nunosempere.github.io/rat/eamentalhealth/analysis/regressions_EA_mental_health.md

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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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

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

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