2019-05-21 14:19:23 +00:00
```
2019-05-21 14:17:50 +00:00
> colnames(A)[c(7,8)]
[1] "Which.of.these.conditions.have.you.been.formally.diagnosed.with."
[2] "Which.of.these.conditions.do.you.think.you.may.have..but.have.never.been.formally.diagnosed.with."
List_of_Mental_Illnesses = c("Depression","Anxiety", "Obsessive Compulsive Disorder", "Disordered Eating", "Alcoholism", "Drug Addiction", "Borderline Personality Disorder", "Bipolar Disorder", "Autism", "ADHD", "Schizophrenia")
(A[,i])
A$num_mental_ilnesses = integer(l) ## This produces a list of 0s.
i=7
l = 303
for(j in c(1:l)){
for(k in List_of_Mental_Illnesses){
if(grepl(k,A[,i][j])){
A$num_mental_ilnesses[j] = A$num_mental_ilnesses[j]+1
}
}
}
i=8
A$num_mental_ilnesses2 = A$num_mental_ilnesses
for(j in c(1:l)){
for(k in List_of_Mental_Illnesses){
if(grepl(k,A[,i][j])){
A$num_mental_ilnesses2[j] = A$num_mental_ilnesses2[j]+1
}
}
}
A$m_ill_or_not = integer(l)
i=7
for(j in c(1:l)){
for(k in List_of_Mental_Illnesses){
if(grepl(k,A[,i][j])){
A$m_ill_or_not[j] = 1
}
}
}
i=8
A$m_ill_or_not2=A$m_ill_or_not
for(j in c(1:l)){
for(k in List_of_Mental_Illnesses){
if(grepl(k,A[,i][j])){
A$m_ill_or_not2[j] = 1
}
}
}
> sink("readme.txt")
> colnames(A)[c(3:6)]
> summary(lm(A$m_ill_or_not ~ A[,3]))
> summary(lm(A$m_ill_or_not ~ A[,4]))
> summary(lm(A$m_ill_or_not ~ A[,5]))
> summary(lm(A$m_ill_or_not ~ A[,6]))
> A[,3]+((A[,4]=="No")*0 + (A[,4]=="No, but I regularly participate in an EA online group")*1 + (A[,4]=="Yes, occasionally")*2 + (A[,4]=="Yes")*3) +A[,5]+((A[,6]=="No")*0 + A[,6]=="Yes")*1 -> t
> summary(lm(A$m_ill_or_not ~ t))
> summary(lm(A$num_mental_ilnesses ~A[,3]))
> summary(lm(A$num_mental_ilnesses ~A[,4]))
> summary(lm(A$num_mental_ilnesses ~A[,5]))
> summary(lm(A$num_mental_ilnesses ~A[,6]))
> summary(lm(A$num_mental_ilnesses ~t))
> sink()
[1] "How.involved.are.you.in.the.Effective.Altruism.Community."
[2] "Do.you.attend.EA.meetings."
[3] "How.much.impact.do.EA.ideas.have.on.your.life."
[4] "Do.you.donate.part.of.your.income.to.GiveWell.recommended.charities."
