Table 6.18 shows results from the 2000 General Social Survey relating happiness and religious attendance (1 = at most several times a year, 2 = once a month to several times a year, 3 = every week to several times a week). a. Fit a multinomial model. Conduct descriptive and inferential analyses about the association. b. Analyze the model goodness of fit.
Solution
summary(gsSurvey$happy)
table(gsSurvey$happy)
help(table)
table(gsSurvey$happy, useNA=\"ifany\")
table(gsSurvey$religion, useNA=\"ifany\")
table(gsSurvey$religion, useNA=\"always\")
table(gsSurvey$happy, gsSurvey$religion, useNA=\"ifany\")
ggfluctuation(table(gsSurvey$happy, gsSurvey$religion, useNA=\"ifany\"))
table(gsSurvey$happy, gsSurvey$health, useNA=\"ifany\")
ggfluctuation(table(gsSurvey$happy, gsSurvey$health, useNA=\"ifany\"))
library(productplots)
prodplot(data=gsSurvey, ~happy+health, c(\"vspine\", \"hspine\"))
## depends very much on ordering of levels
gsSurvey$health <- factor(gsSurvey$health, levels=c(\"1\", \"2\", \"3\"))
gsSurvey$happy <- factor(gsSurvey$happy, levels=c(\"VERY HAPPY\",\"PRETTY HAPPY\",\"NOT TOO HAPPY\"))
prodplot(data=gsSurvey, ~happy+health, c(\"vspine\", \"hspine\")) + aes(fill=happy)
levels(gsSurvey$happy) <- c(\"VERY HAPPY\",\"PRETTY HAPPY\",\"NOT TOO HAPPY\")
levels(gsSurvey$health) <- c(\"1\", \"2\", \"3\")
prodplot(data=gsSurvey, ~happy+health, c(\"vspine\", \"hspine\")) + aes(fill=happy)
prodplot(data=gsSurvey, ~happy+health, c(\"vspine\", \"hspine\"), na.rm=T) + aes(fill=happy)
.
Table 6-18 shows results from the 2000 General Social Survey relating.docx
1. Table 6.18 shows results from the 2000 General Social Survey relating happiness and religious
attendance (1 = at most several times a year, 2 = once a month to several times a year, 3 = every
week to several times a week). a. Fit a multinomial model. Conduct descriptive and inferential
analyses about the association. b. Analyze the model goodness of fit.
Solution
summary(gsSurvey$happy)
table(gsSurvey$happy)
help(table)
table(gsSurvey$happy, useNA="ifany")
table(gsSurvey$religion, useNA="ifany")
table(gsSurvey$religion, useNA="always")
table(gsSurvey$happy, gsSurvey$religion, useNA="ifany")
ggfluctuation(table(gsSurvey$happy, gsSurvey$religion, useNA="ifany"))
table(gsSurvey$happy, gsSurvey$health, useNA="ifany")
ggfluctuation(table(gsSurvey$happy, gsSurvey$health, useNA="ifany"))
library(productplots)
prodplot(data=gsSurvey, ~happy+health, c("vspine", "hspine"))
## depends very much on ordering of levels
gsSurvey$health <- factor(gsSurvey$health, levels=c("1", "2", "3"))
gsSurvey$happy <- factor(gsSurvey$happy, levels=c("VERY HAPPY","PRETTY
HAPPY","NOT TOO HAPPY"))
prodplot(data=gsSurvey, ~happy+health, c("vspine", "hspine")) + aes(fill=happy)
levels(gsSurvey$happy) <- c("VERY HAPPY","PRETTY HAPPY","NOT TOO HAPPY")
levels(gsSurvey$health) <- c("1", "2", "3")
prodplot(data=gsSurvey, ~happy+health, c("vspine", "hspine")) + aes(fill=happy)
prodplot(data=gsSurvey, ~happy+health, c("vspine", "hspine"), na.rm=T) + aes(fill=happy)
