| Title: | Creating Actuarial Life Tables |
| Version: | 1.0.0 |
| Maintainer: | Grace Rade <grade03426@gmail.com> |
| Description: | Contains data and functions that can be used to make actuarial life tables. Each function adds a column to the inputted dataset for each intermediate calculation between mortality rate and life expectancy. Users can run any of our functions to complete the life table until that step, or run lifetable() to output a full life table that can be customized to remove optional columns. Methods for creating lifetables are as described in Zedstatistics (2021) https://www.youtube.com/watch?v=Dfe59glNXAQ. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Depends: | R (≥ 2.10), dplyr (≥ 1.0.10) |
| LazyData: | true |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), tibble (≥ 3.1.8), htmltools |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| URL: | https://github.com/g-rade/actLifer https://g-rade.github.io/actLifer/ |
| NeedsCompilation: | no |
| Packaged: | 2023-11-16 18:56:39 UTC; grace.rade |
| Author: | Grace Rade  [aut,
cre, cph],
Maeve Tyler-Penny
[aut],
Julia Ting [aut] |
| Repository: | CRAN |
| Date/Publication: | 2023-11-16 21:13:55 UTC |
Central Death Rate
Description
Adds a new column called CentralDeathRate to the dataset that was input. This column represents the central death rate of each age group - deaths/population.
Usage
central_death_rate(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
Value
Data frame that was input with an added CentralDeathRate column.
Examples
# This function adds a CentralDeathRate column to the dataset
central_death_rate(mortality2, "age_group", "population", "deaths")
Conditional Probability of Death at Age x
Description
Adds a new column called ConditionalProbDeath to the dataset that was input. This column represents the probability of death given the age group for each age group. In other words, the probability a person in a given age group will die before their next birthday.
Usage
conditional_death_prob(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable |
age |
The age grouping variable, must be cateogrical |
pop |
Population of each age group, must be numeric |
deaths |
The number of deaths at each age group, must be numeric |
Value
Data frame that was input with an added column, ConditionalProbDeath.
Examples
# This function will add a ConditionalProbDeath column to the dataset
conditional_death_prob(mortality2, "age_group", "population", "deaths")
Conditional Probability of Survival at Age x
Description
Adds a new column called ConditionalProbLife to the dataset that was input. ConditionalProbLife column contains the probabilities of surviving for each given age group. In other words, this is the probability of someone surviving to their next birthday.
Usage
conditional_life_prob(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable |
age |
The age grouping variable, must be cateogrical |
pop |
Population of each age group, must be numeric |
deaths |
The number of deaths at each age group, must be numeric |
Value
Dataset that was input with added columns ConditionalProbDeath and ConditionalProbLife. In other words, we are doing the "steps" up to the conditional probability of survival.
Examples
# This function will add the ConditionalProbDeath and ConditionalProbLife columns
# to the dataset
conditional_life_prob(mortality2, "age_group", "population", "deaths")
Error Handling Function
Description
Checks inputs data, age, pop, and deaths to make sure they are valid.
Usage
input_check(data, age, pop, deaths)
Arguments
data |
data frame input in the upper function |
age |
age string or character input in the upper function |
pop |
pop string or character input in the upper function |
deaths |
deaths string or character input in the upper function |
Value
data frame with numeric pop and deaths columns
Life Expectancy of Age x
Description
Adds a new column called LifeExpectancy to the dataset that was input. LifeExpectancy is how many more years we expect a person of age x to live beyond their current age.
Usage
life_expectancy(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
Value
Dataset that was input with the added columns: ConditionalProbDeath, ConditionalProbLife, NumberToSurvive, PersonYears, TotalYears, and LifeExpectancy.
Examples
# This function will add the ConditionalProbDeath, ConditionalProbLife,
# NumberToSurvive, PropToSurvive, PersonYears, TotalYears, and LifeExpectancy
# columns to the dataset.
# This will be a full lifetable
life_expectancy(mortality2, "age_group", "population", "deaths")
Lifetable Function
Description
Gives user more control over their lifetable compared to the life_expectancy() function. Allows the user to add in the central death rate and proportion surviving to age x. Allows the user to omit accessory columns which are used to calculate life expectancy.
Usage
lifetable(
data,
age,
pop,
deaths,
includeAllSteps = TRUE,
includeCDR = TRUE,
includePS = TRUE,
...
