12-case-study-wages.Rmd

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knit: bookdown::preview_chapter
---

# Wages

The main purpose of this chapter is to describe working with longitudinal data. Here's the outline:

- Using old wages data
    - Making the standard plots, to examine overall trend, focus on policy decisions
    - Computing features for each subject, focus on the individual, and opportunity for a person to see how they fit  in the story
    - GLM  fit and diagnostics

- New wages data ()
    - Data collection process and choices: can refer to yowie package
    - Finding errors in data?
    - Repeat some oof earlier plots with this new data, maybe with complete cases

```{r}
library(brolgar)
wages %>%
  sample_n_keys(size = 5) %>%
  ggplot(aes(x = xp,
             y = ln_wages,
             group = id)) + 
  geom_line()
```

## New  wages data

```{r}
load("data/wages_hs2020_complete.rda")
wages_hs2020_complete %>%
  ggplot() +
  geom_line(aes(x = year,
                y = mean_hourly_wage,
                group = id)) +
  facet_wrap(~race) +
  geom_smooth(aes(x = year,
              y = mean_hourly_wage))
wages_hs2020_complete %>%
  ggplot() +
  geom_smooth(aes(x = year,
                  y = mean_hourly_wage, colour=race), se=FALSE)
```