081 0.5236
## Residuals 239 3975.9 16.6354
##
## [[4]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$demo4rb 2 19.3 9.6603 0.5778 0.5619
## Residuals 237 3962.5 16.7193
##
## [[5]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$smmeddx 1 93.9 93.896 5.7708 0.01706 *
## Residuals 239 3888.8 16.271
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[6]]
## [1] 0.1445911
##
## [[7]]
## [1] -0.01019719
##
## [[8]]
## [1] -0.09489258
##
## [[9]]
## [1] -0.1228293
##
## [[10]]
## [1] 0.07327107
##
## [[11]]
## [1] 0.08670143
##
## [[12]]
## [1] 0.1164361
##
## [[13]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$hlth2rb 1 152.6 152.591 9.5218 0.00227 **
## Residuals 239 3830.1 16.025
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[14]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$fhxmeddx 1 96.4 96.380 5.9272 0.01564 *
## Residuals 239 3886.3 16.261
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
print_summaries_cont(X=FPV)
## age: corr = 0.00181169 p-value = 0.9777728
## cigs prior to ACI: corr = 0.1445911 p-value = 0.02478125
## yrs since smoked daily: corr = -0.01019719 p-value = 0.8753849
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis4)), : NAs introduced by coercion
## age started smoked daily: corr = -0.09489258 p-value = 0.1435728
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis24)), : NAs introduced by coercion
## readiness to quit: corr = -0.1228293 p-value = 0.1832511
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis26)), : NAs introduced by coercion
## motivation: corr = 0.07327107 p-value = 0.4244702
## stress scale: corr = 0.08670143 p-value = 0.1825207
## ces-d: corr = 0.1164361 p-value = 0.07177658
print_n_cont(w=FPV)
## age: eff n = 239
## cigs prior to ACI: eff n = 241
## yrs since smoked daily: eff n = 239
## age started smoking dailyI: eff n = 241
## readiness to quit: eff n = 241
## motivation: eff n = 241
## stress scale: eff n = 241
## ces-d eff n = 241
## future precaution
table(as.numeric(vuln_dt$pervul4))
##
## 1 2 3 4 5 6 7
## 10 26 53 133 18 3 1
table(as.numeric(vuln_dt$pervul5))
##
## 1 2 3 4 5 6 8
## 9 23 51 135 20 5 1
table(as.numeric(vuln_dt$pervul6))
##
## 1 2 3 4 5 6 8
## 9 25 56 128 19 6 1
future_precaution <- matrix(cbind(as.numeric(vuln_dt$pervul4),
as.numeric(vuln_dt$pervul5),
as.numeric(vuln_dt$pervul6)),
ncol = 3)
FUTPREC <- apply(future_precaution, 1, mean)
printSummaryCols(X=FUTPREC)
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## [[1]]
## [1] -0.1187524
##
## [[2]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$race_eth 3 3.136 1.04533 1.2942 0.277
## Residuals 240 193.855 0.80773
##
## [[3]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$gender 1 6.043 6.0429 7.6585 0.006087 **
## Residuals 242 190.948 0.7890
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[4]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$demo4rb 2 1.192 0.59603 0.7403 0.4781
## Residuals 240 193.242 0.80518
##
## [[5]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$smmeddx 1 0.505 0.50518 0.6222 0.431
## Residuals 242 196.486 0.81192
##
## [[6]]
## [1] -0.04848875
##
## [[7]]
## [1] 0.08582246
##
## [[8]]
## [1] 0.1030699
##
## [[9]]
## [1] -0.01240651
##
## [[10]]
## [1] 0.007016251
##
## [[11]]
## [1] 0.02582342
##
## [[12]]
## [1] 0.01479429
##
## [[13]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$hlth2rb 1 0.618 0.61767 0.7612 0.3838
## Residuals 242 196.373 0.81146
##
## [[14]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$fhxmeddx 1 0.256 0.25616 0.3151 0.5751
## Residuals 242 196.735 0.81295
print_summaries_cont(X=FUTPREC)