)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
includeAllSteps |
If false, will only include the proportion surviving to age x and life expectancy for age x |
includeCDR |
If true, will include the central death rate for each age group |
includePS |
If true, will include the proportion surviving for each age group |
... |
Other optional grouping variables (can be race, gender, etc.) |
Value
Lifetable
Examples
# Running lifetable() and choosing not to include CentralDeathRate and
# ProportionToSurvive (optional columns) in the output dataset
lifetable(mortality2, "age_group", "population", "deaths", FALSE, TRUE, TRUE)
A sample mortality data
Description
A data extract takes from the CDC Wonder database.
Usage
mortality
Format
A data frame with 85 rows of 3 columns representing the US population at mulit-year different age groups with which we use to make a life table. This data is from the year 2018
- age_group
Categorical variable identifying each age group
- deaths
the mid-year number of deaths in each age group
- population
the US population of each age group
Source
A sample mortality data
Description
A data extract taken from the CDC Wonder database.
Usage
mortality2
Format
A data frame with 85 rows of 3 columns representing the deaths and US population at each single-year age group with which we can use to make a life table. This data is from the year 2016.
- age_group
Categorical variable identifying each age group
- deaths
the mid-year number of deaths in each age group
- population
the US population of each age group
Source
https://wonder.cdc.gov/ucd-icd10.html
A sample mortality data
Description
A data extract taken from the CDC Wonder database.
Usage
mortality3
Format
A data frame with 170 rows of 4 columns representing the deaths and US population at each single-year age group for each sex with which we can use to make a life table. This data is from the year 2016.
- age_group
Categorical variable identifying each age group
- deaths
the mid-year number of deaths in each age group
- population
the US population of each age group
- gender
a categroical variable grouping the data into male and female
Source
<https://wonder.cdc.gov
The Number of People to Survive to Age x
Description
Adds a new column called NumberToSurvive to the dataset that was input. NumberToSurvive represents the number of people living at the beginning of the given age interval, using an arbitrary 100,000 people for the first age group in the table.
Usage
number_to_survive(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
Value
Dataset that was input with added columns: ConditionalProbDeath, ConditionalProbLife, and NumberToSurvive.
Examples
# This function will add the ConditionalProbDeath, ConditionalProbLife, and
# NumberToSurvive columns to the dataset
number_to_survive(mortality2, "age_group", "population", "deaths")
Person Years Lived at Age x
Description
Adds a new column called PersonYears to the dataset that was input. PersonYears represents the number of years lived at age x based on the number surviving to age x.
Usage
person_years(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
Value
Dataset that was input with the added columns: ConditionalProbDeath, ConditionalProbLife, NumberToSurvive, PropToSurvive, PersonYears.
Examples
# This function will add the ConditionalProbDeath, ConditionalProbLife,
# NumberToSurvive, PropToSurvive, and PersonYears columns to the dataset
person_years(mortality2, "age_group", "population", "deaths")
Proportion to Survive to Age x
Description
Adds a new column called PropToSurvive to the dataset that was input. PropToSurvive is the proportion surviving to age x
Usage
prop_to_survive(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
Value
Data frame that was input with columns for steps up to proportion surviving to age x included. That is, the original data with the following added columns: ConditionalProbDeath, ConditionalProbLife, NumberToSurvive, PropToSurvive
Examples
# This function will add the ConditionalProbDeath, ConditionalProbLife,
# NumberToSbrvivem and PropToSurvive columns to the dataset
prop_to_survive(mortality2, "age_group", "population", "deaths")
Total Years Lived From Age x
Description
Adds a new column called TotalYears to the dataset that was input. TotalYears is the number of years lived from age zero to age x.
Usage
total_years_lived(data, age, pop, deaths)
Arguments
data |
The mortality dataset, includes an age grouping variable, |
age |
The age grouping variable, must be categorical |
pop |
Population of each age group, must be numeric |
deaths |
The midyear number of deaths at each age group, must be numeric |
Value
Dataset that was input with the added columns: ConditionalProbDeath, ConditionalProbLife, NumberToSurvive, PersonYears, and TotalYears.
Examples
# This function will add the ConditionalProbDeath, ConditionalProbLife,
# NumberToSurvive, PropToSurvive, PersonYearsm and TotalYears columns to the
# dataset
total_years_lived(mortality2, "age_group", "population", "deaths")