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Financial Marginalization and Cryptocurrency before Reddit post
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2 changed files with 49 additions and 49 deletions
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@ -116,11 +116,11 @@ SHED$crypto.used.as.payment <- SHED$S16_b == "Yes"
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# Do you and/or your spouse or partner
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# currently have a checking, savings or money
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# market account?
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SHED$does.not.have.bank.account <- SHED$BK1 == "No"
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SHED$lacks.bank.account <- SHED$BK1 == "No"
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# C2A
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# Do you currently have at least one credit card?
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SHED$does.not.have.credit.card <- SHED$C2A == "No"
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SHED$lacks.credit.card <- SHED$C2A == "No"
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# ppgender
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# Gender [Ipsos source]
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@ -308,7 +308,7 @@ SHED <- svydesign(ids = ~0, data = SHED, weights = SHED$weight_pop)
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svyvar.covariance <- svyvar(~ age + is.male + crypto.used.as.payment +
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does.not.have.bank.account + does.not.have.credit.card, SHED, na.rm = TRUE)
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lacks.bank.account + lacks.credit.card, SHED, na.rm = TRUE)
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attr(svyvar.covariance, "var") <- NULL
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svyvar.correlation <- cov2cor(as.matrix(svyvar.covariance))
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@ -316,29 +316,29 @@ print(round(svyvar.correlation, 3))
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corrplot(svyvar.correlation, tl.col = "darkred", tl.srt = 35,
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method = "shade", number.digits = 2, addshade = "all", diag = FALSE,
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title = "\n\n Correlation Plot",
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title = "\n\n Correlation Matrix of Financial Marginalization\nand Use of Cryptocurrency as a Means of Payment",
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addCoef.col = "black", type = "lower")
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```
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# Main results
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## does.not.have.bank.account
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## lacks.bank.account
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```{r main-results-does-not-have-bank-account}
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```{r main-results-lacks-bank-account}
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svyglm.fit <- svyglm(crypto.used.as.payment ~ age + is.male + does.not.have.bank.account,
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svyglm.fit <- svyglm(crypto.used.as.payment ~ age + is.male + lacks.bank.account,
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SHED, family = stats::quasibinomial(link = "logit"))
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summary(svyglm.fit)
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or_svyglm(SHED$variables$variables, svyglm.fit, incr = list(age = 1))
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or_svyglm(SHED$variables, svyglm.fit, incr = list(age = 1))
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```
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## does.not.have.credit.card
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## lacks.credit.card
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```{r main-results-does-not-have-credit-card}
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```{r main-results-lacks-credit-card}
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svyglm.fit <- svyglm(crypto.used.as.payment ~ age + is.male + does.not.have.credit.card,
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svyglm.fit <- svyglm(crypto.used.as.payment ~ age + is.male + lacks.credit.card,
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SHED, family = stats::quasibinomial(link = "logit"))
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summary(svyglm.fit)
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or_svyglm(SHED$variables, svyglm.fit, incr = list(age = 1))
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