Call:
lm(formula = A$m_ill_or_not ~ A[, 3])
Residuals:
Min 1Q Median 3Q Max
-0.4659 -0.4585 -0.4536 0.5415 0.5464
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.468410 0.078905 5.936 8.12e-09 ** *
A[, 3] -0.002477 0.017804 -0.139 0.889
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.4999 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 6.519e-05, Adjusted R-squared: -0.003302
F-statistic: 0.01936 on 1 and 297 DF, p-value: 0.8894
Call:
lm(formula = A$m_ill_or_not ~ A[, 4])
Residuals:
Min 1Q Median 3Q Max
-0.5238 -0.4375 -0.4359 0.5625 0.6667
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.3333 0.2893 1.152 0.250
A[, 4]No 0.1905 0.2961 0.643 0.520
A[, 4]No, but I regularly participate in an EA online group 0.1505 0.3029 0.497 0.620
A[, 4]Yes, occasionally 0.1026 0.2948 0.348 0.728
A[, 4]Yes, often 0.1042 0.2926 0.356 0.722
Residual standard error: 0.501 on 298 degrees of freedom
Multiple R-squared: 0.005741, Adjusted R-squared: -0.007604
F-statistic: 0.4302 on 4 and 298 DF, p-value: 0.7868
Call:
lm(formula = A$m_ill_or_not ~ A[, 5])
Residuals:
Min 1Q Median 3Q Max
-0.4756 -0.4608 -0.4571 0.5392 0.5429
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.479256 0.114810 4.174 3.92e-05 ** *
A[, 5] -0.003696 0.023524 -0.157 0.875
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.5002 on 299 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 8.256e-05, Adjusted R-squared: -0.003262
F-statistic: 0.02469 on 1 and 299 DF, p-value: 0.8753
Call:
lm(formula = A$m_ill_or_not ~ A[, 6])
Residuals:
Min 1Q Median 3Q Max
-0.4758 -0.4520 -0.4520 0.5480 0.5480
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.317e-15 3.530e-01 0.000 1.000
A[, 6]No 4.758e-01 3.558e-01 1.337 0.182
A[, 6]Yes 4.520e-01 3.550e-01 1.273 0.204
Residual standard error: 0.4992 on 300 degrees of freedom
Multiple R-squared: 0.006182, Adjusted R-squared: -0.0004435
F-statistic: 0.9331 on 2 and 300 DF, p-value: 0.3945
Call:
lm(formula = A$m_ill_or_not ~ t)
Residuals:
Min 1Q Median 3Q Max
-0.4891 -0.4565 -0.4469 0.5416 0.5608
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.496827 0.108987 4.559 7.53e-06 ** *
t -0.003841 0.010449 -0.368 0.713
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.4998 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.0004549, Adjusted R-squared: -0.002911
F-statistic: 0.1352 on 1 and 297 DF, p-value: 0.7134
Call:
lm(formula = A$num_mental_ilnesses ~ A[, 3])
Residuals:
Min 1Q Median 3Q Max
-0.8559 -0.8305 -0.8135 1.1441 5.1695
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.864417 0.173834 4.973 1.12e-06 ** *
A[, 3] -0.008484 0.039223 -0.216 0.829
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.101 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.0001575, Adjusted R-squared: -0.003209
F-statistic: 0.04679 on 1 and 297 DF, p-value: 0.8289
Call:
lm(formula = A$num_mental_ilnesses ~ A[, 4])
Residuals:
Min 1Q Median 3Q Max
-1.0476 -0.7692 -0.7422 0.9524 4.9524
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.3333 0.6315 0.528 0.598
A[, 4]No 0.7143 0.6464 1.105 0.270
A[, 4]No, but I regularly participate in an EA online group 0.5699 0.6614 0.862 0.390
A[, 4]Yes, occasionally 0.4359 0.6436 0.677 0.499
A[, 4]Yes, often 0.4089 0.6389 0.640 0.523
Residual standard error: 1.094 on 298 degrees of freedom
Multiple R-squared: 0.01426, Adjusted R-squared: 0.001027
F-statistic: 1.078 on 4 and 298 DF, p-value: 0.3677
Call:
lm(formula = A$num_mental_ilnesses ~ A[, 5])
Residuals:
Min 1Q Median 3Q Max
