analyze.R
In crunch: Crunch.io Data Tools

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library(crunch)
load("vignettes.RData")
options(width=120)

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#  tab1 <- crtabs(~ educ, data=ds)
#  tab1

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tab1

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#  tab2 <- crtabs(~ educ + gender, data=ds)
#  tab2

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tab2

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#  weight(ds)

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print(NULL)

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#  weight(ds) <- ds$weight

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#  crtabs(~ educ + gender, data=ds)

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tab2weighted

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#  crtabs(~ educ + gender, data=ds, weight=NULL)

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tab2

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prop.table(tab1)

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prop.table(tab2, 2)

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round(100*prop.table(tab2, 2))

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#  tab3 <- crtabs(~ imiss + gender, data=ds)
#  tab3

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tab3

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#  ds$imiss <- dichotomize(ds$imiss, c("Very Important", "Somewhat Important"))

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#  tab3mr <- crtabs(~ imiss + gender, data=ds)
#  tab3mr

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tab3mr

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class(tab3mr)

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round(100*prop.table(tab3mr, 2))

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#  crtabs(~ imiss$imiss_f + gender, data=ds)

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tab3subvar

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#  round(crtabs(~ imiss + educ + gender, data=ds))

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round(tab4)

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#  crtabs(mean(age) ~ educ + gender, data=ds)

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tab5

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#  crtabs(min(age) ~ educ + gender, data=ds)

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tab6

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#  crtabs(min(age) ~ 1, data=ds)

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tab6a

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#  categories(ds$track)

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print(track.cats)

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#  round(crtabs(mean(track) ~ educ + gender, data=ds), 2)

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round(tab7, 2)

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#  round(crtabs(mean(track) ~ educ + gender, data=ds[ds$pid3 == "Democrat",]), 2)

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round(tab8, 2)

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#  ds$snowdenleakapp

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cat(snowdenleakapp.var, sep="\n")

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#  ols1 <- lm(I(snowdenleakapp == "Strongly approve") ~ newsint2 + pid3 + gender + age,
#      data=ds)
#  summary(ols1)

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summary(ols1)

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#  logit1 <- glm(I(snowdenleakapp == "Strongly approve") ~ newsint2 + pid3 + gender + age,
#      family=binomial(link="logit"), data=ds)
#  summary(logit1)

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summary(logit1)