parmsurvfit: Fitting right censored data to parametric distributions.

Description

Executes parametric survival analysis techniques similar to those in 'Minitab'. Fits right censored data to a given parametric distribution, produces summary statistics of the fitted distribution, and plots parametric survival, hazard, and cumulative hazard plots. Produces Anderson-Darling test statistic and probability plots to assess goodness of fit of right censored data to a distribution.

Details

Functions

• fit_data

• surv_summary

• surv_prob

• plot_surv

• plot_haz

• plot_cumhaz

• plot_density

• plot_ppsurv

• compute_AD

Datasets

• aggressive

• firstdrink

• graduate

• oscars

• rearrest

Data on time until drivers honked their horn when being blocked from an intersection

Description

Diekmann et al. (1996) investigated the association between driver characteristics and social status of cars to aggressive driver responses by measuring the time that elapsed between the being blocked and honking the horn. Researchers intentionally blocked 57 motorists at a green light by a Volkswagen Jetta, and recorded the time it took for motorists to show signs of aggression. Signs of aggression included honking their horn or beaming the headlights at the Jetta

Usage

aggressive

Format

A data frame with 57 rows and 2 variables:

seconds

Number of seconds until showing signs of aggression

censor

censoring status indicator variable (0 = censored event time, 1 = complete event time)

Source

https://stats.idre.ucla.edu/other/examples/alda/

Anderson-Darling goodness of fit test statistic

Description

Computes Anderson-Darling goodness of fit test statistic given that the data follows a specified parametric distribution.

Usage

compute_AD(data, dist, time = "time", censor = "censor")

Arguments

Examples

data("rearrest")
compute_AD(rearrest, "lnorm", time = "months")
compute_AD(rearrest, "weibull", time = "months")

Data on age at first drink of alcohol.

Description

Data on age at first drink of alcohol.

Usage

firstdrink

Format

A data frame with 1000 rows and 3 variables:

age

the age at which the survey respondent had their first drink of alcohol

censor

censoring status indicator variable (0 = censored event time, 1 = complete event time)

gender

a dichotomous variable identifying gender (1 = male, 2 = female)

Source

"National Comorbidity Survey (1990-1992)"

Fitting right censored survival data to distribution

Description

Fits right censored data to a distribution using maximum likelihood estimates.

Usage

fit_data(data, dist, time = "time", censor = "censor", by = "")

Arguments

See Also

fitdistcens

Examples

data("rearrest")
fit_data(rearrest, "lnorm", time = "months")

fit_data(rearrest, "weibull", time = "months", by = "personal")

Data on time until graduation for 1000 college students.

Description

A dataset that contains the time (in years) that 1000 students (472 males and 528 females) took to graduate (obtain a bachelor’s degree) from college (measured from the time they entered a post-secondary institution, i.e. either a junior college or four year degree granting institution). The Gender column contains the gender of each student (1 = male, 2 = female), and Censor contains the values of the censoring status variable.

Usage

graduate

Format

A data frame with 1000 rows and 3 variables:

years

years until graduation

censor

censoring status indicator variable (0 = censored event time, 1 = complete event time)

gender

a dichotomous variable identifying gender (1 = male, 2 = female)

Source

National Educational Longitudinal Survey (NELS) from 1988-2002

Data on time until actors receive their first Academy Award nomination

Description

The dataset contains data for the top 128 grossing actors up to 2017 as listed on Box Office Mojo. The data for the first film appearance and for the first Oscar nomination was taken from IMDb. It should be noted that of the 128 observations in the data set, 48 were right-censored. Right-censored observations represent actors who have not received an Oscar nomination by the year 2017 or actors that died before 2017 without ever receiving an Oscar nomination. For the censor variable "1" represents complete observations, actors who received an Oscar nomination by the year 2017, and "0" represents right-censored observations.