-0.8445 -0.8336 -0.8117 1.1555 5.1664
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.77898 0.25197 3.092 0.00218 **
A[, 5] 0.01092 0.05163 0.212 0.83263
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.098 on 299 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.0001496, Adjusted R-squared: -0.003194
F-statistic: 0.04474 on 1 and 299 DF, p-value: 0.8326
Call:
lm(formula = A$num_mental_ilnesses ~ A[, 6])
Residuals:
Min 1Q Median 3Q Max
-0.8790 -0.7966 -0.7966 1.1210 5.1210
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.097e-14 7.744e-01 0.000 1.000
A[, 6]No 8.790e-01 7.807e-01 1.126 0.261
A[, 6]Yes 7.966e-01 7.788e-01 1.023 0.307
Residual standard error: 1.095 on 300 degrees of freedom
Multiple R-squared: 0.005158, Adjusted R-squared: -0.001474
F-statistic: 0.7778 on 2 and 300 DF, p-value: 0.4604
Call:
lm(formula = A$num_mental_ilnesses ~ t)
Residuals:
Min 1Q Median 3Q Max
-0.8826 -0.8265 -0.8100 1.1306 5.1636
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.89580 0.24014 3.730 0.000229 ** *
t -0.00660 0.02302 -0.287 0.774576
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.101 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.0002766, Adjusted R-squared: -0.003089
F-statistic: 0.08217 on 1 and 297 DF, p-value: 0.7746
> sink("readme.txt", append=TRUE)
> summary(lm(A$num_mental_ilnesses2 ~A[,3]))
> summary(lm(A$num_mental_ilnesses2 ~A[,4]))
> summary(lm(A$num_mental_ilnesses2 ~A[,5]))
> summary(lm(A$num_mental_ilnesses2 ~A[,6]))
> summary(lm(A$num_mental_ilnesses2 ~t))
> summary(lm(A$m_ill_or_not2 ~A[,3]))
> summary(lm(A$m_ill_or_not2 ~A[,4]))
> summary(lm(A$m_ill_or_not2 ~A[,5]))
> summary(lm(A$m_ill_or_not2 ~A[,6]))
> summary(lm(A$m_ill_or_not2 ~t))
> sink()
Call:
lm(formula = A$num_mental_ilnesses2 ~ A[, 3])
Residuals:
Min 1Q Median 3Q Max
-1.9681 -1.5266 0.1202 1.1202 9.2968
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.05642 0.23945 8.588 5.07e-16 ** *
A[, 3] -0.08830 0.05403 -1.634 0.103
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.517 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.008912, Adjusted R-squared: 0.005575
F-statistic: 2.671 on 1 and 297 DF, p-value: 0.1033
Call:
lm(formula = A$num_mental_ilnesses2 ~ A[, 4])
Residuals:
Min 1Q Median 3Q Max
-2.0159 -1.4766 -0.0159 0.9841 8.9841
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.3333 0.8693 0.383 0.7016
A[, 4]No 1.6825 0.8897 1.891 0.0596 .
A[, 4]No, but I regularly participate in an EA online group 1.6344 0.9104 1.795 0.0736 .
A[, 4]Yes, occasionally 1.3462 0.8858 1.520 0.1297
A[, 4]Yes, often 1.1432 0.8794 1.300 0.1946
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.506 on 298 degrees of freedom
Multiple R-squared: 0.02933, Adjusted R-squared: 0.0163
F-statistic: 2.251 on 4 and 298 DF, p-value: 0.06363
Call:
lm(formula = A$num_mental_ilnesses2 ~ A[, 5])
Residuals:
Min 1Q Median 3Q Max
-2.0011 -1.5848 0.1654 1.1654 9.3319
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.08439 0.34797 5.990 6.01e-09 ** *
A[, 5] -0.08326 0.07130 -1.168 0.244
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.516 on 299 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.004541, Adjusted R-squared: 0.001212
F-statistic: 1.364 on 1 and 299 DF, p-value: 0.2438
Call:
lm(formula = A$num_mental_ilnesses2 ~ A[, 6])
Residuals:
Min 1Q Median 3Q Max
-1.7984 -1.6158 0.2016 1.2016 9.2016
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.878e-15 1.071e+00 0.000 1.0000
A[, 6]No 1.798e+00 1.079e+00 1.666 0.0967 .
