R Dataset / Package COUNT / titanicgrp

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Correlation Coefficient

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Regression

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<iframe src="https://embed.picostat.com/r-dataset-package-count-titanicgrp.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-22866.csv 184 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the titanicgrp data set which pertains to titanicgrp. The titanicgrp data set is found in the COUNT R package. You can load the titanicgrp data set in R by issuing the following command at the console data("titanicgrp"). This will load the data into a variable called titanicgrp. If R says the titanicgrp data set is not found, you can try installing the package by issuing this command install.packages("COUNT") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the titanicgrp R data set. The size of this file is about 184 bytes.

Documentation

titanicgrp

Description

The data is an grouped version of the 1912 Titanic passenger survival log,

Usage

data(titanicgrp)

Format

A data frame with 12 observations on the following 5 variables.

survive

number of passengers who survived

cases

number of passengers with same pattern of covariates

age

1=adult; 0=child

sex

1=Male; 0=female

class

ticket class 1= 1st class; 2= second class; 3= third class

Details

titanicgrp is saved as a data frame. Used to assess risk ratios

Source

Found in many other texts

References

Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Hilbe, Joseph M (2009), Logistic Regression Models, Chapman & Hall/CRC

Examples

library(MASS)
library(msme)
data(titanicgrp)
glmlr <- glm(survive ~ age + sex + factor(class) + offset(log(cases)),
             family=poisson, data=titanicgrp)
summary(glmlr)
exp(coef(glmlr))lcases <- titanicgrp$cases
nb2o <- nbinomial(survive ~ age + sex + factor(class), 
                                        formula2 =~ age + sex,
                                        offset = lcases,
                                        mean.link="log",
                                        scale.link="log_s",
                                        data=titanicgrp)
summary(nb2o)
exp(coef(nb2o))
--

Dataset imported from https://www.r-project.org.

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