Usage

oscars

Format

A data frame with 128 rows and 12 variables:

obs

observation number

name

name of actor

adj_gross

actor's total adjusted gross earnings (in millions)

num_movies

number of movies actor received credit for

avg_gross

actor's average gross earnings per movie

top_movie

title of actor's movie with the top gross earnings

top_gross

actor's top gross earnings from a single movie

gender

actor's gender

years_until_nom

number of years between actor's first full film appearance and first Oscar nomination

censor

censoring status indicator variable (0 = censored event time, 1 = complete event time)

first_film_appearance

year of actor's first full film appearance

first_oscar_nom

year of actor's first Oscar nomination

Source

https://github.com/shannonpileggi/SP–Pablo–RProgramming

Plotting parametric cumulative hazard curves

Description

Plots cumulative hazard curve of right censored data given that it follows a specified parametric distribution.

Usage

plot_cumhaz(data, dist, time = "time", censor = "censor", by = "")

Arguments

Examples

data("rearrest")
plot_cumhaz(rearrest, "lnorm", time = "months")
plot_cumhaz(rearrest, "weibull", time = "months", by = "personal")

Plotting density function overlayed on top of a histogram of data

Description

Creates histogram of right censored data with the density function of a fitted parametric distribution overlayed.

Usage

plot_density(data, dist, time = "time", censor = "censor", by = "")

Arguments

Examples

data("rearrest")
plot_density(rearrest, "exp", time = "months")
plot_density(rearrest, "weibull", time = "months", by = "personal")

Plotting parametric hazard curves

Description

Plots hazard curve of right censored data given that it follows a specified parametric distribution.

Usage

plot_haz(data, dist, time = "time", censor = "censor", by = "")

Arguments

Examples

data("rearrest")
plot_haz(rearrest, "logis", time = "months")
plot_haz(rearrest, "weibull", time = "months", by = "personal")

Plotting percent-percent plots for parametric fitting of data

Description

Creates percent-percent plot of right censored data given that it follows a specified parametric distribution.

Usage

plot_ppsurv(data, dist, time = "time", censor = "censor")

Arguments

Examples

data("rearrest")
plot_ppsurv(rearrest, "weibull", time = "months")
plot_ppsurv(rearrest, "exp", time = "months")

Plotting parametric survival curves

Description

Plots survival curve of right censored data given that it follows a specified parametric distribution.

Usage

plot_surv(data, dist, time = "time", censor = "censor", by = "")

Arguments

Examples

data("rearrest")
plot_surv(rearrest, "lnorm", time = "months")
plot_surv(rearrest, "weibull", time = "months", by = "personal")

Data on time until re-incarceration for 194 inmates.

Description

Henning and Frueh (1996) followed criminal activities of 194 inmates released from a medium security prison for 36 months. The data from this study can be used to investigate the time until the former inmates were re-arrested. If the former inmate had been re-arrested for a criminal act before 36 months (after initial prison release) had passed, then that former inmate’s event time was complete. If the former inmate had not been re-arrested for a criminal act after 36 months had passed, or had completely dropped out of the study, then that former inmate’s event time was right censored.

Usage

rearrest

Format

A data frame with 194 rows and 5 variables:

months

months until re-arrest

censor

censoring status indicator variable (0 = censored event time, 1 = complete event time)

personal

a dichotomous variable identifying former inmates who had a history of person-related crimes (1 = personal), i.e. those with one or more convictions for offenses such as aggravated assault or kidnapping

property

a dichotomous variable indicating whether former inmates were convicted of a property-related crime (1 = property)

cenage

the "centered" age of individual, i.e. the difference between the age of the individual upon release and the average age of all inmates in the study.

Source

https://stats.idre.ucla.edu/other/examples/alda/

Survival probability based on parametric distribution

Description

Computes probability of survival beyond time t given that the data follows a specified parametric distribution.

Usage

surv_prob(data, dist, x, lower.tail = F, time = "time",
  censor = "censor", by = "")

Arguments

Examples

data("rearrest")
surv_prob(rearrest, "lnorm", 110, time = "months")
surv_prob(rearrest, "weibull", 90, time = "months", lower.tail = TRUE)

Summary statistics based on parametric distribution

Description

Estimates various statistics, including median, mean, standard deviation, and percentiles of survival time given that the data follows a specified parametric distribution.

Usage

surv_summary(data, dist, time = "time", censor = "censor", by = "")

Arguments

Examples

data("rearrest")
surv_summary(rearrest, "lnorm", time = "months")
surv_summary(rearrest, "weibull", time = "months", by = "personal")