A[, 6]Yes 1.616e+00 1.077e+00 1.501 0.1345
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.514 on 300 degrees of freedom
Multiple R-squared: 0.01166, Adjusted R-squared: 0.005067
F-statistic: 1.769 on 2 and 300 DF, p-value: 0.1723
Call:
lm(formula = A$num_mental_ilnesses2 ~ t)
Residuals:
Min 1Q Median 3Q Max
-2.0964 -1.5447 0.1544 1.1544 9.2547
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.19677 0.33090 6.639 1.5e-10 ** *
t -0.05016 0.03172 -1.581 0.115
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 1.518 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.008347, Adjusted R-squared: 0.005008
F-statistic: 2.5 on 1 and 297 DF, p-value: 0.1149
Call:
lm(formula = A$m_ill_or_not2 ~ A[, 3])
Residuals:
Min 1Q Median 3Q Max
-0.7611 -0.6938 0.2658 0.2927 0.3062
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.77453 0.07110 10.894 < 2e-16 ** *
A[, 3] -0.01345 0.01604 -0.839 0.402
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.4504 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.002362, Adjusted R-squared: -0.0009972
F-statistic: 0.7031 on 1 and 297 DF, p-value: 0.4024
Call:
lm(formula = A$m_ill_or_not2 ~ A[, 4])
Residuals:
Min 1Q Median 3Q Max
-0.8710 -0.6875 0.2540 0.3125 0.6667
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.3333 0.2595 1.285 0.2000
A[, 4]No 0.4127 0.2656 1.554 0.1213
A[, 4]No, but I regularly participate in an EA online group 0.5376 0.2718 1.978 0.0488 *
A[, 4]Yes, occasionally 0.3590 0.2644 1.357 0.1757
A[, 4]Yes, often 0.3542 0.2625 1.349 0.1783
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.4495 on 298 degrees of freedom
Multiple R-squared: 0.02254, Adjusted R-squared: 0.009421
F-statistic: 1.718 on 4 and 298 DF, p-value: 0.1459
Call:
lm(formula = A$m_ill_or_not2 ~ A[, 5])
Residuals:
Min 1Q Median 3Q Max
-0.7305 -0.7177 0.2772 0.2798 0.2823
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.733081 0.103298 7.097 9.31e-12 ** *
A[, 5] -0.002572 0.021165 -0.122 0.903
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.45 on 299 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 4.938e-05, Adjusted R-squared: -0.003295
F-statistic: 0.01477 on 1 and 299 DF, p-value: 0.9034
Call:
lm(formula = A$m_ill_or_not2 ~ A[, 6])
Residuals:
Min 1Q Median 3Q Max
-0.7345 -0.7016 0.2655 0.2984 0.2984
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -6.837e-15 3.175e-01 0.000 1.0000
A[, 6]No 7.016e-01 3.200e-01 2.192 0.0291 *
A[, 6]Yes 7.345e-01 3.193e-01 2.300 0.0221 *
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.449 on 300 degrees of freedom
Multiple R-squared: 0.01804, Adjusted R-squared: 0.0115
F-statistic: 2.756 on 2 and 300 DF, p-value: 0.06514
Call:
lm(formula = A$m_ill_or_not2 ~ t)
Residuals:
Min 1Q Median 3Q Max
-0.7515 -0.7072 0.2767 0.2868 0.3009
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.759607 0.098306 7.727 1.71e-13 ** *
t -0.004031 0.009425 -0.428 0.669
---
Signif. codes: 0 ‘ ’ ‘ ’ ‘ ’ ‘ ’ ‘ ’
Residual standard error: 0.4508 on 297 degrees of freedom
(4 observations deleted due to missingness)
Multiple R-squared: 0.0006157, Adjusted R-squared: -0.002749
F-statistic: 0.183 on 1 and 297 DF, p-value: 0.6691
2019-05-21 14:19:23 +00:00
```