## age: corr = -0.1187524 p-value = 0.06513642
## cigs prior to ACI: corr = -0.04848875 p-value = 0.4508656
## yrs since smoked daily: corr = 0.08582246 p-value = 0.1833114
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis4)), : NAs introduced by coercion
## age started smoked daily: corr = 0.1030699 p-value = 0.1097424
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis24)), : NAs introduced by coercion
## readiness to quit: corr = -0.01240651 p-value = 0.8925642
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis26)), : NAs introduced by coercion
## motivation: corr = 0.007016251 p-value = 0.9386073
## stress scale: corr = 0.02582342 p-value = 0.6899894
## ces-d: corr = 0.01479429 p-value = 0.8185242
print_n_cont(w=FUTPREC)
## age: eff n = 242
## cigs prior to ACI: eff n = 244
## yrs since smoked daily: eff n = 242
## age started smoking dailyI: eff n = 244
## readiness to quit: eff n = 244
## motivation: eff n = 244
## stress scale: eff n = 244
## ces-d eff n = 244
## relative pessimism
table(as.numeric(vuln_dt$opbais1))
##
## 1 2 3 4 5 6 8
## 29 45 98 49 17 5 1
table(as.numeric(vuln_dt$opbais2))
##
## 1 2 3 4 5 6 8
## 26 39 107 46 17 8 1
table(as.numeric(vuln_dt$opbais3))
##
## 1 2 3 4 5 6 8
## 26 44 98 50 16 9 1
rel_pess <- matrix(cbind(as.numeric(vuln_dt$opbais1),
as.numeric(vuln_dt$opbais2),
as.numeric(vuln_dt$opbais3)),
ncol = 3)
RELPESS <- apply(rel_pess, 1, mean)
printSummaryCols(X=RELPESS)
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## [[1]]
## [1] 0.1149278
##
## [[2]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$race_eth 3 1.665 0.55502 0.4338 0.729
## Residuals 240 307.078 1.27949
##
## [[3]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$gender 1 1.30 1.3002 1.0234 0.3127
## Residuals 242 307.44 1.2704
##
## [[4]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$demo4rb 2 0.763 0.38138 0.3013 0.7401
## Residuals 240 303.764 1.26568
##
## [[5]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$smmeddx 1 8.788 8.7877 7.0898 0.008273 **
## Residuals 242 299.956 1.2395
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[6]]
## [1] 0.06563944
##
## [[7]]
## [1] 0.09860434
##
## [[8]]
## [1] -0.08485841
##
## [[9]]
## [1] -0.1612643
##
## [[10]]
## [1] 0.01984565
##
## [[11]]
## [1] 0.1192447
##
## [[12]]
## [1] 0.1342592
##
## [[13]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$hlth2rb 1 4.945 4.9446 3.9388 0.04831 *
## Residuals 242 303.799 1.2554
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[14]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$fhxmeddx 1 0.443 0.4432 0.3479 0.5559
## Residuals 242 308.300 1.2740
print_summaries_cont(X=RELPESS)
## age: corr = 0.1149278 p-value = 0.07433952
## cigs prior to ACI: corr = 0.06563944 p-value = 0.3071798
## yrs since smoked daily: corr = 0.09860434 p-value = 0.1260881
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis4)), : NAs introduced by coercion
## age started smoked daily: corr = -0.08485841 p-value = 0.1882994
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis24)), : NAs introduced by coercion
## readiness to quit: corr = -0.1612643 p-value = 0.07721493
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis26)), : NAs introduced by coercion
## motivation: corr = 0.01984565 p-value = 0.827528
## stress scale: corr = 0.1192447 p-value = 0.06458051
## ces-d: corr = 0.1342592 p-value = 0.03647607
print_n_cont(w=RELPESS)
## age: eff n = 242
## cigs prior to ACI: eff n = 244
## yrs since smoked daily: eff n = 242
## age started smoking dailyI: eff n = 244
## readiness to quit: eff n = 244
## motivation: eff n = 244
## stress scale: eff n = 244
## ces-d eff n = 244
##current vulnerability
printSummaryCols(X=ropbais5)
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## [[1]]
