Deciding between the Covariance Analytical Approach and the Change-Score Approach in Two Wave Panel Data

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Standard

Deciding between the Covariance Analytical Approach and the Change-Score Approach in Two Wave Panel Data. / Carmen, Köhler; Hartig, Johannes; Schmid, Christine.
in: Multivariate Behavioral Research, Jahrgang 56, Nr. 3, 21.07.2021, S. 447-458.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Harvard

APA

Vancouver

Carmen K, Hartig J, Schmid C. Deciding between the Covariance Analytical Approach and the Change-Score Approach in Two Wave Panel Data. Multivariate Behavioral Research. 2021 Jul 21;56(3):447-458. Epub 2020 Feb 19. doi: 10.1080/00273171.2020.1726723

Bibtex

@article{6e9c1255dd484238b96b64d0cf83a306,
title = "Deciding between the Covariance Analytical Approach and the Change-Score Approach in Two Wave Panel Data",
abstract = "The manuscript focuses on effects in nonrandomized studies with two outcome measurement occasions and one explanatory variable, and in which groups already differ at the pretest. Such study designs are often encountered in educational and instructional research. Two prominent approaches to estimate effects are (1) covariance analytical approaches and (2) latent change-score models. In current practice, both approaches are applied interchangeably, without a clear rationale for when to use which approach. The aim of this contribution is to outline under which conditions the approaches produce unbiased estimates of the instruction effect. We present a theoretical data generating model in which we decompose the variances of the relevant variables, and examine under which data generating conditions the estimated instruction effect is unbiased. We show that, under specific assumptions, both methods can be used to answer the general question of whether instruction has an effect. Another implication from the results is that practitioners need to consider which underlying data generating assumptions the approaches make, since a violation of those assumptions will lead to biased effects. Based on our results, we give recommendations for preferable research designs.",
keywords = "Educational science, Change-Score Model, conditional model, instruction effect, multilevel SEM",
author = "K{\"o}hler Carmen and Johannes Hartig and Christine Schmid",
note = "Publisher Copyright: {\textcopyright} 2020 Taylor & Francis Group, LLC.",
year = "2021",
month = jul,
day = "21",
doi = "10.1080/00273171.2020.1726723",
language = "English",
volume = "56",
pages = "447--458",
journal = "Multivariate Behavioral Research",
issn = "0027-3171",
publisher = "Psychology Press Ltd",
number = "3",

}

RIS

TY - JOUR

T1 - Deciding between the Covariance Analytical Approach and the Change-Score Approach in Two Wave Panel Data

AU - Carmen, Köhler

AU - Hartig, Johannes

AU - Schmid, Christine

N1 - Publisher Copyright: © 2020 Taylor & Francis Group, LLC.

PY - 2021/7/21

Y1 - 2021/7/21

N2 - The manuscript focuses on effects in nonrandomized studies with two outcome measurement occasions and one explanatory variable, and in which groups already differ at the pretest. Such study designs are often encountered in educational and instructional research. Two prominent approaches to estimate effects are (1) covariance analytical approaches and (2) latent change-score models. In current practice, both approaches are applied interchangeably, without a clear rationale for when to use which approach. The aim of this contribution is to outline under which conditions the approaches produce unbiased estimates of the instruction effect. We present a theoretical data generating model in which we decompose the variances of the relevant variables, and examine under which data generating conditions the estimated instruction effect is unbiased. We show that, under specific assumptions, both methods can be used to answer the general question of whether instruction has an effect. Another implication from the results is that practitioners need to consider which underlying data generating assumptions the approaches make, since a violation of those assumptions will lead to biased effects. Based on our results, we give recommendations for preferable research designs.

AB - The manuscript focuses on effects in nonrandomized studies with two outcome measurement occasions and one explanatory variable, and in which groups already differ at the pretest. Such study designs are often encountered in educational and instructional research. Two prominent approaches to estimate effects are (1) covariance analytical approaches and (2) latent change-score models. In current practice, both approaches are applied interchangeably, without a clear rationale for when to use which approach. The aim of this contribution is to outline under which conditions the approaches produce unbiased estimates of the instruction effect. We present a theoretical data generating model in which we decompose the variances of the relevant variables, and examine under which data generating conditions the estimated instruction effect is unbiased. We show that, under specific assumptions, both methods can be used to answer the general question of whether instruction has an effect. Another implication from the results is that practitioners need to consider which underlying data generating assumptions the approaches make, since a violation of those assumptions will lead to biased effects. Based on our results, we give recommendations for preferable research designs.

KW - Educational science

KW - Change-Score Model

KW - conditional model

KW - instruction effect

KW - multilevel SEM

UR - http://www.scopus.com/inward/record.url?scp=85079776359&partnerID=8YFLogxK

U2 - 10.1080/00273171.2020.1726723

DO - 10.1080/00273171.2020.1726723

M3 - Journal articles

C2 - 32075436

VL - 56

SP - 447

EP - 458

JO - Multivariate Behavioral Research

JF - Multivariate Behavioral Research

SN - 0027-3171

IS - 3

ER -

DOI

Zuletzt angesehen

Forschende

  1. Marco Waage

Publikationen

  1. Pragmatics broadly viewed
  2. Dimensions, dialectic, discourse
  3. Non-acceptances in context
  4. What Role for Public Participation in Implementing the EU Floods Directive? A comparison with the Water Framework Directive, early evidence from Germany, and a research agenda
  5. Contrasting requests in Inner Circle Englishes
  6. Learning Analytics an Hochschulen
  7. From teacher-centered instruction to peer tutoring in the heterogeneous international classroom
  8. Nitrogen uptake by grassland communities
  9. Kommentar zu Ute Tellmann
  10. Operationalizing Network Theory for Ecosystem Service Assessments
  11. Thanking and responding to thanks in American English: Language patterning and contextual appropriateness
  12. Competition in fragmented markets
  13. Mapping the Order of New Migration
  14. Is There a Way Back or Can the Internet Remember its Own History?
  15. Case study: The development of a multi-material heat sink by Additive Manufacturing using Aerosint technology
  16. Synthesis and future research directions linking tree diversity to growth, survival, and damage in a global network of tree diversity experiments
  17. Predicting the future performance of soccer players
  18. Testing for a break in the persistence in yield spreads of EMU government bonds
  19. Deep drawing of high-strength tailored blanks by using tailored tools
  20. Fluorometer controlled apparatus designed for long-duration algal-feeding experiments and environmental effect studies with mussels
  21. An assessment of the published results of animal relocations
  22. Numerical Investigation of the Effect of Rolling on the Localized Stress and Strain Induction for Wire + Arc Additive Manufactured Structures
  23. Diversity of Play
  24. Identification of Parameters and States in PMSMs
  25. Managing information in the case of opinion spamming