A comparison of generalised linear models and compositional models for ordered categorical data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F20%3A73596479" target="_blank" >RIV/61989592:15310/20:73596479 - isvavai.cz</a>

Výsledek na webu

<a href="https://journals.sagepub.com/doi/epub/10.1177/1471082X18816540" target="_blank" >https://journals.sagepub.com/doi/epub/10.1177/1471082X18816540</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1177/1471082X18816540" target="_blank" >10.1177/1471082X18816540</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A comparison of generalised linear models and compositional models for ordered categorical data

Popis výsledku v původním jazyce

Ordered categorical data occur in many applied fields, such as geochemistry, econometrics, sociology and demography or even transportation research, for example, in the form of results from various questionnaires. There are different possibilities for modelling proportions of individual categories. Generalised linear models (GLMs) are traditionally used for this purpose, but also methods of compositional data analysis (CoDa) can be considered. Here, both approaches are compared in depth. Particularly, different assumptions of the models on variability are highlighted. Advantages and disadvantages of individual models are pointed out. While the CoDa model may be inappropriate when the variability of the compositional coordinates depends on the regressors, for example, due to different total counts on which the coordinates are based, the GLM may underestimate the uncertainty of the predictions considerably in case of large-scale data.

Název v anglickém jazyce

A comparison of generalised linear models and compositional models for ordered categorical data

Popis výsledku anglicky

Ordered categorical data occur in many applied fields, such as geochemistry, econometrics, sociology and demography or even transportation research, for example, in the form of results from various questionnaires. There are different possibilities for modelling proportions of individual categories. Generalised linear models (GLMs) are traditionally used for this purpose, but also methods of compositional data analysis (CoDa) can be considered. Here, both approaches are compared in depth. Particularly, different assumptions of the models on variability are highlighted. Advantages and disadvantages of individual models are pointed out. While the CoDa model may be inappropriate when the variability of the compositional coordinates depends on the regressors, for example, due to different total counts on which the coordinates are based, the GLM may underestimate the uncertainty of the predictions considerably in case of large-scale data.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

STATISTICAL MODELLING

ISSN

1471-082X

e-ISSN

1477-0342

Svazek periodika

20

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

25

Strana od-do

249-273

Kód UT WoS článku

000532435800002

EID výsledku v databázi Scopus

2-s2.0-85060626313