Discussion_14

library(tidyverse)

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library(faraway)

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library(lme4)

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Example for Discussion_14.

Reading data psid.txt:

psid <- read.delim("./psid.txt", header = TRUE)
attach(psid)
head(psid)

##   age educ sex income year person
## 1  31   12   M   6000   68      1
## 2  31   12   M   5300   69      1
## 3  31   12   M   5200   70      1
## 4  31   12   M   6900   71      1
## 5  31   12   M   7500   72      1
## 6  31   12   M   8000   73      1

ggplot of 20 subjects revealed that some individuals have a slowly increasing income, specially if having steady employment in the same job.

psid20 <- filter(psid, person <= 20)
library(ggplot2)
ggplot(psid20, aes(x=year, y=income))+geom_line()+facet_wrap(~ person)

I found this one specially interesting, because it shows pattern of difference between men’s and women’s incomes.

ggplot(psid20, aes(x=year, y=income+100, group=person)) +geom_line() + facet_wrap(~ sex) + scale_y_log10()