| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document Help

Title:Omissions by design in a survey : is this a good choice when using Structural Equation Models?
Authors:ID Ribeiro Vicente, Paula Cristina (Author)
Files:URL https://sciendo.com/article/10.2478/ngoe-2024-0018
 
.pdf RAZ_Ribeiro_Vicente_Paula_Cristina_2024.pdf (548,29 KB)
MD5: D5841ED0614B991B9F005ECB009A8B19
 
Language:English
Work type:Review
Typology:1.01 - Original Scientific Article
Organization:EPF - Faculty of Business and Economics
Abstract:Missing observations can arise due to the effort required to answer many questions in long surveys and the cost required to obtain some responses. Implementing a planned missing design in surveys helps reduce the number of questions each respondent needs to answer, thereby lowering survey fatigue and cutting down on implementation costs. The three-form and the two-method design are two different types of planned missing designs. An important consideration when designing a study with omissions by design is to know how it will affect statistical results. In this work, a simulation study is conducted to analyze how the usual fit measures, root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker-Lewis index (TLI) perform in the adjustment of a Structural Equation Model. The results revealed that the CFI, TLI, and SRMR indices exhibit sensitivity to omissions with small samples, low factor loadings and large models. Overall, this study contributes to our understanding of the importance of considering omissions by design in market research.
Keywords:omissions by design, Structural Equation Model, survey
Publication status:Published
Publication version:Version of Record
Publication date:06.10.2024
Year of publishing:2024
Number of pages:str. 83-91
Numbering:Vol. 70, no. 3
PID:20.500.12556/DKUM-93029 New window
UDC:303.425
ISSN on article:0547-3101
COBISS.SI-ID:237928963 New window
DOI:10.2478/ngoe-2024-0018 New window
Publication date in DKUM:02.06.2025
Views:252
Downloads:11
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
Copy citation
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share



Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Record is a part of a journal

Title:Naše gospodarstvo : revija za aktualna gospodarska vprašanja
Shortened title:Naše gospod.
Publisher:Ekonomsko-poslovna fakulteta, Društvo ekonomistov Maribor, Ekonomski center Maribor
ISSN:0547-3101
COBISS.SI-ID:751364 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Title:Načrtovane opustitve opazovanj v raziskavi : ali je to dobra izbira pri uporabi modelov strukturnih enačb?
Abstract:Manjkajoča opazovanja se lahko pojavijo zaradi napora, potrebnega za odgovarjanje na številna vprašanja v dolgih anketah, in stroškov, ki so potrebni za pridobitev nekaterih odgovorov. Izvajanje načrtovane zasnove manjkajočih opazovanj v anketah pomaga zmanjšati količino vprašanj, na katera mora odgovoriti vsak anketiranec, s čimer se zmanjša utrujenost anketirancev in zmanjšajo stroški izvajanja. Načrt s tremi oblikami in načrt z dvema metodama sta dve različni vrsti načrtovanih manjkajočih opazovanj. Pomemben vidik pri načrtovanju raziskave z načrtovanimi opustitvami je vedeti, kako bo to vplivalo na statistične rezultate. V tem članku je izvedena simulacijska študija, da bi analizirali, kako se običajna merila ustreznosti, kvadratni koren povprečne kvadrirane napake ocen (angl. root mean square error of approximation - RMSEA), standardizirani kvadratni koren povprečja kvadriranih ostankov (angl. standardized root mean square residual - SRMR), primerjalna mera prileganja (angl. comparative fit index - CFI) in Tucker-Lewisov indeks (TLI), obnesejo pri prilagoditvi modela strukturnih enačb. Rezultati so pokazali, da indeksi CFI, TLI in SRMR kažejo občutljivost na izpuste pri majhnih vzorcih, nizkih faktorskih obremenitvah in velikih modelih. Na splošno ta študija prispeva k našemu razumevanju pomena upoštevanja opustitev opazovanj pri načrtovanju tržnih raziskav.
Keywords:opustitve opazovanj pri načrtovanju, model strukturnih enačb, anketa


Collection

This document is a part of these collections:
  1. Naše gospodarstvo

Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica