Dolphins

Survival analysis

Notable topics: Survival analysis

Recorded on: 2018-12-17

Timestamps by: Alex Cookson

## Screencast

## Timestamps

Using year function from lubridate package to simplify calculating age of dolphins

Combining count and fct_lump functions to get counts of top 5 species (with other species lumped in "Other")

Creating boxplot of species and age

Dealing with different types of NA (double, logical) (he doesn't get it in this case, but it's still useful)

Adding acquisition type as colour dimension to histogram

Creating a spinogram of acquisition type over time (alternative to histogram) using geom_area

Binning year into decade using truncated division operator %/%

Fixing annoying triangular gaps in spinogram using complete function to fill in gaps in data

Using fct_reorder function to reorder acquisition type (bigger categories are placed on the bottom of the spinogram)

Adding vertical dashed reference line using geom_vline function

Starting analysis of acquisition location

Matching messy text data with regex to aggregate into a few categories variables with fuzzyjoin package

Using distinct function's .keep_all argument to keep only one row per animal ID

Using coalesce function to conditionally replace NAs (same functionality as SQL verb)

Starting survival analysis

Using survfit function from survival package to get a baseline survival curve (i.e., not regressed on any independent variables)

Fixing cases where death year is before birth year

Fixing specification of survfit model to better fit the format of our data (right-censored data)

Built-in plot of baseline survival model (estimation of percentage survival at a given age)

Using broom package to tidy the survival model data (which is better for ggplot2 plotting)

Fitting survival curve based on sex

Cox proportional hazards model (to investigate association of survival time and one or more predictors)

Explanation of why dolphins with unknown sex likely have a systematic bias with their data

Investigating whether being born in captivity is associated with different survival rates

Summary of screencast