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Title: Graphical Check for Proportional Odds Assumption
Version: 0.1.1
Description: Implements the method described at the UCLA Statistical Consulting site https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/ for checking if the proportional odds assumption holds for a cumulative logit model.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
Imports: dplyr, tidyr (≥ 1.0.0), ggplot2, assertthat, stats, rlang, magrittr, stringr
Depends: R (≥ 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-06-06 00:08:55 UTC; melissa
Author: Melissa Wong ORCID iD [aut, cre]
Maintainer: Melissa Wong <melissa.wong.stats@gmail.com>
Repository: CRAN
Date/Publication: 2021-06-06 04:10:02 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

lhs

A value or the magrittr placeholder.

rhs

A function call using the magrittr semantics.

Value

The result of calling rhs(lhs).


National Health and Nutrition Examination Survey 2011-2012

Description

A dataset used in the UCLA Statistical Consulting Survey Analysis in R guide https://stats.idre.ucla.edu/r/seminars/survey-data-analysis-with-r/

Usage

nhanes

Format

A data frame with 9756 rows and 16 variables:

seqn

Respondent sequence number

ridageyr

Age in years at screening

riagendr

Gender

dmdmartl

Marital status

dmdeduc2

Education level - Adults 20+

sdmvpsu

Masked variance pseudo-PSU

sdmvstra

Masked variance pseudo-stratum

wtint2yr

Full sample 2 year interview weight

female

Gender

hsq496

How many days feel anxious

hsq571

SP donated blood in the past 12 months

hsd010

General health condition

pad630

Minutes moderate-intensity work

pad675

Minutes moderate recreational activities

paq665

Moderate recreational activities

pad680

Minutes sedentary activity

Source

https://wwwn.cdc.gov/nchs/nhanes/Search/DataPage.aspx?Component=Demographics&CycleBeginYear=2011


Simulated data for ordinal logistic regression example.

Description

A dataset used in the UCLA Statistical Consulting Ordinal Logistic Regression Example https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/

Usage

ologit

Format

A data frame with 400 rows and 4 variables:

apply

Likelihood of applying to graduate school

pared

Indicator for whether at least 1 parent has a graduate degree

public

Indicator for whether undergraduate institution is public or private

gpa

Student's grade point average

Source

https://stats.idre.ucla.edu/stat/data/ologit.dta


Graphical check for proportional odds assumption

Description

Generates the plots described in https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/ for checking if the proportional odds assumption holds for a cumulative logit model.

Usage

## S3 method for class 'pomcheck'
plot(x, legend.position = "none", ...)

Arguments

x

a pomcheck object

legend.position

the position of legends ("none", "left", "right", "bottom", "top", or two-element numeric vector)

...

currently unused

Value

None

See Also

pomcheck

Examples

plot(pomcheck(Species ~ Sepal.Width, iris))

Graphical check for proportional odds assumption

Description

Implements the method described in https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/ for checking if the proportional odds assumption holds for a cumulative logit model.

Usage

pomcheck(object, ...)

## Default S3 method:
pomcheck(object, x, data, ...)

## S3 method for class 'formula'
pomcheck(formula, data, ...)

Arguments

object

character string for response

...

currently unused

x

vector of character string(s) for explanatory variable(s)

data

data frame containing the variables

formula

formula of the form y ~ x1 + x2 + ...

Value

an object of class 'pomcheck'

Methods (by class)

See Also

plot.pomcheck

Examples

pomcheck(Species ~ Sepal.Length, iris)
pomcheck(Species ~ Sepal.Length + Sepal.Width, iris)
pomcheck(object="Species", x="Sepal.Length", iris)
pomcheck(object="Species", x=c("Sepal.Length", "Sepal.Width"), iris)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.