## [1] 0.1620779
##
## [[2]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$race_eth 3 1.753 0.58439 2.3025 0.07773 .
## Residuals 240 60.915 0.25381
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[3]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$gender 1 0.239 0.23858 0.9248 0.3372
## Residuals 242 62.429 0.25797
##
## [[4]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$demo4rb 2 0.126 0.062773 0.242 0.7852
## Residuals 240 62.253 0.259388
##
## [[5]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$smmeddx 1 0.684 0.68369 2.6693 0.1036
## Residuals 242 61.984 0.25613
##
## [[6]]
## [1] 0.01946218
##
## [[7]]
## [1] 0.1362904
##
## [[8]]
## [1] -0.01742725
##
## [[9]]
## [1] 0.09267698
##
## [[10]]
## [1] 0.1378037
##
## [[11]]
## [1] 0.03071973
##
## [[12]]
## [1] 0.04982805
##
## [[13]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$hlth2rb 1 0.591 0.59111 2.3044 0.1303
## Residuals 242 62.077 0.25652
##
## [[14]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$fhxmeddx 1 1.861 1.86053 7.4045 0.006979 **
## Residuals 242 60.808 0.25127
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
print_summaries_cont(X=ropbais5)
## age: corr = 0.1620779 p-value = 0.01156973
## cigs prior to ACI: corr = 0.01946218 p-value = 0.7622888
## yrs since smoked daily: corr = 0.1362904 p-value = 0.03408195
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis4)), : NAs introduced by coercion
## age started smoked daily: corr = -0.01742725 p-value = 0.7873747
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis24)), : NAs introduced by coercion
## readiness to quit: corr = 0.09267698 p-value = 0.311996
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis26)), : NAs introduced by coercion
## motivation: corr = 0.1378037 p-value = 0.1285177
## stress scale: corr = 0.03071973 p-value = 0.6351213
## ces-d: corr = 0.04982805 p-value = 0.4393935
print_n_cont(w=ropbais5)
## age: eff n = 242
## cigs prior to ACI: eff n = 244
## yrs since smoked daily: eff n = 242
## age started smoking dailyI: eff n = 244
## readiness to quit: eff n = 244
## motivation: eff n = 244
## stress scale: eff n = 244
## ces-d eff n = 244
## future pessimism
OPBIAS4R <- vuln_dt$OPBIAS4R
table(OPBIAS4R)
## OPBIAS4R
## Less serious About same More serious
## 34 120 86
OPBIAS4R_2way <- recode(OPBIAS4R,
"Less serious" = "0" ,
"About same" = "0",
"More serious" = "1")
table(OPBIAS4R_2way, exclude = NULL)
## OPBIAS4R_2way
## 0 1 <NA>
## 154 86 7
printSummaryCols(X=OPBIAS4R_2way)
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## Warning in is.data.frame(y): NAs introduced by coercion
## [[1]]
## [1] 0.07927809
##
## [[2]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$race_eth 3 1.413 0.47108 2.0676 0.1052
## Residuals 236 53.770 0.22784
##
## [[3]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$gender 1 0.279 0.27857 1.2075 0.2729
## Residuals 238 54.905 0.23069
##
## [[4]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$demo4rb 2 0.826 0.41276 1.7963 0.1682
## Residuals 236 54.229 0.22978
##
## [[5]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$smmeddx 1 1.740 1.74047 7.7509 0.0058 **
## Residuals 238 53.443 0.22455
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[6]]
## [1] 0.03328334
##
## [[7]]
## [1] 0.1149167
##
## [[8]]
## [1] -0.1886454
##
## [[9]]
## [1] -0.175277
##
## [[10]]
## [1] -0.1228072
##
## [[11]]
## [1] 0.0151374
##
## [[12]]
## [1] 0.1047836
##
## [[13]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$hlth2rb 1 0.980 0.98041 4.3049 0.03908 *
## Residuals 238 54.203 0.22774
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## [[14]]
## Df Sum Sq Mean Sq F value Pr(>F)
## vuln_dt$fhxmeddx 1 0.034 0.034279 0.1479 0.7009
## Residuals 238 55.149 0.231719
print_summaries_cont(X=OPBIAS4R_2way)
## age: corr = 0.07927809 p-value = 0.2230255
## cigs prior to ACI: corr = 0.03328334 p-value = 0.6078999
## yrs since smoked daily: corr = 0.1149167 p-value = 0.07683041
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis4)), : NAs introduced by coercion
## age started smoked daily: corr = -0.1886454 p-value = 0.003486515
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis24)), : NAs introduced by coercion
## readiness to quit: corr = -0.175277 p-value = 0.05763666
## Warning in cor.test.default(as.numeric(X),
## as.numeric(as.character(vuln_dt$smhis26)), : NAs introduced by coercion
## motivation: corr = -0.1228072 p-value = 0.1814615
## stress scale: corr = 0.0151374 p-value = 0.816679
## ces-d: corr = 0.1047836 p-value = 0.1061216
print_n_cont(w=OPBIAS4R_2way)
## age: eff n = 238
## cigs prior to ACI: eff n = 240
## yrs since smoked daily: eff n = 238
## age started smoking dailyI: eff n = 240
## readiness to quit: eff n = 240
## motivation: eff n = 240
## stress scale: eff n = 240
## ces-d eff n = 240
# Compute correlations between the variables ---------------------------
indices <- cbind(FPV, FUTPREC, RELPESS, ropbais5, OPBIAS4R_2way)
cor(FPV, FUTPREC, use="complete.obs")
## [1] 0.1203358
cor.indices <- round(cor(indices, use="complete.obs"), 3)
write.csv(cor.indices, file = "vuln-indices-correlations.csv")
# Save object ---------------------------
save.image(file="table1.RData")